That attention is a positive step forward. New solutions are bringing greater visibility to smartphones and mobile devices, helping IT teams understand factors like battery health, connectivity, device performance, and overall mobile fleet health. 

But as mobile work becomes more business-critical, the bar for Mobile DEX is rising. Visibility into the device is important, but it is only part of the story. 

For organizations whose business depends on mobile devices, from retail stores and hospitals to logistics hubs and field operations, the real opportunity is to understand whether employees can complete critical work without disruption. 

For these organizations, Mobile DEX is no longer just about monitoring devices. It is about protecting the workflows those devices enable. 

Mobile Devices Now Power Critical Workflows 

Across frontline and mobile-first environments, mobile devices have become the connective tissue of critical work. They support the workflows employees rely on to serve customers, care for patients, move goods, inspect assets, and keep operations running. 

In these environments, a mobile device is far more than an endpoint. It may be the point of sale on a retail floor, the clinical workstation at a patient鈥檚 bedside, the scanner in a distribution center, the inspection tool in the field, or the communication hub inside a manufacturing facility. 

When those devices fail, or when the applications and networks supporting them fail, the impact is immediate. Operations slow down. Productivity drops. Customers wait. Revenue, service levels, and employee experience are all affected. 

That reality changes the question organizations need Mobile DEX to answer. 

The question is not simply: Is the device healthy? 

The real question is: Can work actually get done? 

Mobile Visibility Is the Starting Point, Not the Finish Line 

Many mobile monitoring solutions focus on the signals that are easiest to collect, such as device inventory, battery health, connectivity status, and basic telemetry. 

Those signals are useful, but they rarely explain why employees are struggling to complete work. 

A device can show healthy battery levels, normal memory consumption, and strong connectivity while still delivering a frustrating user experience. 

The issue may show up as a POS terminal slowing during peak checkout, a clinical application lagging during patient care, a field worker losing connectivity before completing a critical update, or a warehouse scanner experiencing intermittent service delays. 

In each case, the problem extends beyond the device itself. 

It reflects the interaction between the device, the application, the network, the user, and the workflow being performed. 

Looking at any one layer in isolation rarely gives IT enough context to understand the root cause or resolve the issue quickly. 

Modern Mobile DEX Must Connect Experience to Outcomes 

As the market matures, organizations are looking for Mobile DEX solutions that go beyond visibility and help them understand how mobile experience affects the business. 

They need to know how application performance affects frontline productivity, how network conditions impact critical tasks, how mobile experiences influence employee satisfaction, and how experience issues affect operational outcomes. 

Most importantly, they need to act on those insights. Visibility alone creates awareness. Visibility connected to operational workflows creates outcomes. 

Aternity Mobile: Built for How Work Happens Today 

麻豆学生精品版 Aternity Mobile is built around a different objective: helping organizations prevent disruption before it affects employees, customers, and operations. 

That requires a more complete, connected view of mobile experience across the environments where work happens. 

Correlated Experience Visibility 

Aternity Mobile brings device health, application performance, and network conditions together into a single correlated view. 

Instead of troubleshooting isolated symptoms, IT teams can see how mobile experience affects real-world workflows, employee productivity, and operational performance. 

Coverage Beyond Smartphones 

Enterprise mobility extends far beyond traditional smartphones. Organizations increasingly rely on rugged mobile devices, shared workforce devices, kiosks, POS systems, ChromeOS devices, and specialty operational endpoints. 

Aternity Mobile provides visibility across the broad range of devices that support frontline and mobile-first operations, not just personal mobile devices. 

Real-Time Insights and Diagnostics 

Detecting issues is only the beginning. Aternity Mobile helps IT teams identify real-time health events and investigate problems using context-rich diagnostics that accelerate troubleshooting and improve root-cause analysis. 

From Visibility to Action 

For many IT teams, the challenge is not finding issues. It is resolving them quickly enough to avoid disruption. 

Aternity Mobile helps organizations connect mobile experience insights directly into operational processes, including automated incident creation, ITSM integration, context-rich triage data, remediation workflows, and user feedback loops. 

That connection helps reduce manual effort, accelerate resolution, and minimize disruption to business-critical workflows. 

Coverage Matters. Data Quality Matters More. 

As mobile environments become more diverse, organizations must support a growing mix of corporate-owned devices, shared devices, frontline endpoints, specialty hardware, and operational systems. 

The challenge is not simply collecting more data. It is collecting consistent, actionable data that teams can trust to guide decisions and support remediation. 

High-fidelity visibility across mobile environments enables organizations to troubleshoot faster, optimize workflows more effectively, and improve the experience for employees and customers. 

The Future of Mobile DEX Is Workflow Continuity 

The next phase of Mobile DEX will not be defined by who collects the most telemetry. It will be defined by who can connect mobile experiences to operational outcomes. 

Organizations increasingly expect Mobile DEX solutions to help them prevent disruption, accelerate issue resolution, improve employee productivity, support frontline operations, and optimize business workflows. 

In other words, the future is not about monitoring devices. It is about keeping work moving. 

The Bottom Line 

Mobile devices have become the primary workspace for millions of employees. As organizations continue investing in mobile-first operations, they need solutions that move beyond device health and visibility alone. 

Aternity Mobile helps organizations understand, optimize, and protect mobile experiences across devices, applications, networks, and workflows while connecting insights to the operational processes required to resolve issues faster. 

Because in today鈥檚 mobile-first world, success is not measured by visibility alone. It is measured by whether work continues without disruption. 

See Aternity Mobile in action and learn how organizations are preventing disruption across frontline and mobile-first environments. Watch the video.

We are excited to announce significant expansion of 麻豆学生精品版 Data Express capabilities, extending support for a broader range of cloud-to-cloud migration and replication scenarios. In addition, 麻豆学生精品版 Data Express is now available through the , providing Oracle Cloud Infrastructure (OCI) customers with an easy way to discover and deploy Data Express as part of their cloud data mobility strategy. This is in addition to a without even the need of a credit card.

Expanding Data Mobility Across Leading Cloud 麻豆学生精品版s

Data Express has been designed to simplify large-scale data movement while maximizing throughput and minimizing transfer times. With this latest expansion, organizations can now move data across a wider range of cloud environments, including:

OCI Regional Data Movement

For organizations operating across multiple OCI regions, tenants, or business units, Data Express now supports OCI-to-OCI regional transfers. This capability helps teams:

• Accelerate region-to-region migrations
• Support disaster recovery planning
• Consolidate storage environments
• Enable data placement closer to applications and users

All global OCI regions are available for service, enabling large data movement for projects such as Singapore to US-East, UAE to Frankfurt, with consistent performance, secure data transfers and enterprise-grade controls. Whether you’re expanding globally or modernizing existing infrastructure, OCI-to-OCI transfers become faster and easier.

AWS Regional Data Movement

As AWS deployments grow, organizations frequently need to move data between accounts, regions, or storage architectures. With AWS-to-AWS regional transfer support, Data Express enables:

• Cross-region data migration
• Storage consolidation projects
• Backup and recovery workflows
• Data relocation for compliance and governance requirements

Large-scale object transfers can now be completed with greater speed and operational efficiency.

For AWS data movement operations available across the globe, Data Express brings the benefit of high-rate transfers across the AWS backbone, with reduced inter-regional charges vs other approaches through accelerated data movement capabilities

AWS OCI

Multi-cloud is no longer an exception. It is rapidly becoming the norm. Data Express now supports bi-directional transfers between:

AWS to OCI and OCI to AWS

This capability enables organizations to:

• Migrate workloads from AWS to  Oracle Cloud Infrastructure or vice-versa
• Replicate data across cloud providers
• Support hybrid and multi-cloud architectures
• Optimize cloud spending by placing data where it delivers the most value
• Build AI and analytics pipelines that span multiple cloud ecosystems

By eliminating barriers between AWS and OCI storage environments, enterprises gain the flexibility to choose the right cloud for every workload.

The AWS to OCI data movement service utilizes high-speed interconnections with reduced inter-connect data transfer charges. Data transfer rates of up to 50 TB/hour, yielding more than 1PB per day are available for AWS to/from OCI data movements, making large data transfers a routine operation for large scale AI or business operations. The service is available immediately for US locations and can be activated for any global region within a short window upon request.

Azure Regional Data Movement

Microsoft Azure customers can now take advantage of Azure-to-Azure data mobility capabilities for:

• Regional migrations
• Storage modernization projects
• Business continuity planning
• Environment consolidation

As Azure footprints expand, Data Express helps ensure data can move efficiently without creating operational bottlenecks.

Why This Matters

Data is the foundation of modern digital initiatives but moving it at scale remains one of the biggest challenges facing IT teams. Traditional transfer methods often struggle with:

• Long migration windows
• Network inefficiencies
• Operational complexity
• Rising egress and infrastructure costs
• Risk of business disruption

Data Express addresses these challenges by providing high-performance data movement designed for enterprise-scale cloud environments.

The result is faster migrations, reduced project risk, and greater flexibility in how organizations manage their cloud strategies.

Now Available on Oracle Cloud Marketplace

To make adoption even easier, 麻豆学生精品版 Data Express is now available through the Oracle Cloud Marketplace, Oracle’s trusted destination for discovering and deploying partner solutions for Oracle Cloud Infrastructure customers.

Availability through Oracle Cloud Marketplace helps customers:

• Easily discover Data Express within the OCI ecosystem
• Accelerate deployment and evaluation
• Integrate data mobility into OCI migration strategies
• Simplify procurement and cloud solution adoption through Private Offer purchases

Explore the listing here: 麻豆学生精品版 Data Express on

Looking Ahead

As organizations continue embracing multi-cloud architectures, the ability to move data seamlessly between providers becomes increasingly critical. With expanded support for OCI, AWS and Azure environments, 麻豆学生精品版 Data Express delivers the flexibility enterprises need to migrate, replicate, and manage data wherever business requirements demand.

From OCI-to-OCI, AWS-to-AWS, AWS-to-OCI, OCI-to-AWS, and Azure-to-Azure workflows, Data Express is helping organizations accelerate their cloud journeys while reducing complexity and risk.

The future of cloud is multi-cloud, and Data Express is making that future easier to navigate. Click here to learn more about Data Express or .

When听packet听searches begin with broad IP-based criteria, engineers spend valuable time retrieving and sorting through traffic that has little bearing on the incident. 麻豆学生精品版 AppResponse accelerates the investigation by narrowing the packet set before retrieval, helping teams reach relevant evidence faster and begin analysis sooner.听

The Problem Is Not Filtering. It Is Filtering Too Late.听

Traditional packet retrieval often begins with broad criteria such as a single IP address or a pair of IP addresses. These criteria are useful, but they may describe far more traffic than the engineer needs.听

Consider an application server supporting several services and hundreds of clients. If one TCP-based service slows during a brief incident window, a broad IP-based search听will听retrieve all server traffic, forcing听an听engineer to filter out unrelated packets before the real investigation can begin.听

The filtering works. It simply happens after both the听platform听and the engineer have already processed traffic that was never relevant.听

That delay increases Mean Time to Evidence, the time between detecting a听problem听and obtaining the packet-level data needed to investigate it.听

Narrow the Packet Set Before Retrieval听

AppResponse extends packet retrieval beyond broad IP-based searches by indexing听additional听criteria such as IP protocol and TCP or UDP source and destination ports. Engineers can use these fields alongside IP addresses, conversations, and incident听timeframes听to define a more precise packet set before traffic is read from storage.听

Those criteria are available through a direct, point-and-click workflow, so听teams听narrow searches without first writing complex packet-filter syntax. Instead of retrieving all traffic associated with a server and reducing the results afterward, an engineer can focus听immediately听on a specific TCP connection, application port, GRE-tunneled flow, or relevant听portion听of a broader conversation.听

By filtering earlier, AppResponse reads less irrelevant traffic and returns a more focused capture.听This听allows analysis to begin sooner and reduces the effort to reach useful packet evidence.听

Faster Evidence, More Efficient NetOps听

Earlier filtering reduces both the time and effort听required听to begin packet analysis. Engineers spend less time waiting for broad searches, constructing听additional听filters, and preparing oversized captures. They can move more directly from an observed application or network condition to the evidence needed to investigate it.听

AppResponse also improves how packet evidence moves across teams. A focused capture tied to the affected protocol, port, conversation, and听timeframe听gives application owners, infrastructure teams, and packet specialists a clearer starting point. That reduces repeated retrieval work and helps NetOps validate or听eliminate听the network as the听likely source听of an issue sooner.听

The point-and-click search experience also makes targeted packet retrieval accessible to more members of the NetOps team. Tier 1 and Tier 2 analysts can gather useful evidence without mastering complex filtering syntax, while senior engineers and packet specialists听remain听focused on deeper interpretation, root-cause validation, and resolution.听

Together, these improvements reduce Mean Time to Evidence and help incidents reach the right owner with less delay.听

From Full-Fidelity Data to Faster Action听

Intelligent Network Observability is not about collecting the largest possible volume of telemetry and leaving engineers to sort it out. It is about providing the right data, in the right context, to the right person so teams can act faster.听

Full-fidelity packets听remain听one of the most authoritative sources of network evidence. AppResponse strengthens that foundation by making packet evidence easier to isolate and use.听

That supports 麻豆学生精品版鈥檚 broader vision for Intelligent Network Observability: giving teams the insight and confidence to听identify听issues sooner, resolve them faster, and reduce the disruption they create for users and the business.听

Turn Packet Evidence into Faster Action听

The value of packet data is not measured by how much traffic an organization can capture. It is measured by how quickly teams can turn that data into a confident decision.听

By helping NetOps teams reach relevant evidence sooner, AppResponse reduces the friction between detecting a problem, understanding its cause, and taking the right action. That means faster investigations today and a stronger foundation for more intelligent, proactive operations over time.听

With BGP Anycast support, NetProfiler gives customers another way to strengthen flow ingestion across distributed, high-volume environments. This capability helps reduce reliance on fixed collection paths, giving NetOps teams a more resilient way to get flow telemetry into NetProfiler as collection points, traffic volumes, and network conditions continue to change.

Making Flow Ingestion More Resilient

As the flow collector for NetProfiler, Flow Gateway ingests, deduplicates, compresses, and forwards flow telemetry to NetProfiler for centralized analytics. In large or distributed environments, multiple Flow Gateways may be deployed as physical or virtual appliances to support collection scale and availability.

With BGP Anycast, multiple Flow Balancing Gateways can advertise the same collection address. Network devices and telemetry sources continue sending flow telemetry to a consistent destination, while standard BGP routing directs that telemetry traffic to an available or preferred Flow Balancing Gateway.

This helps organizations:

• Improve flow ingestion availability
• Support geographically distributed collection designs
• Reduce dependence on static collector paths
• Simplify traffic redirection as environments grow or change

NetProfiler environments can also use VIP-based load balancing to distribute telemetry across multiple Flow Gateways within a defined collection architecture. BGP Anycast adds another option for distributed environments where routing-based resilience is a better fit.

Why BGP Anycast Matters to NetOps

For NetOps teams, resilient flow ingestion is not about architecture for its own sake. It is about having confidence that critical traffic intelligence will be available when the environment changes, traffic shifts, or an issue needs to be investigated quickly.

In large, distributed environments, fixed collection paths can add operational friction. Collection points may span multiple sites or regions. Flow volumes may increase. Routing paths may change. Teams still need consistent telemetry feeding NetProfiler so they can detect anomalies, validate traffic patterns, and understand whether network behavior is changing.

BGP Anycast helps reduce that friction by allowing the network to make routing decisions based on standard BGP mechanisms. Network devices and telemetry sources can send flow telemetry to a shared collection address, while routing directs that telemetry traffic to an available or preferred Flow Gateway.

The result is more resilient flow collection that better aligns with modern network realities: distributed environments, dynamic traffic patterns, changing collection points, and growing availability requirements.

Connecting Flow Collection to Intelligent Network Observability

Resilient flow collection becomes more valuable when it is connected to the broader 麻豆学生精品版 observability portfolio. Flow telemetry gives NetOps teams a scalable view of traffic behavior, while packets, infrastructure context, broader network visibility, and AI-driven correlation add the surrounding evidence needed to understand what changed, why it matters, and what to do next.

• AppResponse adds packet-level detail for deeper investigation.
• NetIM provides infrastructure health, topology, and path context.
• NPM+ extends visibility to endpoints, remote users, cloud, SaaS, VPN, Zero Trust, and collaboration environments.
• 麻豆学生精品版 IQ Ops correlates signals across domains to reduce noise, prioritize incidents, and accelerate investigation.

This broader context is central to Intelligent Network Observability. Flow telemetry helps teams see traffic behavior at scale. Packet, infrastructure, endpoint, user, and application data add the surrounding context. Together, these signals help teams move faster from symptoms to cause and from cause to action.

Improving Confidence in Distributed Network Operations

For NetOps teams, the value of BGP Anycast is not the routing architecture itself. It is the confidence that critical traffic intelligence will be available when teams need to detect change, investigate issues, and make decisions under pressure.

By strengthening flow ingestion for distributed, high-volume NetProfiler environments, BGP Anycast helps make one of 麻豆学生精品版鈥檚 key evidence layers more resilient. When that flow intelligence is combined with packet evidence from AppResponse, infrastructure context from NetIM, broader network visibility from NPM+, and AI-driven correlation from 麻豆学生精品版 IQ Ops, teams gain better operational context and a faster path from detection to action.

That is how BGP Anycast supports the bigger 麻豆学生精品版 goal of reducing disruption before it affects users or business operations: stronger flow intelligence, better context, and more confidence that IT teams can keep networks, applications, and users moving.

麻豆学生精品版 has been named a Leader in the IDC MarketScape: Worldwide Digital Employee听Experience 2026 Vendor Assessment.听

As organizations increasingly look beyond endpoint monitoring toward a more comprehensive approach to digital employee experience, we believe this recognition reflects 麻豆学生精品版’s long-standing vision: helping IT teams unify endpoint, application, and network visibility to improve employee experiences, accelerate issue resolution, and drive better business outcomes. 

Digital employee experience has evolved significantly in recent years. What began as a focus on device health and endpoint performance has expanded into a broader operational discipline that spans applications, networks, collaboration tools, cloud services, automation, AI, and employee sentiment. 

Employees don’t experience technology one layer at a time. They simply expect everything to work. When productivity declines, the root cause could be a device issue, a slow application, a network bottleneck, a cloud service disruption, or a collaboration problem. Solving these challenges requires a more connected approach to understanding and improving digital experience. 

Why 麻豆学生精品版鈥檚 Approach Aligns with IDC鈥檚 View of DEX 

Today’s enterprises need more than endpoint telemetry. They need a unified view of the entire digital experience. 

搁颈惫别谤产别诲听础迟别谤苍颈迟测听brings together endpoint monitoring, application performance, network observability, employee sentiment, and sustainability analytics into a single platform. By correlating signals across these domains, organizations can move beyond isolated alerts and听identify听the root causes of digital friction faster.听

This broader view is particularly important in hybrid and distributed work environments where employees depend on complex chains of technologies to stay productive. When issues arise, IT teams need the ability to connect what the employee experiences with what is happening across devices, applications, networks, and cloud services. 

Rather than requiring teams to navigate multiple disconnected tools, 麻豆学生精品版 helps organizations understand how these systems interact and where experience breakdowns occur. 

Beyond Endpoint Monitoring: The Evolution of DEX 

The digital employee experience market is undergoing a major transformation. 

Organizations are increasingly replacing reactive support models with proactive operations that continuously monitor experience, identify emerging issues, and help IT teams take action before employees are impacted. 

At the same time, IT leaders are trying to reduce tool sprawl and eliminate siloed visibility. As observability, automation, IT operations, and digital experience converge, enterprises are looking for platforms that provide a complete picture of employee experience rather than isolated views of individual technologies. 

This shift is accelerating demand for solutions that unify data across endpoints, applications, networks, and employee feedback to provide actionable insights and measurable business outcomes. 

Turning Visibility Into Action 

Visibility is only valuable if organizations can use it to improve outcomes. 

Modern IT teams need solutions that not only identify problems but also help accelerate investigation, reduce operational effort, and support faster remediation. 

One of 麻豆学生精品版’s most differentiated capabilities is Aternity Replay, which helps IT teams virtually recreate and troubleshoot user issues without disrupting employees. By enabling teams to see what users experienced, Replay can significantly reduce diagnostic time and eliminate much of the guesswork traditionally associated with troubleshooting. 

As organizations work to reduce downtime, improve productivity, and deliver better digital experiences, the ability to move quickly from insight to resolution becomes increasingly important. 

AI-Powered Operations With Governance Built In 

Artificial intelligence is becoming a foundational element of digital employee experience. 

Organizations are rapidly exploring how AI can help identify issues faster, recommend corrective actions, automate repetitive tasks, and improve operational efficiency. 

However, as AI becomes more deeply integrated into IT operations, governance becomes equally important. 

麻豆学生精品版’s vision extends beyond AI-powered analytics. 麻豆学生精品版鈥檚 agentic framework introduces a governed path to autonomous operations, combining AI-driven intelligence with policy controls, human oversight, and role-based experiences for employees, service desks, IT engineers, and business leaders. 

This approach helps organizations move beyond simply generating recommendations toward creating trusted, scalable automation that operates within defined governance frameworks. 

The future of DEX will not be defined by dashboards alone. It will be defined by how effectively organizations can transform insight into action while maintaining control, accountability, and operational resilience. 

Built for Enterprise Scale 

Many of the world’s largest organizations operate highly regulated, service-critical environments where performance, governance, and compliance are non-negotiable. 

As enterprises pursue digital transformation initiatives, they need platforms that can support large-scale operations while helping IT teams reduce complexity and improve employee productivity. 

麻豆学生精品版 continues to invest in observability, automation, AI, and digital experience innovation to help organizations modernize IT operations, reduce digital friction, and create more productive digital workplaces. 

From financial services and healthcare to government and global enterprises, organizations are increasingly seeking scalable platforms that can help them navigate growing complexity while maintaining exceptional employee experiences. 

The Future of DEX Is 麻豆学生精品版-Based 

Digital employee experience is no longer a standalone monitoring function. 

It is becoming a strategic pillar of modern IT operations and an important driver of productivity, employee satisfaction, and business performance. 

As the market continues to evolve, organizations are looking for unified platforms that bring together observability, automation, AI, and experience intelligence to reduce operational silos and improve decision making. 

We believe this shift represents the future of digital employee experience. 

As technology environments become more distributed and complex, organizations need a better way to understand and improve the experiences employees have every day. 麻豆学生精品版 Aternity helps make that possible by unifying endpoint, application, network, sentiment, automation, and AI-driven insights in a single platform designed to help organizations move from reactive troubleshooting to proactive, intelligent, and increasingly autonomous operations. 

Download the IDC MarketScape Excerpt  

See why 麻豆学生精品版 was named a Leader in the IDC MarketScape: Worldwide Digital Employee Experience 2026 Vendor Assessment and discover the trends shaping the future of digital employee experience. 

Get the report

Source: IDC MarketScape: Worldwide Digital Employee Experience 2026 Vendor Assessment, IDC #US53014625, June 2026. 

*IDC MarketScape vendor analysis model is designed to provide an overview of the competitive fitness of technology and service suppliers in a given market.  The research methodology utilizes a rigorous scoring methodology based on both qualitative and criteria that results in a single graphical illustration of each vendor鈥檚 position within a given market. The Capabilities score measures vendor product, go-to-market and business execution in the short-term. The Strategy score measures alignment of vendor strategies with customer requirements in a 3-5-year timeframe. Vendor market share is represented by the size of the circles. Vendor year-over-year growth rate relative to the given market is indicated by a plus, neutral or minus next to the vendor name.

Why zero disruption matters for Australian banks

From core banking platforms and trading systems to mobile apps and branch networks, Australian banks depend on highly connected, always鈥憃n digital environments. Disruption is not just about major outages; it often starts with slow applications, intermittent connectivity or blind spots that quietly erode productivity and increase risk. Each so-called 鈥渕inor鈥� issue generates tickets, stretches IT teams and distracts them from strategic work such as risk reduction and the introduction of new digital services.

麻豆学生精品版鈥檚 Zero Disruption approach changes that equation. Instead of waiting for employees or customers to report problems, banks can continuously observe what is happening across endpoints, applications and networks. This makes it possible to understand where issues are emerging, how they are affecting people and what action is needed before any disruption occurs.

Tools like Aternity Replay combine actual employee experience with full telemetry, letting IT teams see exactly what staff experienced on any web or SaaS application and cut resolution time from days to minutes, without forcing error reproduction or expecting employees to step the help desk through what happened.

A global platform with financial鈥憇ervices pedigree

Ours is a global company, operating in 88 countries, with thousands of market鈥憀eading customers including 95% of the Fortune 100 and 83% of the Forbes Global 500. Financial services is one of 麻豆学生精品版鈥檚 key industries, giving confidence that our platform is proven in highly regulated, mission鈥慶ritical environments.

And this experience has already translated into real鈥憌orld outcomes:

• One large financial services organisation saved millions of dollars through AI-driven automation on the 麻豆学生精品版 麻豆学生精品版, which drastically reduced both incident cost and manual troubleshooting effort.
• A major American organisation managed to cut their spend by identifying underutilised software licences and optimising licencing costs.
• One vital healthcare organisation was able to achieve significant cost savings by pinpointing devices that were not needed or not needing replacement in this financial year.
• With automated alerting, Halkbank saw a dramatic increase in availability on their mobile platform over the past two years, despite more than double the volume of traffic.
• Arab National Bank was able to align its business objectives and fully prepare for a critical system upgrade thanks to complete backend visibility for its migration.

Doing more with less through AI and automation

By going deeper into endpoints, applications and networks, 麻豆学生精品版 helps banks move beyond anecdotal complaints to quantifiable trends and insights. This makes it possible to prioritise remediation and automation where it matters most, focus investments where they will deliver the greatest impact and safely build confidence in more autonomous operations.

麻豆学生精品版 customers worldwide are already running AI at massive scale, with 22 million monthly automations, 8.3 million monthly remediations and 300 million annualised automations. For banks, this means routine problems 鈥� from device鈥憀evel fixes and SaaS performance issues to configuration changes 鈥� can be resolved consistently by the platform, freeing engineers to focus on higher鈥憊alue work.

Of course, human judgement remains central for complex, high鈥憆isk changes, but AI鈥慸riven remediation reduces the time spent on repetitive tasks and helps teams support more endpoints and applications without a resultant growth in costs.

Turning global experience into local business cases

Boards and executive teams in Australian banks rightly expect technology investments to be backed by clear value stories and robust ROI calculations. 麻豆学生精品版 can help you build those stories using peer use cases and proven business cases from banks and enterprises around the world. This includes concrete metrics such as numbers of automations achieved, cost savings per person, reduction in licence spend, asset refresh optimisation and incident鈥憆elated cost avoidance.

A structured journey moves organisations from interest to investment. 麻豆学生精品版 runs targeted discovery workshops that bring peer use cases and proven business cases into the room, then works with stakeholders to quantify ROI, risk reduction and cost optimisation. Together, we can help you build board鈥憆eady proposals in weeks rather than months, grounded in real鈥憌orld examples such as remediation savings or licence optimisation 鈥� all aligned directly with your organisation鈥檚 own environment and strategic priorities.

Connecting Australian banks with global peers

麻豆学生精品版鈥檚 customer base is not just a pretty set of logos; it is a network of peers from whom Australian banks can learn. For example, 麻豆学生精品版 is working with a large bank that plans to increase spend from US$800,000 to US$1.5 million for AIOps with Aternity 360 in a tight fiscal environment, based on demonstrated value. 麻豆学生精品版 has connected that bank with a large global bank so they can use each other鈥檚 business cases at board level, sharing insights on which use cases landed best, how ROI was quantified and how stakeholders were engaged.

Australian banks can now tap into this rich network to validate their own strategies and explore relevant use cases before committing to investment. Whether it鈥檚 understanding how peers approached tools consolidation, licence optimisation or network blind鈥憇pot mitigation, 麻豆学生精品版 can facilitate conversations that turn global experience into local advantage.

Learn about听麻豆学生精品版鈥檚 targeted Zero Disruption discovery workshops for financial institutions by booking a meeting or reading more.

In our recent webinar, From Signals to Outcomes: How 360掳 Digital Experience Prevents Disruption in the Real World, Forrester鈥檚 Christy Punch and customers from Princess Alexandra Hospital NHS Trust and PG&E joined 麻豆学生精品版 to explore a critical shift: 

Visibility is no longer enough. Prevention is the new standard. 

Here are five takeaways every IT leader should be acting on now. 

1. Data overload isn鈥檛 the issue. Context is the breakthrough. 

Most IT teams are flooded with dashboards across devices, apps, networks, and collaboration tools. But here鈥檚 the catch. Seeing more doesn鈥檛 mean understanding more. 

Teams may spot the signals, yet still miss what matters most: the user experience and business impact. 

The goal isn鈥檛 more data. 滨迟鈥檚 end-to-end experience clarity that helps teams take action faster. 

2. DEX must connect signals to outcomes 

Signals tell you something is wrong. They don鈥檛 tell you what it means. 

The real shift is connecting experience data to what the business cares about: 

• Can employees start work without delay?听

• Can teams collaborate without friction?听

• Can frontline workers complete critical tasks?听

By connecting signals to outcomes, IT turns DEX from basic monitoring into a strategic driver of productivity and resilience. 

3. No tickets doesn鈥檛 mean zero disruption 

The webinar highlighted a revealing example: 

At Princess Alexandra Hospital, devices that seemed 鈥渂roken鈥� were taken out of service instead of logged through a support ticket. No ticket existed, but the disruption was real. 

That鈥檚 the blind spot in traditional IT metrics. Zero tickets can create a false sense of stability. The real goal is zero disruption: finding and fixing issues before users need to report them. 

4. Full visibility is the foundation for better experience 

Work now happens across devices, networks, apps, and locations. 

It spans: 

• Laptops and mobile devices听

• SaaS and cloud apps听

• Microsoft Teams, Zoom, and collaboration tools听

• Remote, hybrid, and frontline environments听

Mobile is increasingly mission-critical, yet it is often the least understood part of the experience. In industries like healthcare and utilities, mobile performance can directly affect patient care, field response, and the ability to support people in critical moments. 

A modern DEX strategy must follow users wherever work happens and connect the full journey into one unified view. 

Because for users, the experience is simple: work either flows, or it doesn鈥檛. 

5. AI needs context to drive action 

AI is reshaping IT and accelerating the shift toward autonomous operations. But success depends on complete visibility and context. 

Without complete visibility, AI lacks the context to act effectively: 

• Network听problems can appear to be听device issues听

• Application delays can be mistaken for user behavior听

• Root cause听remains听uncertain听

With full context, AI can move from insight to trusted action: 

• Patterns听surface faster听

• Root cause is听identified听sooner听

• Automation becomes听reliable and听trusted听

360掳 visibility gives AI the context to act with confidence and turns autonomous IT into an achievable reality. 

The future of DEX is zero disruption 

The webinar made the shift clear: the next era of DEX is not about watching dashboards. 滨迟鈥檚 about preventing disruption before work slows down. 

That requires IT teams to: 

• Connect听signals across the听full听digital听environment听

• Understand what users are听actually experiencing听

• 础肠迟听产别蹿辞谤别听蝉尘补濒濒听颈蝉蝉耻别蝉听产别肠辞尘别听产耻蝉颈苍别蝉蝉听诲颈蝉谤耻辫迟颈辞苍听

That is how IT moves beyond visibility to measurable outcomes and makes zero disruption the new standard for digital experience. 

.听See听how leading organizations are听turning听360掳 Digital Experience听into a practical path to autonomous IT, trusted automation,听and听zero-disruption work at scale with听搁颈惫别谤产别诲听础迟别谤苍颈迟测.听

With our latest release, 麻豆学生精品版 takes a major step forward, extending the Unified Agent to macOS, strengthening Aternity鈥檚 Mac capabilities, and accelerating AI-driven, proactive IT operations.

Unified Agent for Mac: Simplicity Today, 麻豆学生精品版 for What鈥檚 Next

The introduction of the Unified Agent for macOS marks a major milestone in simplifying endpoint management and accelerating innovation delivery.

The Unified Agent provides a single, modular platform to deploy, manage, and update Aternity and other 麻豆学生精品版 capabilities, reducing complexity while unlocking faster access to innovation. And just as importantly, it lays the foundation for seamlessly delivering new modules and innovations as they become available.

With a single agent, IT teams can deploy Aternity without managing multiple agents, automatically stay current with the latest features without manual overhead, reduce endpoint footprint by consolidating agents, and easily adopt future modules such as NPM+, UC, and more without additional deployment effort.

For IT teams, this means faster deployment, simplified lifecycle management, and continuous innovation鈥攚ithout disruption.

Advancing Aternity on Mac

Alongside the Unified Agent, Aternity continues to expand its depth and coverage on macOS, bringing enterprises closer to true cross-platform parity.

The Aternity Agent for Mac now provides monitoring across device performance, native applications, and web applications, while supporting modern macOS versions and expanding telemetry with disk, VPN, and user context data.

These latest enhancements deliver richer device context, broader telemetry, and improved operating system support, empowering IT teams to troubleshoot faster and extend visibility across every endpoint.

What鈥檚 New in This Release

This release introduces continued innovation across the Aternity platform, including ongoing delivery of new capabilities through the Unified Agent, improvements to telemetry collection and system stability, enhancements that support automation and AI-driven operations, and Mac-specific updates such as improved Wi-Fi telemetry and remediation script timestamping.

Together, these advancements accelerate Aternity鈥檚 evolution into a unified, AI-ready platform for autonomous IT operations.

Why It Matters

This isn鈥檛 just an incremental update. 滨迟鈥檚 a fundamental shift in how IT delivers digital experience.

By unifying visibility, simplifying management, and enabling continuous innovation through a single agent, 麻豆学生精品版 helps IT teams move beyond reactive troubleshooting to a prevention-first approach that eliminates disruption before it impacts employees. The result is faster resolution, lower complexity, and a consistently exceptional digital experience across every user, device, and application.

With this release, organizations can:

• Reduce complexity with a single, unified agent across endpoints
• Accelerate innovation without disruption through seamless, continuous updates
• Extend 360掳 visibility across endpoints, applications, and the network

And this is just the beginning. Explore Aternity鈥檚 latest innovations on our听product release page听and take the next step toward zero-disruption digital experience.

Instead, they say:

• 鈥淪alesforce is freezing.鈥�
• 鈥淭eams calls keep breaking up.鈥�
• 鈥淭he application is painfully slow.鈥�

As a result, IT Operations teams must quickly determine not only that users are struggling, but also why.

Modern Digital Employee Experience (DEX) platforms do an excellent job identifying user impact. They surface slowdowns, crashes, login failures, poor SaaS performance, and widespread degradation across departments or regions. However, detecting frustration is only the first step.

IT teams still need to answer critical operational questions:

• What changed?
• Which dependency failed?
• Did the issue originate in the application, infrastructure, or network?

This is exactly where the integration between 麻豆学生精品版 Aternity employee experience and 麻豆学生精品版 APM+ changes the troubleshooting workflow.

The Gap Between User Experience and Application Root Cause

Today, most IT organizations still troubleshoot using disconnected tools.

Typically, DEX platforms identify that users are affected, while application observability tools monitor transactions and services separately. Meanwhile, infrastructure and network teams investigate performance issues in parallel.

Consequently, IT teams often spend valuable time manually correlating data, switching between consoles, escalating issues across teams, and rebuilding timelines by hand.

In other words, DEX tools often answer: 鈥淯sers are affected.鈥�

But IT still needs another workflow to answer: 鈥淲hat actually happened?鈥�

Start with the User Impact

Aternity gives IT Operations a far better starting point because it immediately shows where digital experience is degrading and who is affected.

For example, IT teams can quickly identify slow application response times, login degradation, crashes, freezes, and the geographic or departmental scope of the issue. At the same time, Aternity correlates device and network conditions that may contribute to poor experience.

More importantly, Aternity connects technical issues directly to business impact. Teams can immediately understand which users and applications are affected and how productivity is suffering.

As a result, IT shifts from infrastructure-first monitoring to experience-first operations.

Instead of starting with an infrastructure alert and searching for impact afterward, teams start with the actual employee experience and work directly toward root cause.

Move Directly from Experience to Application Root Cause

Once Aternity identifies an issue, IT teams can launch directly into APM+ with the correct application and time context already preserved.

That transition dramatically streamlines the investigation process.

Rather than forcing teams to manually reconstruct events across disconnected systems, 麻豆学生精品版 creates one continuous workflow from user impact to application root cause.

From there, APM+ reveals what happened inside the application environment, including transaction traces, service dependencies, slow database calls, API failures, and latency across microservices.

As a result, teams can move beyond symptoms and isolate the underlying cause much faster.

Simply put, Aternity answers: 鈥淲ho felt the issue?鈥�

While APM+ answers: 鈥淲hat caused it?鈥�

Together, they connect user experience directly to application behavior.

Accelerate Resolution with Shared Context

When DEX and application observability work together, IT teams spend less time chasing symptoms and more time resolving problems.

Instead of manually correlating siloed data, teams can move seamlessly from user complaint to impacted application to transaction-level root cause.

Consequently, teams reduce operational friction while accelerating resolution.

In addition, APM+ delivers full-fidelity visibility designed for IT Operations. Therefore, teams can investigate issues with complete context instead of relying on sampled data or partial traces.

Ultimately, the integration helps organizations:

• Accelerate root cause identification
• Reduce escalations and manual troubleshooting
• Lower MTTR
• Align user experience with operational insight

Digital experience problems rarely originate in a single domain. While employees experience the symptom first, the root cause often lives deep inside modern application architectures.

By connecting Aternity with 麻豆学生精品版 APM+, IT Operations teams can finally bridge that gap, moving from user impact to application root cause through one continuous workflow.

Explore the Aternity to APM+ workflow, request a demo.

But instrumentation is only the first step.

As organizations begin introducing OpenTelemetry into their environments, often alongside existing observability tools, incident response remains a challenge. Even with additional telemetry, operations teams frequently lack access to the context required to diagnose issues quickly, explain user impact, and restore service with confidence.

This is where 麻豆学生精品版 APM+ comes in.

APM+: Complete Transaction and Code鈥慙evel Views for Operations

APM+ builds on OpenTelemetry to deliver application observability that works for IT Ops, not just developers.

Instead of sampling, APM+ retains full鈥慺idelity, end鈥憈o鈥慹nd transaction context at up to 1 second granularity. Every transaction is captured independently, making anomalies, outliers, and early degradation visible the moment they appear.

That transaction context extends directly into application code. Method鈥� and class鈥憀evel execution data shows exactly where time is spent, where errors occur, and how execution paths behave under real production conditions. For Ops teams, this means fewer hand鈥憃ffs, less guesswork, and faster root cause analysis.

Instrument Everything Without the Cost

Instrumentation costs often force IT Operations to limit observability. APM+ and OpenTelemetry makes broad instrumentation possible.

As application coverage grows, ingestion鈥慴ased pricing forces teams to limit observability to Tier鈥�1 applications, re鈥慽ntroducing blind spots across the broader portfolio. IT Operations is left with partial visibility precisely when broad coverage matters most.

麻豆学生精品版 APM+ changes the economics of application observability. Priced at up to 70% less than traditional APM tools, it removes the cost barriers that typically restrict deep visibility to a small set of Tier鈥�1 applications.

But lower pricing alone isn鈥檛 enough to make broad OTel instrumentation sustainable. As coverage expands, controlling telemetry growth becomes just as critical as reducing data storage costs. That鈥檚 where 麻豆学生精品版 Smart OTel comes in.

Smart OTel applies intelligence at the point of collection, filtering low鈥憊alue noise before it drives cost, while preserving high鈥憊alue transactions at full fidelity. The result is predictable cost and sustainable coverage, even as application footprints grow.

For IT Ops, that means broader application visibility without sacrificing depth鈥r the budget.

From Visibility to Faster Operational Resolution

For operations teams, seeing an issue isn鈥檛 enough, resolution speed is what counts.

APM+ correlates transaction data with dependencies, infrastructure behavior, and user experience. When performance degrades, IT Ops can move directly from detection to diagnosis with the right context already captured.

There鈥檚 no need to reconstruct timelines across disconnected tools. The execution details required to understand impact and cause are already there鈥攁ccelerating MTTR and improving confidence during incidents.

OpenTelemetry Is the Foundation. APM+ Makes It Operational.

OpenTelemetry enables organizations to instrument everything. APM+ permits IT Ops teams to detect, diagnose, and remediate everything.

Together, they eliminate the trade鈥憃ffs that have historically limited application observability in operations. Teams no longer have to choose between broad coverage and deep insight, or between controlling cost and maintaining full鈥慺idelity, actionable visibility.

Click here to learn more about 麻豆学生精品版 APM+ or request a demo.

The constraint isn鈥檛 desire or awareness. 滨迟鈥檚 the economic and operational reality of applying deep observability across modern application environments at scale. That鈥檚 why OpenTelemetry (OTel) is emerging as a critical foundation for modern application observability.

The Observability Gap Most Enterprises Live With

As application environments scale, traditional APM approaches become economically impractical to apply broadly, forcing teams into difficult tradeoffs:

• Focus deep instrumentation on tier鈥憃ne applications, leaving the long tail largely invisible
• Or absorb pricing tied to telemetry volume to deploy more broadly

The result is a fragile operating model. Teams pay heavily for observability but still face blind spots across much of the application portfolio. When incidents occur outside the handful of deeply instrumented services, troubleshooting becomes slow, manual, and dependent on guesswork.

As environments become more distributed鈥攁nd as AI workflows introduce new dependencies and execution paths鈥攖hese blind spots only multiply.

Why OpenTelemetry Changes the Game

OpenTelemetry fundamentally shifts what鈥檚 possible. As an open, vendor鈥憂eutral standard, it makes deep, consistent instrumentation feasible across the entire application estate, not just a select few services.

With OpenTelemetry, teams gain:

• Standards鈥慴ased instrumentation across languages, frameworks, and platforms
• Freedom from proprietary agents and data formats
• The ability to instrument cloud鈥憂ative, hybrid, and legacy environments consistently
• A common telemetry foundation that can evolve as architectures change

Most importantly, OpenTelemetry removes the structural barriers that historically limited observability coverage. It becomes realistic to instrument all applications, not just what the budget allows.

This is a necessary step toward modern application observability, but it鈥檚 not sufficient on its own.

The Hidden Challenge of 鈥淚nstrument Everything鈥�

OpenTelemetry makes it technically possible to capture telemetry everywhere. At enterprise scale, however, raw telemetry volume grows fast鈥攁nd often uncontrollably.

As coverage expands:

• Trace volume increases exponentially
• Storage and ingestion costs rise
• Signal鈥憈o鈥憂oise ratio drops
• Operations teams struggle to find what actually matters

Streaming all raw telemetry downstream without governance simply shifts the problem. Instead of blind spots, teams face data overload, higher costs, and operational complexity that undermines the very value observability is meant to deliver.

This is where many organizations stall. Open instrumentation without intelligent control becomes unsustainable.

The Missing Layer

OpenTelemetry makes it possible to instrument everything, but at enterprise scale, raw telemetry quickly becomes overwhelming. As teams expand instrumentation across applications, services, and AI workflows, telemetry volume grows exponentially, driving higher storage costs, increased noise, and operational complexity. Without controls at the point of collection, 鈥渙pen鈥� observability can become unsustainable.

麻豆学生精品版 Smart OTel is purpose鈥慴uilt to solve this problem.

Smart OTel is 麻豆学生精品版鈥檚 intelligent telemetry governance technology, designed to turn open instrumentation into scalable, enterprise鈥慻rade observability. Instead of streaming unfiltered telemetry downstream, Smart OTel applies intelligence at the point of collection, filtering, enriching, and shaping telemetry in real time鈥攂efore data overload becomes an issue.

With Smart OTel, 麻豆学生精品版 ensures:

• High鈥憊alue signals are preserved at full fidelity, including complete transaction context
• Low鈥憊alue, redundant, or noisy data is intelligently reduced or filtered
• Trace depth and execution context are maintained, even as coverage expands
• Telemetry volume and cost remain predictable and controlled

This approach allows organizations to confidently scale OpenTelemetry instrumentation across their entire application estate, without runaway observability costs or sacrificing the depth required for fast, accurate troubleshooting.

Crucially, Smart OTel is built on open OpenTelemetry standards. Telemetry remains portable, vendor鈥憂eutral, and aligned with OpenTelemetry as observability strategies, architectures, and tools evolve鈥攚hile benefiting from 麻豆学生精品版鈥檚 intelligence and operational expertise.

From Raw Signals to Operational Intelligence

When OpenTelemetry is paired with Smart OTel, observability moves beyond basic monitoring.

Teams gain the ability to:

• Preserve complete transaction context across applications and dependencies
• Detect degradation early through correlated signals and baselines
• Move directly from alert to root cause using captured execution context
• Extend observability into AI agents and workflows, making AI behavior transparent and diagnosable

This intelligent telemetry foundation also enables higher鈥憃rder capabilities such as AI鈥慳ssisted root cause analysis, guided remediation, and over time, more autonomous operations.

Modern enterprises don鈥檛 run tens of applications; they run hundreds. Observability strategies must scale accordingly.

Observability That Finally Scales with the Business

OpenTelemetry provides the openness and flexibility required to instrument everything. 麻豆学生精品版 Smart OTel ensures that doing so remains economically viable, operationally manageable, and analytically useful.

Together, they eliminate the historic tradeoff between depth and breadth, making it possible to achieve full鈥慺idelity application observability across the entire application estate, not just the most critical services.

That鈥檚 the difference between limited monitoring and real production鈥憀evel understanding,  where every transaction, every dependency, and every user impact is visible when it matters.

To learn how 麻豆学生精品版 APM+ supports OpenTelementy, click here.

We believe these results highlight the continued evolution of 麻豆学生精品版鈥檚 platform鈥攃ombining deep visibility, advanced analytics, and automation to address the most critical DEX challenges enterprises face today.

Our Performance Across Key Use Cases

The 2026 Critical Capabilities report evaluates DEX tools across five primary use cases, including IT support, endpoint operations, experience analytics, employee enablement, and cost optimization.

We believe 麻豆学生精品版 demonstrated broad strength and balanced performance across all categories, including:

• Cost Optimization (highest scoring use case): Supporting more efficient endpoint management and lifecycle decisions through data-driven insights
• IT Support: Enabling faster issue resolution and improved support outcomes through enhanced visibility and automation
• Endpoint Operations: Driving operational efficiency across complex endpoint environments
• Experience Analysis and Employee Enablement: Providing actionable insights into digital experience across users, applications, and devices

We feel these results reflect a platform designed to support both operational efficiency and improved employee experience across enterprise environments.

Our Perspective on Year-Over-Year Improvement

In 2026, 麻豆学生精品版 demonstrated year-over-year improvement across all evaluated use cases and the majority of capability areas.

We believe these results demonstrate sustained investment in the platform and continued progress across the full DEX lifecycle鈥攆rom visibility to action.

A 麻豆学生精品版 Approach to DEX

As organizations evolve beyond point solutions, the ability to unify data, insights, and action across endpoints, network, applications, and infrastructure is becoming increasingly important.

麻豆学生精品版鈥檚 approach combines:

• 360掳 visibility across endpoints, application, and network performance
• Advanced analytics and AI-driven insights
• Automation and workflow integration to act on those insights

This platform approach enables organizations to move beyond isolated monitoring toward continuous optimization of digital experience at scale.

Why We Believe Critical Capabilities Matters

鈥淕artner Magic Quadrant research methodology provides a graphical competitive positioning of four types of technology providers in fast-growing markets: Leaders, Visionaries, Niche Players and Challengers. As companion research, Gartner Critical Capabilities notes provide deeper insight into the capability and suitability of providers鈥� IT products and services based on specific or customized use cases.鈥�*

Together, these perspectives help IT and digital workplace leaders:

• Better understand how solutions perform in real-world scenarios
• Align product capabilities to business priorities
• Make more informed technology decisions

Learn More

Want to see how leading organizations are turning DEX insights into action?

for our 360掳 Digital Experience webinar to hear perspectives from industry analysts, 麻豆学生精品版 leaders, and customers – and learn how to detect issues earlier, act faster, and deliver zero disruption at scale.

*Gartner, Gartner Magic Quadrant & Critical Capabilities,

Gartner, Critical Capabilities for Digital Employee Experience Management Tools, Stuart Downes, Dan Wilson, Robin Milton-Schonemann

GARTNER and MAGIC QUADRANT are trademarks of Gartner, Inc. and/or its affiliates. Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner鈥檚 business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.

But as digital environments become more complex, disruption is no longer limited to major outages. It often starts with small interruptions: a slow application, a dodgy device or a network issue at a remote site. Each one may seem minor by itself, but at scale these issues erode productivity, increase demand on IT teams and distract people from the work that matters.

For resource companies, the next step is not just about faster issue resolution. 滨迟鈥檚 about moving towards a zero-disruption future, where problems are identified, understood and resolved before they affect their employees, operations or safety.

Disruption is a productivity issue

In the resources sector, productivity depends on smooth work flows across highly connected environments. Operational teams, field workers, engineers, IT teams and business functions all rely on digital systems to make decisions, manage assets and keep things moving.

When workflows are disrupted, the impact spreads quickly. Employees get annoyed and lose focus, IT tickets increase and support teams are pulled into reactive troubleshooting. Over time, this creates drag across the organisation, slowing operations and diverting IT teams and workers alike from higher-value work.

The new zero-disruption paradigm

麻豆学生精品版鈥檚 new zero-disruption approach changes the equation. Instead of waiting for employees to report problems, IT can continuously observe what is happening across endpoints, applications and networks. This makes it possible to understand where issues are emerging, how they are affecting people and what action is needed before any disruption occurs.

This is achieved by bringing together autonomous intelligence 鈥� the foundation for zero-disruption 鈥� with AI observability, deep insights into the application and digital employee experience (DEX) plus a strong data foundation with high-frequency data analytics and accelerated AI data movement.

If you don鈥檛 know what your employees are experiencing and if you don鈥檛 know how your apps and networks are behaving, you鈥檙e basically in the dark. And paying for it.

Cost savings are about prevention, not just responding

Why this matters? Resource companies are under constant pressure to make considered investment decisions. Digital initiatives need to show measurable value, align with operational and strategic priorities and contribute to efficiency across the organisation.

Zero disruption supports that goal by reducing the cost of avoidable downtime, repeated troubleshooting and manual remediation. When IT teams can identify root cause faster, automate the right response and prevent recurring issues, they spend less time reacting and more time improving the digital environment.

This is where full-fidelity telemetry matters. 麻豆学生精品版 brings together visibility across devices, applications and networks, helping organisations move beyond fragmented data and anecdotal experience. With a unified data store and intelligence layer, teams can correlate what changed, how it was experienced and what needs to happen next. All without asking the employee to step the help desk through what went wrong.

AI also has an important role to play, but only when it is grounded in complete, high-quality data and governed by clear controls. 麻豆学生精品版鈥檚 approach allows organisations to automate at their own pace, moving from guided action to more autonomous operations as confidence grows.

Safety depends on reliable digital experience

In the resources sector, employee experience is not just a workplace technology issue. 滨迟鈥檚 a direct connection to safety, operational reliability and the ability to make timely decisions.

When employees are working in remote, mobile or high-risk environments, digital disruption can create frustration, delay and uncertainty. A poor connection, an unreliable application or unresolved device issue can slow down communication and pull your employees away from critical tasks.

A zero-disruption model helps reduce that risk. By identifying issues before employees even know there鈥檚 a problem, IT can support a safer, more connected workforce. Instead of asking employees to describe what happened after the fact, new tools such as 麻豆学生精品版 Aternity Replay help IT see the experience more clearly, understand the impact and resolve issues without adding to the employee鈥檚 workload.

This matters because the goal is not simply fewer tickets. The goal is fewer disruptions. In a resources-sector context, that means keeping people connected, supported and focused wherever they work.

Better digital experience helps teams do more with less

Skills shortages and increasing operational complexity mean resource companies need technology that helps people work smarter. AI and automation can remove repetitive, labour-intensive tasks so employees can focus on higher-value work.

For IT teams, this means moving from reactive operations to autonomous operations. 麻豆学生精品版鈥檚 intelligence layer can continuously observe the digital environment, prioritise what matters and apply the right response within IT-defined guardrails. Human judgement remains available where it is needed, but routine issues can be handled faster and with greater consistency.

For employees, the experience becomes simpler. Instead of juggling tickets, dashboards and workarounds, they can receive proactive support through tools they already use. A conversational interface can surface an issue, explain what is happening and ask for approval to fix it when needed.

That is a very different employee digital experience. It shifts the burden away from the user and IT team and helps prevent disruption before it affects the workday.

Building the foundation for autonomous IT

For resource companies, the path to zero disruption starts with visibility, context and governance.

• Visibility means seeing across the full digital environment, including endpoints, applications and networks.
• Context means understanding not just that an issue occurred, but how it affected the employee experience.
• Governance means ensuring AI-driven action is safe, controlled and aligned with the organisation鈥檚 operating model.

With these foundations in place, resource companies can modernise IT operations while supporting the broader goals of digital transformation: greater efficiency, lower cost, safer work and a better employee experience.

The zero-disruption future is not about eliminating every IT ticket. It is about preventing issues before they become discernible problems, resolving them automatically where appropriate and giving IT teams the insights they need when human judgement is required.

For the resources sector, that is the next frontier of digital transformation: a connected, intelligent and prevention-first operating model that keeps people productive, helps control cost and supports safer work from pit to port.

Discover how 麻豆学生精品版 can help your organisation move from reactive IT to a zero-disruption future.

Today, I鈥檓 proud to share an important milestone on that journey: 麻豆学生精品版 has achieved FedRAMP庐 Class D (High) Certification for the 麻豆学生精品版 麻豆学生精品版 for Government, now listed on the .

Why FedRAMP Matters: Milliseconds Matter to Mission Success

This achievement is more than a compliance milestone. It reflects 麻豆学生精品版鈥檚 commitment to delivering trusted, resilient observability that enables Civilian, DoD, and federal agencies to operate with speed, precision, and confidence at mission scale.

In today鈥檚 environment, performance is mission-critical. When every second counts, agencies need complete visibility across users, applications, and networks to detect and resolve issues before they impact operations.

What is FedRAMP Class D?

FedRAMP Class D, the equivalent of what was formerly called FedRAMP High,听sets听a rigorous standard for protecting sensitive federal data in cloud environments, including Controlled Unclassified Information (CUI).听麻豆学生精品版听is proud听to be听among听the听first听Digital Employee听Experience听(DEX)听platforms听to听achieve this听milestone.听听Achieving this听certification听requires strict security controls, continuous monitoring, and a resilient architecture designed for both compliance and operational continuity.

Just as important, 麻豆学生精品版 uses the same core SaaS code base for both federal and commercial customers. As a result, 麻豆学生精品版 commercial customers directly听benefit听from the same hardened security architecture, operational controls, compliance processes, and platform rigor听required听to satisfy some of the most demanding cybersecurity standards in the world.

The Strategic Edge of SaaS for Government Agencies

From the outset, we designed the 麻豆学生精品版 麻豆学生精品版 for Government from the ground up to meet Class D requirements with a unified approach, simplifying compliance while maintaining strong security, performance, and resilience. With the current federal focus on maximizing efficiency, transitioning from traditional on-premises systems to cloud-native, SaaS-based architectures is no longer just an option. It is a necessity. SaaS solutions offer several compelling benefits over legacy on-prem solutions: 

• Dynamic Scalability: Seamlessly scales to meet fluctuating user demands, whether supporting a small team or hundreds of thousands of users, without requiring costly, time-consuming infrastructure upgrades.
• Security at Scale: Deployed on AWS GovCloud, the platform allows agencies to benefit from specialized 麻豆学生精品版 teams that continuously monitor, patch, and harden system security. This delivers a level of protection that is difficult to replicate in siloed, on-prem environments.
• Cost Efficiency: By reducing hardware dependencies, maintenance overhead, and specialized staffing needs, agencies can reallocate critical resources away from infrastructure upkeep and back to their core missions.
• Continuous Innovation: SaaS ensures our government customers receive automatic updates and cutting-edge features without operational disruption, keeping them steps ahead of evolving cyber threats.
• Built-in Ecosystem Integration: Because the platform is built on AWS GovCloud, federal agencies gain instant, trusted integration with other critical government SaaS and cloud solutions, such as Microsoft 365.

We鈥檙e confident that as more agencies embrace SaaS, they鈥檒l continue to unlock operational advantages that simply aren鈥檛 possible with legacy IT models. 

Committed to the mission, today and tomorrow

Achieving FedRAMP Class D (High) Certification reinforces 麻豆学生精品版’s role as a trusted partner in Federal modernization. We are excited to help our agency partners eliminate blind spots, optimize digital experiences, and secure their cloud journeys with confidence.

It also marks the next phase of our commitment to federal agencies鈥攄elivering observability that not only meets compliance requirements, but enables faster decisions, stronger resilience, and mission success.

Learn more about the 麻豆学生精品版 麻豆学生精品版 for Government.

Just as importantly, we see this as a validation of our strategy: delivering a unified, AI-powered platform that brings together endpoint, application, and network visibility to enable truly intelligent digital experience management, and move enterprises closer to zero-disruption IT Operations. 

Why DEX Matters More Than Ever 

Digital employee experience is no longer a nice-to-have鈥攊t鈥檚听mission critical.听

Today鈥檚 employees expect fast, reliable, seamless interactions with every application and device they use. When performance breaks down, productivity drops, employee frustration rises, and IT teams are forced into reactive firefighting. 

At the same time, IT leaders are under increasing pressure to: 

• Deliver proactive, scalable support 

• Personalize employee experiences 

• Deploy AI backed with high-quality telemetry 

• Maximize the value of digital and infrastructure investments 

DEX sits at the center of these priorities. And as organizations move toward AI-driven and autonomous operations, the goal is no longer just visibility, it鈥檚 eliminating disruptions before they impact employees. 

Built for Modern DEX 

麻豆学生精品版 continues to differentiate by delivering enterprise-scale DEX through a unified platform approach. 

Unlike point solutions, 麻豆学生精品版 Aternity brings together: 

• Device, application, and network visibility through a single agent 

• Deep integrations across ITSM, endpoint management, and observability ecosystems 

• Extensibility through OpenTelemetry-based data and automation frameworks 

• Built-in remediation and no-code workflows for faster resolution 

This platform approach enables customers to move beyond fragmented monitoring and towards end-to-end, actionable insights that prevent issues before they escalate, helping organizations operate with minimal disruption. 

Innovation That Drives Real Impact 

Over the past year, 麻豆学生精品版 has continued to push the boundaries of what鈥檚 possible in DEX. 

Key innovations include: 

• Agentic AI advancements that enable persona-aware insights, investigations, and governed actions 

• Aternity Replay, delivering privacy-first session insights for faster root cause analysis 

• Expanded AI-driven automation, helping IT teams move from detection to resolution faster 

• Smart OTel, enabling broader telemetry ingestion and AI-ready data pipelines 

• Continued expansion across mobile, unified communications, and endpoint ecosystems 

Together, these innovations reflect a clear focus: helping IT teams shift from reactive troubleshooting to proactive, and increasingly autonomous, operations, with the ultimate goal of preventing disruption altogether. 

DEX for the AI Era 

As enterprises adopt generative AI and agentic AI, digital experience data becomes foundational.听

AI systems are only as effective as the data they rely on. Without accurate, contextual insight into real user experiences, automation falls short. 

麻豆学生精品版鈥檚 approach ensures organizations have: 

• Full-fidelity, real-time telemetry 

• Context across users, devices, apps, and networks 

• AI-driven insights embedded directly into workflows 

This is what enables self-healing systems, predictive optimization, and intelligent service delivery – reducing incidents, accelerating resolution, and driving toward a zero-disruption digital workplace. 

Looking Ahead: From Insight to Action听at Scale听

In our view, being named as a Leader for the third consecutive year is an important milestone, but it鈥檚 not the finish line. 

We believe the future of DEX is about: 

• Closing the gap between insight and action 

• Embedding AI into every stage of the experience lifecycle 

• Delivering autonomous, zero-disruption IT environments 

麻豆学生精品版 is committed to continuing to innovate, invest, and lead, helping organizations deliver exceptional, interruption-free digital experiences for every employee, everywhere. 

Learn More鈥� 

Want to see how leading organizations are turning DEX insights into action?鈥� 

鈥痜or our 360掳 Digital Experience鈥痺ebinar鈥痶o hear perspectives from industry analysts, 麻豆学生精品版 leaders, and customers鈥斺�痑nd learn how to detect issues earlier, act faster, and deliver zero disruption at scale.鈥�

Source: Gartner Report,听Magic Quadrant for Digital Employee Experience Management Tools, By Dan Wilson, Stuart Downes, etc., June 2026.听

Gartner and Magic Quadrant are a trademark of Gartner, Inc. and/or its affiliates.听

Gartner does not endorse any vendor, product or service depicted in its research publications and does not听advise technology users to听select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research and advisory organization and should not be construed as statements of fact. Gartner听disclaims听all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.听

But when data volumes reach hundreds of terabytes or petabytes, DIY data movement stops being a scripting exercise and becomes a high-risk systems problem.

What works for gigabytes can quietly fail at scale.

Familiar Tools Don鈥檛 Scale the Way You Think

Tools like rsync and rclone are popular for a reason鈥攖hey鈥檙e simple, reliable, and flexible. Even enterprise teams often augment them with Robocopy, SCP, or cloud-native tools like AWS CLI or AzCopy. But these tools were not designed for distributed, multi-cloud, high-throughput data movement at enterprise scale.

As datasets grow:

• Transfers must be parallelized manually (or wrapped with custom tooling)
• Performance tuning becomes non-trivial鈥攅ven with tools like rclone or AzCopy
• Single-threaded or protocol limitations constrain throughput
• Cross-cloud transfers (AWS Azure GCP) introduce unpredictable latency

Even purpose-built utilities like AWS DataSync or Google Storage Transfer Service can struggle with cross-cloud orchestration, consistency, and throughput at scale.

What once moved data overnight can stretch into weeks or months.

Failure Becomes Inevitable and Expensive

At petabyte scale, failures are not edge cases. They are expected.

With DIY pipelines built on tools like rsync, rclone, or SCP:

• Transfers fail mid-stream due to transient network issues
• Resume capabilities vary widely (and aren鈥檛 always efficient)
• Integrity validation often requires additional scripting or third-party tooling
• Cross-region transfers using native cloud tools can introduce inconsistent retry behavior

Even when using managed tools like AWS DataSync or Azure Data Factory, organizations still face gaps in end-to-end orchestration and failure recovery across environments.

Engineers spend cycles re-running jobs, validating data, and troubleshooting edge cases.

A single interruption can cascade into days of rework and additional cloud spend.

No Built-In Governance or Auditability

Open-source and native tools were not designed with enterprise governance in mind.

When stitching together tools like rsync + cron jobs + custom scripts, or mixing with AWS DataSync / Azure Data Factory / GCP Transfer Service, teams often encounter:

• Fragmented logs across systems
• No centralized job tracking or orchestration
• Limited visibility into what data moved, when, and by whom
• No consistent policy enforcement across clouds

Even 鈥渆nterprise鈥� workflows often rely on combinations of ETL/orchestration tools (e.g., Airflow, Glue, Data Factory) that were not purpose-built for high-speed bulk data movement.

The result is fragmented visibility. Operations teams struggle to answer basic questions such as:

• What data was transferred?
• Did the transfer complete successfully?
• Who initiated the movement?
• Can we prove compliance if we’re audited?

As environments grow more distributed, answering those questions often requires digging through multiple systems and manually correlating logs.

Cost Overruns Hide in Plain Sight

DIY approaches are often justified as 鈥渇ree鈥濃�攅specially when using rsync, rclone, Robocopy, or SCP. But the real cost shows up elsewhere. A typical enterprise migration may involve several engineers maintaining scripts, monitoring transfers, resolving failures, and validating results. Add cloud egress charges, temporary storage, bandwidth upgrades, and duplicate transfers caused by failed jobs, and costs can grow much faster than anticipated. Even managed services like AWS DataSync or Azure Data Box can introduce unexpected costs tied to data movement, storage staging, and operational overhead. Costs quietly escalate into the six-figure range鈥攐r higher.

What begins as a “free” solution often becomes a significant operational expense.

The Biggest Risk: Not Finishing at All

The most overlooked risk isn鈥檛 inefficiency鈥攊t鈥檚 incompletion.

DIY pipelines built on tools like rsync, rclone, or custom Python/CLI scripts require continuous manual oversight. As complexity increases鈥攅specially across multi-cloud environments (AWS, Azure, GCP, OCI)鈥攖eams hit:

• Scaling bottlenecks
• Knowledge silos (only a few engineers understand the pipeline)
• Operational fatigue and higher error rates
• Increasing fragility as more tools are stitched together

Even organizations using DataSync, Data Factory, or Transfer Service often find these tools insufficient for large-scale, multi-cloud orchestration without additional custom engineering.

Over time, many DIY data movement projects become dependent on a small group of engineers who understand how the workflow was assembled. As requirements evolve, more tools, scripts, and exceptions are added, increasing complexity and operational risk.

Eventually, the challenge is no longer moving the data. It’s maintaining the process well enough to finish the project.

The Bottom Line: DIY Is a Risk Multiplier

There鈥檚 nothing wrong with tools like rsync, rclone, SCP, or Robocopy鈥攖hey remain essential utilities. And cloud-native options like AWS DataSync, Azure Data Factory, and Google Transfer Service have their place. But using any combination of these as the foundation for large-scale, multi-cloud data movement introduces compounded risks across:

• Time 鈫� delays, inefficiency, unpredictability
• Execution 鈫� failures, retries, fragile pipelines
• Governance 鈫� lack of visibility and control
• Cost 鈫� hidden labor, infrastructure, and egress

Cloud migration strategies used to be built around finality. Choose a target cloud. Move the data. Lock it in place. Why? Because moving petabytes of data across clouds or regions was painful, slow, expensive, risky, and operationally disruptive.

A New Model for Data Movement: Fast, Portable, Strategic

That all changes with 麻豆学生精品版 Data Express. When organizations can easily and quickly move data clouds and cloud regions, that finality disappears.

麻豆学生精品版 Data Express enables organizations to move massive volumes of data across clouds and regions, turning data mobility into a strategic advantage for migration, resilience, and AI. It removes the friction from large鈥憇cale data movement. It delivers high鈥憇peed, secure, and predictable transfer of massive datasets across AWS, Oracle Cloud, and their regions鈥攕o organizations can migrate faster, build resilient multi鈥慶loud architectures, and fuel AI with the data that matters, wherever it lives.

With Data Express, data is no longer something you relocate once and optimize around forever. It becomes portable, strategic, and continuously optimized. This fundamentally changes migration itself. Cloud migration stops being a one鈥憈ime project and becomes an ongoing capability.

The Real Question

The question isn’t whether it’s possible to build a large-scale data movement workflow with rsync, rclone, or cloud-native tools. Many organizations do exactly that.

The challenge is sustaining it as data volumes grow, timelines tighten, and business priorities shift. What starts as a simple transfer project can quickly become an ongoing operational burden that consumes engineering time, increases costs, and introduces risk.

For organizations moving hundreds of terabytes or petabytes of data, success depends on more than getting data from one location to another. It requires a solution that can deliver predictable performance, operational visibility, and the flexibility to support future migration, multi-cloud, and AI initiatives.

Learn how 麻豆学生精品版 Data Express helps organizations move data faster, more efficiently, and with greater confidence at enterprise scale.

It is a reasonable place to start. Accuracy shows whether a model produces correct responses and helps data science teams validate training approaches, compare architectures, and improve results.

But accuracy alone says very little about how AI behaves once it leaves the lab and enters the enterprise.

When AI becomes part of real workflows, supporting employees, serving customers, or informing business decisions, accuracy alone is no longer sufficient.

Accuracy Is Necessary, But 滨迟鈥檚 Not Operational Intelligence

An AI model can be accurate and still fail the business.

Accuracy does not capture:

• Latency: A correct response that arrives too late degrades user experience just as surely as an incorrect one.
• Cost: Inference pricing, token consumption, and compute usage rarely appear in accuracy metrics, but they surface quickly on a bill.
• Adoption lag: A model can be accurate and still unused. Accuracy does not indicate whether AI is trusted, adopted, or delivering value.
• Dependency impact: Many AI agents sit inside workflows, triggering actions or passing outputs downstream. When something breaks, failures often propagate silently.

In short, accuracy measures what an AI produces. It says very little about how the system behaves.

The Real Challenges of AI in Production

At runtime, AI is subject to the same pressures as any other production technology. Performance fluctuates. Costs vary. Usage ebbs and flows.

This is where organizations encounter the same operational challenges they face with any application:

• Why does response time degrade during peak usage?
• Which AI use cases are delivering value?
• Where is adoption lagging across the organization?
• Who is using Shadow AI?
• How do we detect when AI鈥慸riven workflows drift from expected behavior?

These are not data science questions. They are operational ones.

As AI becomes business鈥慶ritical, it must be managed with the same discipline as other applications. AI should be no exception.

AI Operational Assurance

Many organizations lack the visibility required to operate AI confidently in production. They often have limited insight into performance, cost efficiency, adoption, and risk.

麻豆学生精品版 AI Assurance addresses this gap by providing operational visibility into how AI behaves in real environments. It helps organizations answer questions such as:

• Is AI delivering consistent performance as usage scales?
• Are inference costs aligned with business value?
• Is AI being used across the organization?

By connecting AI behavior to operational and business outcomes, AI Assurance moves AI out of isolated experimentation and into a governable part of the enterprise stack.

Accuracy Is the Starting Line, Not the Finish

Model accuracy will always matter. But as AI becomes embedded in daily operations, organizations must look beyond correctness to understand performance, cost, adoption, and impact. Success is not solely defined by whether AI produces the right answer; it’s also defined by whether the system performs reliably, scales sustainably, and delivers expected value.

麻豆学生精品版 AI Assurance provides the framework to move AI from experimentation to a system organizations can trust and scale.

The real cost isn鈥檛 just compute, storage and bandwidth. 滨迟鈥檚 time, people, operational drag, missed opportunities鈥攁nd what many teams quietly refer to as the double bubble: paying twice for infrastructure while waiting for data to arrive.

麻豆学生精品版 Data Express fundamentally changes those economics.

The Myth of 鈥淔ree鈥� Data Movement

DIY data movement is usually justified as a cost-saving measure. After all, the tools appear deceptively inexpensive, and the cloud is already paid for.

But those apparent savings disappear quickly when transfers stretch from days into weeks, or weeks into months. Organizations frequently underestimate the operational overhead required to make DIY approaches work at scale. Teams must spend significant time learning different tools, integrating them into a cohesive workflow, and continuously managing performance issues along the way.

The hidden costs add up fast. Businesses often end up paying for extended infrastructure usage in both the source and destination environments while also absorbing licensing fees, support costs, and the labor required to orchestrate, monitor, retry, document, and troubleshoot transfers. Delays and failures can also slow critical initiatives such as cloud migrations, analytics projects, and AI deployments, postponing the business value these projects were meant to deliver.

What starts as a 鈥渘o-cost鈥� approach can easily become a budget drain hiding in plain sight, a huge delay in attaining business objectives, and even career derailment for those who took on complex DIY projects and failed to deliver results.

The Double Bubble: Pay Twice, Wait Longer

One of the costliest financial impacts of slow or unreliable data movement is the double bubble. This challenge arises when a business must migrate their data from one cloud to another for reasons such as an acquisition or divestiture, consolidation of applications, or simply for a better cost structure in a different region or cloud.  

With such projects, there typically is a business plan that targets new revenue, cost synergies for merged entities, or reduced cost of operations as a business scales or serves a larger base of customers.  They key is to complete the migration quickly to reach the new state of the business.

When data transfers take too long, organizations are forced to:

• Keep legacy environments running longer than planned
• Pay for cloud infrastructure that sits idle waiting for data
• Maintain parallel systems, licenses, and support contracts

In other words, you pay twice鈥攐nce for where the data is, and again for where it needs to be鈥攚hile gaining value from neither.

Data Express attacks the double bubble directly by compressing migration timelines. 

Faster, predictable data transfers mean legacy environments can be decommissioned sooner and target environments become productive faster. The savings compound quickly.

Time Is Money鈥擡specially in Migration and AI

Speed isn鈥檛 just a technical metric. 滨迟鈥檚 a financial one. Every day a migration is delayed pushes back cloud ROI, postpones modernization goals, and slows AI and analytics initiatives that depend on timely access to data.

DIY approaches often fail to account for time value. Data Express consistently reduces data movement windows from weeks to days鈥攐r days to hours鈥攃hanging the economics of the entire initiative.

With Data Express, faster data movement allows organizations to realize cloud savings sooner, accelerate analytics initiatives, and begin training and deploying AI models earlier in the process.

The business impact arrives sooner鈥攏ot just eventually.

Headcount: The Most Overlooked ROI Lever

DIY data movement consumes people. Highly skilled engineers spend days or weeks writing scripts, managing retries, troubleshooting failed transfers, tuning performance, and coordinating workflows across different environments and cloud providers. This work is not strategic鈥攁nd it doesn鈥檛 scale.

Data Express dramatically reduces the operational burden by automating and simplifying the transfer process. With centralized visibility, resilient transfers, and predictable performance at scale, organizations can dramatically reduce the amount of manual intervention required. This allows engineering teams to redirect their expertise toward innovation and higher-value projects rather than ongoing transfer maintenance and troubleshooting.

The result is lower ongoing labor costs and the ability to redeploy scarce engineering talent to higher-value initiatives. In many organizations, this headcount efficiency alone justifies the investment.

Egress Fees: The Unavoidable Tax on Multi-cloud Data Movement

Beyond lost opportunity costs, there are actual hard costs in moving data.  One of the most significant is cloud egress fees, which are charged when data is transferred out of cloud environments鈥攂etween different cloud providers or different regions within the same cloud provider, or to on-premises systems. These fees can be substantial when dealing with petabytes of data. 

It can easily cost $50,000-90,000 in egress charges to move one PB of data out of a cloud provider, although each of the four major hyperscalers have different rates depending on various factors including where the data resides, so actual costs do vary.  And remember, you may be moving multiple petabytes, and with AI, you will likely need to do this repeatedly to refresh your AI models.

Egress charges with Data Express can be a fraction of that, depending on data type. When you use Data Express to make the move, the 麻豆学生精品版  can reduce that data up to 90%, depending on its reducibility. Further, Data Express builds a dynamic Data Fabric that scales to 100鈥檚 of Gbps of network capacity, enjoying significant cost reductions compared to basic egress. And, you only pay for the actual data moving across the network.

So Data Express brings big savings over what you would pay otherwise with egress charges. This is one more part of the TCO that you should be considering in your DIY equation.

Risk Reduction Is a Financial Outcome

Failed or incomplete transfers aren鈥檛 just technical issues鈥攖hey鈥檙e financial risks. Data loss, improper data movement, corruption, or partial migrations lead to:

• Rework and delays
• Compliance exposure
• Loss of stakeholder confidence

DIY tools often lack enterprise-grade verification, resilience, and auditability, increasing both operational risk and cost. Data Express reduces these risks with built-in integrity checks, security controls, and reliability at scale鈥攍owering the likelihood of costly remediation or compliance issues.

Predictability Enables Better Financial Planning

Another hidden cost of DIY approaches is unpredictability. When transfer performance varies widely or projects frequently encounter delays, organizations struggle to accurately plan migration timelines, decommission legacy systems, and forecast cloud spending.

This unpredictability forces conservative planning鈥攍onger overlap periods, larger buffers, and higher spend 鈥渏ust in case.鈥�

Data Express provides deterministic performance, allowing organizations to confidently align migration timelines with financial plans, schedule cutovers more accurately, and reduce unnecessary overlap between old and new environments.

Predictability itself becomes a cost-saving mechanism.

From Cost Center to Strategic Enabler

Perhaps the biggest financial shift is psychological. DIY makes data movement a cost center鈥攕omething to minimize, delay, or work around.

Data Express reframes it as a strategic enabler:

• Migrations become repeatable and reversible
• Multi-cloud strategies become economically viable
• AI initiatives accelerate without ballooning budgets

When data can move quickly and reliably, organizations stop paying the hidden taxes associated with rigidity and delay.

The Bottom Line

DIY data movement may appear less expensive at first glance, but the hidden costs often tell a very different story. Extended migration timelines, duplicated infrastructure costs, higher labor demands, operational risk, and delayed business outcomes can quickly outweigh any perceived savings from using free or open-source tools.

麻豆学生精品版 Data Express eliminates these hidden costs by turning data movement into a predictable, scalable, and financially efficient capability.

The question is no longer 鈥淗ow much does data movement cost?鈥� 滨迟鈥檚 鈥淗ow much value are we leaving on the table by doing it the hard way?鈥�

Learn more here.

The GigaOm Radar evaluates vendors based on execution, innovation, and platform maturity, not just features, giving NetOps teams a clear view of which solutions can meet the demands of modern environments.

This year鈥檚 report highlights a clear shift: observability has moved beyond monitoring. The report highlights a shift toward platforms that turn data into understanding and understanding into action.

Visibility Is the Foundation. Fragmentation Is the Barrier.

Network teams have done the hard part. Over the past decade, they鈥檝e built out visibility across packets, flows, infrastructure, endpoints, and cloud environments. There is no shortage of data.

The problem is not a lack of data. 滨迟鈥檚 that most of it remains fragmented. Packet tools, flow monitors, infrastructure platforms, and endpoint solutions each provide a different version of reality. During incidents, teams don鈥檛 lack information 鈥� they鈥檙e reconciling conflicting answers.

That鈥檚 not an observability problem. That鈥檚 an architecture problem. The challenge is no longer collecting more data. 滨迟鈥檚 turning fragmented data into coherent, actionable insight.

How the GigaOm Radar Evaluates 麻豆学生精品版 Maturity

The Radar makes this shift explicit, moving away from device-centric monitoring toward platforms that combine end-to-end visibility with intelligence and action. The expectation is no longer just to collect telemetry, but to reduce the manual effort required to interpret and act on it.

To meet that standard, platforms must:

• Collect multiple telemetry types across the entire environment
• Correlate that data into a single, consistent view
• Apply intelligence to identify root cause and drive next actions

This is the difference between monitoring systems and decision systems. And it highlights a clear challenge in the market: fragmented telemetry produces fragmented insight, and the operator becomes the integration layer.

Why 麻豆学生精品版 Is Positioned as a Leader

麻豆学生精品版鈥檚 position as a Leader and Fast Mover reflects more than alignment with market direction. It reflects a fundamentally different approach to solving the problem the Radar highlights.

This positioning is not incidental. It is the result of an architecture designed specifically to address the fragmentation that limits most observability platforms today.

At the core of the 麻豆学生精品版 platform is full-fidelity telemetry across packets, flows, infrastructure, and user experience, delivered not as separate tools, but as a unified system.

By contrast, parts of the market remain divided across incomplete approaches. Some vendors emphasize packet-level depth but struggle to scale or extend visibility. Others prioritize flow-based monitoring, trading precision for efficiency and scalability. Many claim to be platforms but still rely on loosely integrated components that require manual correlation.

麻豆学生精品版 eliminates those tradeoffs by capturing and correlating:

• Packets for deep, ground-truth analysis
• Flows for scalable visibility and trends
• Infrastructure metrics for network and device health
• End-user experience data for real-world performance

These are not just multiple data sources. When pulled together in the 麻豆学生精品版 Data Store, they form a single, consistent model of how the network behaves.

That distinction becomes clear in real-world operations. Instead of stitching together partial answers from multiple tools, teams gain a unified view of cause and effect across the entire environment. Troubleshooting accelerates, false leads are reduced, and resolution becomes far more predictable.

From AI Insight to Autonomous Action

Because 麻豆学生精品版 operates on unified, full-fidelity data, it can apply AI in a way fragmented platforms cannot.

As reflected in the Radar, 麻豆学生精品版 combines multiple forms of AI to move from analysis to action:

• Causal AI to identify root cause across domains
• Predictive AI to anticipate issues before they escalate
• Generative AI to deliver clear, explainable recommendations
• Agentic AI to move from assisted operations toward autonomous execution

This progression is critical. Many platforms can surface signals, but without consistent, correlated data, AI outputs remain incomplete or inconclusive.

麻豆学生精品版鈥檚 AI operates on correlated telemetry across packets, flows, infrastructure, and user experience within the 麻豆学生精品版 Data Store. That foundation provides the context needed to connect signals into a single explanation, reduce manual investigation, and accelerate resolution.

As 麻豆学生精品版 advances its agentic AI capabilities, the platform is increasingly able not just to explain and recommend, but to act within governed boundaries, helping teams move from reactive troubleshooting toward proactive, and ultimately more autonomous, operations.

Why This Matters Now

Modern environments expose the limits of fragmented observability. Zero Trust, encryption, SaaS, and distributed users make it impossible for any single data source to explain what鈥檚 happening end to end. This is where most approaches break down.

Packet data provides depth but not scale. Flow data scales but lacks precision. Endpoint data shows impact but not always cause. Without correlation across all of these, teams are left stitching together incomplete answers during critical incidents.

麻豆学生精品版 is built to solve this directly.

By unifying full-fidelity telemetry across packets, flows, infrastructure, and user experience into a single, correlated data model, 麻豆学生精品版 gives NetOps teams a complete and consistent view of the entire environment. Instead of reconciling conflicting data across tools, teams can move directly from detection to root cause to resolution.

That unified foundation is what makes observability actionable, enabling faster troubleshooting, more reliable insights, and a clear path toward automation.

The Bottom Line

The 2026 GigaOm Radar for Network Observability confirms a shift already underway: visibility alone is not enough. The real value lies in turning that visibility into understanding, and that understanding into action.

麻豆学生精品版鈥檚 position as a Leader and Fast Mover reflects a platform built for that reality. By combining full-fidelity telemetry, unified data, and AI-driven intelligence, 麻豆学生精品版 enables organizations not just to observe their networks, but to operate them with clarity, speed, and a clear path toward automation.

Check out the GigaOm Radar here: 2026 GigaOm Radar for Network Observability

That mental model no longer holds.

Today, enterprises need to move data quickly between cloud providers and cloud regions,鈥攕ecurely, reliably, and at scale. And with that need comes something far more powerful than faster transfers: a fundamental shift in how organizations think about cloud migrations, analytics, and AI.

From 鈥淢ove Once鈥� to 鈥淢ove Freely鈥�

Cloud migration strategies used to be built around finality. Choose a target cloud. Move the data. Lock it in place.

Why? Because moving petabytes of data across clouds or regions was painful, slow, expensive, risky, and operationally disruptive.

That all changes with 麻豆学生精品版 Data Express. When organizations can easily and quickly move data clouds and cloud regions, that finality disappears.

麻豆学生精品版 Data Express enables organizations to move massive volumes of data across clouds and regions, turning data mobility into a strategic advantage for migration, resilience, and AI. It removes the friction from large鈥憇cale data movement. It delivers high鈥憇peed, secure, and predictable transfer of massive datasets across AWS, Oracle Cloud, and their regions鈥攕o organizations can migrate faster, build resilient multi鈥慶loud architectures, and fuel AI with the data that matters, wherever it lives.

With Data Express, data is no longer something you relocate once and optimize around forever. It becomes portable, strategic, and continuously optimized. This fundamentally changes migration itself. Cloud migration stops being a one鈥憈ime project and becomes an ongoing capability.

Multi鈥慍loud Finally Works the Way It Was Promised

Multi鈥慶loud has long been discussed but rarely realized at scale. The reason wasn鈥檛 lack of intent鈥攊t was lack of data mobility.

Applications can be replicated. Infrastructure can be cloned. But data鈥攅specially massive, mission鈥慶ritical datasets鈥攈as traditionally resisted movement. That created de-facto lock鈥慽n, even when organizations used multiple clouds.

Now with 麻豆学生精品版 Data Express, organizations can:

• Rebalance datasets between regions to reduce latency, improve user experience, or meet regulatory requirements
• Shift large datasets to where compute is most cost鈥慹ffective at any given moment
• Move data between regions for business resiliency
• Run Oracle鈥慶entric workloads close to OCI services while feeding analytics or AI pipelines in AWS

Multi鈥慶loud stops being a diagram on a slide and starts behaving like an operational reality.

Region-to-Region Data Movement Enables True Cloud Resilience

You can now redefine business continuity and disaster recovery with Data Express. The ability to move data between OCI regions and between AWS regions also transforms static, pre鈥憄rovisioned replicas that may or may not stay in sync. With Data express, you can:

• Rapidly replicate or refresh datasets securely across regions
• Recover massive volumes of data without days鈥攐r weeks鈥攐f downtime
• Treat regional failures and global uncertainty as recoverable events, not existential threats
• Leverage economic and technical advantages of different cloud providers

This same regional mobility also supports data residency requirements, performance optimization for global users, and workload placement based on evolving business needs.

With Data Express, resilience becomes dynamic, not brittle.

AI Changes Everything, and Data Movement Makes AI Possible

AI doesn鈥檛 just consume data. It demands data鈥攍arge volumes of it, rapidly accessible and often centralized for training.

Here鈥檚 the challenge: enterprise data is everywhere. Just a few examples include:

• Your proprietary enterprise data from ERP, SCM, CRM might be in OCI
• Human interaction data such as customer, service logs, expert advice in AWS
• Multi-modal data such as images, video, sensor data scattered across regions

Without fast, secure data movement, AI initiatives stall before they start. But with Data Express, data can move freely across clouds and regions, so AI architectures can change dramatically. Training data can be aggregated without months of preparation. Model training can run where the best GPUs or lowest costs exist. Inference pipelines can pull fresh data regardless of where it originated.

In short, AI velocity accelerates with data agility.

Organizations that can move data quickly can experiment faster, retrain models more frequently, run Agents faster and operationalize AI at scale.

Data Gravity Becomes a Strategic Choice, Not a Constraint

For years, 鈥渄ata gravity鈥� meant something you worked around. Once data landed in a cloud or region, everything else was pulled toward it. Now, gravity is something you can intentionally create or release.

Need analytics closer to business users? Move the data.

Need AI compute elsewhere? Move the data.

Need to exit a region, rebalance costs, or modernize architecture? Move the data.

When data movement is reliable and repeatable, architectural decisions stop being permanent compromises. They become fluid optimizations.

The New Cloud Operating Model

The ability to move data across AWS regions, across OCI regions, and between AWS and OCI doesn鈥檛 just improve performance. It reshapes organizational thinking.

Leading enterprises are moving toward a new model where:

• Data is treated as a shared, agile asset
• Clouds are execution environments, not destinations
• Migrations are reversible
• AI pipelines are unconstrained by data silos

The cloud stops being a place you move to and becomes a platform you continuously optimize across.

Data Agility Is the New Competitive Advantage

The next phase of cloud adoption won鈥檛 be defined by which provider you choose鈥攂ut by how freely your data can move between them. Organizations that embrace this shift will migrate faster with less risk, extract more value from multi鈥慶loud investments, and build AI systems that aren鈥檛 limited by geography or vendor boundaries.

Data Express transforms data movement from a bottleneck into a capability鈥攎aking cloud migrations reversible, multi鈥慶loud strategies practical, and AI initiatives unconstrained by where data resides.

In a world where data fuels every competitive advantage, agility is no longer optional. 滨迟鈥檚 foundational.

With 麻豆学生精品版 Data Express for the first time, it鈥檚 truly fast, easy, secure and achievable. Learn more here.

That challenge becomes more pressing as certificate lifetimes get shorter. What was recently a 398-day cycle is now being reduced toward a 47-day maximum. Certificates that were reviewed periodically now require more frequent attention, increasing the likelihood of missed renewals, configuration drift, and more time spent troubleshooting when something breaks.

Most organizations already have tools to issue and renew certificates. The challenge isn鈥檛 lifecycle management. 滨迟鈥檚 confirming that certificate updates are applied correctly and do not introduce issues in production.

Why TLS Lifetimes Are Shrinking and What It Means for Operations

The move toward shorter TLS certificate lifetimes is being driven by the and enforced by major browser vendors like Google, Apple, and Mozilla. The goal is to reduce risk.

Shorter lifetimes limit the window of exposure if a certificate or private key is compromised and reduces reliance on long-lived credentials that can drift out of compliance. Reduced lifetimes also push organizations toward more automation and consistent management practices.

The operational impact of these changes is straightforward: certificates are replaced more frequently, and validation windows are shrinking. As a result, the pace of change increases 鈥� certificates are updated more often and small inconsistencies surface more quickly.

When issues occur, teams still need to determine:

• Which certificate is in use
• Whether the correct certificate was presented
• If expected protocols and ciphers were negotiated

Logs and alerts can point to symptoms, but they rarely provide the context to resolve issues quickly. As certificate changes happen more often, that lack of context becomes harder to work around.

Where AppResponse Fits

As TLS certificate lifetimes move toward 47 days, teams are required to validate certificate changes far more frequently. The challenge isn鈥檛 just managing renewals. 滨迟鈥檚 confirming that those changes are working as expected in production.

麻豆学生精品版 AppResponse reduces the time required to verify certificate changes and troubleshoot issues by making certificate behavior visible in real traffic.

• Understand certificate usage in real traffic: AppResponse shows which certificates are actively in use and alerts when they approach expiration, helping teams focus on the certificates that affect production.
• Detect configuration drift from frequent updates: More frequent certificate rotation increases the likelihood of inconsistent configurations. AppResponse detects weak or non-approved ciphers and TLS versions before they cause outages or failed validations.
• Validate certificate deployments during TLS handshakes: AppResponse exposes handshake behavior in detail, allowing teams to confirm that newly deployed certificates are presented correctly.
• Identify trust chain issues introduced during certificate rotation: Frequent updates increase the chance of missing intermediates or misconfigured chains. Packet-level visibility allows teams to confirm the full certificate chain is presented correctly and pinpoint where validation breaks down.

These capabilities apply across on-prem, cloud, and hybrid environments, allowing teams to verify certificate changes and resolve issues quickly as certificate lifecycles accelerate.

Managing TLS at a Faster Pace

The shift to 47-day TLS certificates increases the frequency of change and reduces the tolerance for error. AppResponse provides the visibility teams need to confirm that certificate updates are working as expected and to identify issues quickly when they are not.

See How AppResponse Supports 47-Day TLS Certificate Lifecycles

To discover how AppResponse helps you monitor certificate expiration, validate certificate deployments, and identify issues introduced by more frequent certificate changes, visit 麻豆学生精品版 AppResponse.

When employees call the service desk saying 鈥渋t just didn鈥檛 work,鈥� support teams are forced to guess, recreating issues after the fact, relying on incomplete user recollection, and combing through telemetry to piece together the story. 

The problem isn鈥檛 a lack of data. 滨迟鈥檚 a lack of context. 

Modern employee workflows span dozens of third鈥憄arty SaaS applications that IT teams don鈥檛 own or control, making traditional, application鈥慽nstrumented replay approaches impossible to scale across the digital workplace. 

Aternity Replay changes that. 

Instead of simply reporting a failure, Replay lets service desk teams rewind the exact user interaction that led to the issue, correlated with device and network conditions at that moment. No screenshots. No video capture. No user dependency. Just the clarity teams need to resolve issues faster and understand why experiences fail. 

Why Traditional Session Replay Never Fit DEX 

Session replay isn鈥檛 new, but it hasn鈥檛 belonged in enterprise IT environments. 

Traditional replay tools were built for digital marketing and application teams. They are app-centric, instrumentation-heavy, and reliant on video or visual reconstruction that introduces real privacy and compliance risk in employee environments. 

Because they lack visibility into device health, network conditions, and competing system activity, traditional replay tools cannot explain why an experience failed in a real employee environment. 

This is where Aternity Replay fundamentally changes the equation. 

Rather than recording video or images, Replay captures DOM-level structural interactions directly from the endpoint and correlates them with rich device and network telemetry, purpose-built for IT and service desk teams. 

The result? Support teams can see exactly how an application behaved, how the page changed, what actions occurred, and simultaneously understand the system conditions that influenced the experience. 

No reproduction. No live troubleshooting sessions. No dependency on the user. 

Why This Matters for the Service Desk 

For service desks under pressure to resolve issues faster and deflect escalations, Replay becomes a powerful force multiplier. 

Faster first-contact resolution: L1 and L2 teams can instantly validate issues by reviewing exactly what the user experienced, not what they remember. 

Lower MTTR and fewer escalations: Correlating replay with endpoint and network telemetry eliminates guesswork and accelerates root-cause identification. 

Confidence without compromise: Replay is privacy-first by design, capturing no images, video, or user-entered text. It is compliant from day one. 

Because Replay requires no application instrumentation or user involvement, service desks can activate visibility quickly without adding operational overhead. 

From Reactive Support to Proactive Insight 

Replay doesn鈥檛 stop at break/fix. 

By surfacing recurring workflow friction and unreported issues across applications, IT teams gain visibility into experience gaps employees may never submit tickets for. 

That insight allows organizations to optimize digital experiences before disruption turns into lost productivity at scale. 

A New Standard for DEX Visibility 

DEX solutions help IT understand what is slow or failing. Aternity Replay finally shows how it failed and why. 

This isn鈥檛 just better troubleshooting. 滨迟鈥檚 a new layer of DEX visibility that connects user behavior, application behavior, and system conditions into a single, explainable experience. 

The blind spot in DEX is closed. The question now is whether your service desk is ready to see. 

See It for Yourself 

Watch the video below to see Aternity Replay in action and discover how service desks can resolve issues faster, reduce escalations, and finally see what employees actually experienced. 

One of the biggest cost drivers is no longer just the device itself. Memory prices have skyrocketed, significantly increasing the cost of every endpoint refresh. What used to be a routine lifecycle decision is now a material budget event, creating real pressure for both IT and finance teams to justify听spending听while still supporting employee productivity.听

Many organizations still rely on age based refresh cycles, replacing a fixed percentage of devices every few years. In today鈥檚 cost environment, that approach often leads to one of two outcomes: over refreshing devices that don’t need it or under refreshing that leaves employees struggling with hardware that can鈥檛 keep up with their work. Neither is sustainable. 

The Growing Challenges of Device Refresh Planning 

Modern device refresh planning requires more nuance than ever before. IT Operations teams must weigh multiple variables鈥搕echnical, financial, and experiential鈥搘hile navigating rising costs and organizational scrutiny. 

Budget Constraints and Cost Inflation 

With memory prices climbing, endpoint refreshes are simply more expensive than they were even a year ago. Justifying new devices when existing ones still function can be difficult, especially when听refresh听decisions听aren鈥檛听clearly tied to performance or productivity outcomes. Without hard data, refresh planning becomes reactive instead of strategic.听

Diverse Hardware Needs and Usage Patterns 

Not every role requires the same level of computing power. Yet many organizations still standardize refreshes across the fleet. In a high cost environment, overprovisioning is no longer just inefficient, it鈥檚 expensive. At the same time, underpowered devices slow employees down and generate support tickets, creating hidden costs of their own. 

Unpredictable Lifespans and Logistical Complexity 

Devices age differently depending on usage, applications, and work style. Unexpected failures disrupt refresh plans and drive unplanned spend, while remote and hybrid work models make tracking inventory, warranties, and device health even more challenging. 

Employee Experience vs. Technical Metrics 

Employees know when their devices are holding them back, but those experiences don鈥檛 always align with traditional IT metrics. Some devices meet technical specs yet still deliver poor real-world performance. Others may feel slow but don鈥檛 actually require replacement. Without visibility into both device health and user experience, refresh decisions remain subjective. 

Being forced into a technology refresh under cost pressure is no easy task. Organizations need a proactive strategy that aligns technology investments with business priorities, especially when hardware costs are rising. 

Remove the Guesswork with Aternity Smart Device Refresh 

Is your IT team struggling to balance employee experience with the rising costs of device refreshes? You鈥檙e not alone. Higher memory prices, combined with increasing performance expectations, have raised the bar for making the 鈥渞ight鈥� refresh decision. 

Aternity Smart Device Refresh takes a smarter, data driven approach. Instead of refreshing devices based on age alone, Aternity collects real-time performance and health data across your entire device fleet and correlates it with actual user experience. The result: clear insight into which devices truly need replacement, which can be upgraded, and which should be retained. This enables IT and finance teams to buy only what they need, avoiding unnecessary spend while still protecting employee productivity. 

Turn Insight into Action 

With the Smart Device Scenario Library, IT teams can define refresh policies that align with business goals and budget realities. Evaluate device performance, hardware specifications, application behavior, warranty status, and user experience, then immediately see the impact of different refresh strategies before making a decision. 

The Action Planner streamlines execution by translating insight into a clear, actionable refresh plan, helping organizations right size refresh cycles even as hardware costs continue to rise. 

Learn More 

Read the IT Asset Cost Reduction Solution Brief to explore how 麻豆学生精品版 helps organizations control infrastructure costs without compromising employee experience. Aternity Smart Device Refresh optimizes refresh decisions, reduces unnecessary upgrades, and ensures investments are driven by real performance data, not assumptions. 

They鈥檙e familiar. They鈥檙e owned. They feel controlled. Dashboards light up green, systems are available, and service levels appear intact. On paper, everything looks fine.

And yet, many IT and Digital Workplace leaders sense a disconnect.

Employees complain about sluggish tools. Collaboration falters at the worst moments. SaaS applications behave differently depending on where people are working. Productivity dips in ways that are hard to quantify, let alone explain.

This is the challenge organizations increasingly face today: everything looks healthy but work still feels harder than it should.

The issue isn鈥檛 that on-prem environments are broken. 滨迟鈥檚 that they can no longer see what matters most.

The Blind Spots Built Into On-Prem Environments

On-prem platforms were designed for a different era of work. An era where:

• Employees worked primarily from offices
• Applications lived in corporate data centers
• Networks were predictable and contained
• User journeys followed familiar paths

In that world, monitoring infrastructure health was often enough. If systems were available and performance thresholds were met, work generally flowed.

That鈥檚 no longer the reality.

Today, even a simple task may involve:

• An endpoint device or mobile handset
• Multiple SaaS applications
• A home, public, or mobile network
• A collaboration platform
• Secure, encrypted connections
• Human behavior and context

On-prem tools tend to observe these elements in isolation, if they see them at all. They can confirm that a system is running, but struggle to explain why a workflow feels slow, inconsistent, or frustrating for the person using it.

This is where blind spots emerge not because IT lacks skill or effort, but because the tools were never designed to connect the full experience.

The Cost of What You Can鈥檛 See

When visibility is fragmented, IT is forced into a reactive posture.

Issues are investigated after employees complain. Tickets bounce between teams. Root cause analysis takes longer than it should. And even once a fix is applied, there鈥檚 often uncertainty about whether the experience actually improved.

More importantly, the quiet problems go unnoticed.

The extra seconds waiting for an app to load. The repeated retries during a video call. The workarounds employees adopt without ever raising a ticket.

These moments rarely show up in traditional metrics, but over time they add up eroding productivity, confidence, and trust in digital tools.

You can鈥檛 optimize what you can鈥檛 see.

What SaaS Makes Visible

SaaS changes the conversation because it changes the vantage point.

Rather than focusing on where systems live, SaaS-based platforms are designed to observe how work actually happens continuously, across environments, and at scale.

A SaaS approach to digital experience can reveal:

• How devices, applications, networks, and workflows interact in real-time
• Where performance degrades along an employee鈥檚 actual journey
• Whether issues are technical, environmental, or behavioral
• How experience varies by role, location, or context

Crucially, this visibility extends beyond incidents. It captures everyday work, the moments that define whether digital tools enable flow or introduce friction.

This is what allows IT teams to move from firefighting to foresight.

From Infrastructure Metrics to Experience Intelligence

The most significant shift SaaS enables isn鈥檛 purely technical, it鈥檚 conceptual.

On-prem environments are good at answering questions like:

• Is the system available?
• Is the server healthy?
• Did a threshold get crossed?

SaaS platforms are built to answer a different set of questions:

• How did this experience feel?
• Where did work slow down?
• Why did productivity dip here?
• What should we prioritize to make the biggest impact?

This shift from monitoring systems to understanding experience is what enables a true 360掳 Digital Experience.

For organizations operating in highly regulated or mission-critical environments, security and compliance are a critical part of this shift.

The 麻豆学生精品版 麻豆学生精品版 for Government has been granted IL5 Provisional Authority by the Defense Information Systems Agency (DISA), a major step in federal cybersecurity compliance. This designation validates the platform’s readiness for testing to confirm its ability to support secure, mission-critical workloads for national security and defense operations. At the same time, 麻豆学生精品版 is actively pursuing the FedRAMP High certification process.

It allows IT to prioritize based on real impact, not just alerts. To validate improvements with confidence. And to align digital performance with business outcomes, not simply uptime.

Seeing Clearly Changes How IT Leads

When blind spots disappear, so does much of the uncertainty IT teams face every day.

Decisions become easier to justify. Improvements become easier to prove. And digital experience stops being something you react to and becomes something you actively shape.

This isn鈥檛 about replacing everything overnight or dismissing what鈥檚 worked in the past. 滨迟鈥檚 about recognizing that the way we see digital work must evolve, just as work itself has.

On-prem environments can still run. But SaaS reveals what really matters.

Want to Explore This Further?

Our eBook, The Quiet Friction of Staying On-Prem: Why SaaS is the Future of 360掳 Digital Experience, goes deeper into:

• The hidden operational and experience costs that don鈥檛 show up in dashboards
• Why on-prem platforms struggle to deliver true 360掳 visibility
• How SaaS enables a more complete, human-centered view of digital work
• What moving forward looks like without disruption

If you鈥檙e evaluating how to modernize digital experience without increasing risk or complexity, it鈥檚 a great place to start.

Download the eBook and see what SaaS reveals that on-prem can鈥檛.

Aligning digital strategy with purpose

In the resources industry, the digital transformation journey is anchored to a clear purpose鈥揻inding new and better ways to deliver the essential materials that society needs. This requires not just technological upgrades, but a continuous drive for operational improvement and a cultural shift towards openness.听

Embedding technology and data across the value chain

A key pillar of digital transformation is mapping and optimising the entire operational value chain, from extraction to processing and delivery. By adding digital overlays鈥搒uch as real-time monitoring, automation systems and data platforms鈥搊rganisations can make smarter, faster decisions that improve performance and reliability.

The 鈥渋nnovation vs core鈥� conundrum

Successful digital transformation balances investment in core operations with exploration of new digital solutions. When weighing up the benefits of a new operational vehicle versus new technology, it鈥檚 about considering overall organisational budgets and benefits at the same time.

Structured business cases and clear metrics are needed to guide these investments and ensure that each digital initiative delivers value and aligns with both operational efficiency and innovation goals.

Building agile data governance

High-quality, well-governed data is the foundation of innovation in resources organisations. From asset management to predictive maintenance, robust data platforms and governance frameworks are essential for extracting actionable insights for operations and enabling advanced analytics and artificial intelligence to flourish.

Partnership and empowerment at all levels

Beyond bytes, digital success in the resources sector requires strong partnerships between business units and technology teams, fostering localised solutions that meet operational needs while encouraging the re-use of proven approaches. The most effective organisations also invest heavily in building digital capabilities across all levels of the workforce, empowering teams to drive change and adoption from within.

Navigating change: closing the gap between business and IT strategy

At the end of the day, transformation is not just about systems鈥揷ulture and mindset shifts are also central. Coaching for digital upskilling, nurturing curiosity, and embedding IT advocates within business units help overcome resistance to change and accelerate technology adoption.

Future focus: connectivity and emerging technologies

Looking ahead, resource companies are prioritising improved connectivity (including remote sites) and investing in frontier technologies like quantum sensors, edge computing and decarbonisation solutions. These innovations align both with sustainability goals and with the global push for green materials and operations.

Lessons learned: ownership, inclusion and business alignment

One lasting lesson from digital leaders in the resources sector is the value of inclusive ownership: involving the entry level and junior roles as well as business leaders in transformation efforts unlocks deeper insights and ensures solutions are fit-for-purpose. Success depends as much on building strong partnerships and shared accountability as it does on technical skill.

Digital transformation in the resources sector is less about chasing technology trends and more about meaningful improvement, deep cultural alignment and sustainable value creation for organisations and society alike. Learn more about how 麻豆学生精品版 supports complex, distributed operations with unified observability, AIOps and resilient connectivity鈥攈elping organisations operate more safely, efficiently and sustainably.

Des essais cliniques au d茅veloppement de traitements novateurs, la R&D est le poumon de la pharmaceutique. Mais cette discipline 么 combien essentielle se heurte parfois 脿 des barri猫res technologiques qui nuisent 脿 la productivit茅 des 茅quipes, 脿 la r茅putation de l鈥檈ntreprise et 脿 la qualit茅 des soins.听

Pour p茅renniser leur croissance, les leaders du secteur se tournent vers l鈥檕bservabilit茅 unifi茅e. Cette pratique innovante corr猫le les donn茅es, les 茅clairages et les actions pour aider l鈥櫭﹒uipe鈥疘T 脿 am茅liorer l鈥檈xp茅rience digitale des scientifiques et techniciens. Chaque minute gagn茅e peut 锚tre ainsi r茅investie dans le bien-锚tre des patients.听

D茅gager du temps pour la R&D听听

Optimiser l鈥檈xp茅rience digitale est devenu un imp茅ratif incontournable des programmes de recherche scientifique. Car si les techniciens de laboratoire ne peuvent pas acc茅der 脿 tout moment aux syst猫mes鈥疞IMS ou aux outils de bio-informatique, le processus R&D s鈥檌nterrompt et les op茅rations tournent au ralenti.听

Gr芒ce 脿 l鈥檕bservabilit茅 unifi茅e, les entreprises peuvent acc茅l茅rer de 58鈥�% la connexion aux applications et optimiser l鈥檈xp茅rience digitale pour faire gagner un temps pr茅cieux aux scientifiques. C么t茅鈥疘T, les 茅quipes s鈥檃ssurent que chaque seconde gagn茅e est r茅investie dans la recherche et le progr猫s.听听

Quand les syst猫mes鈥疘T critiques impulsent la croissance听听

En optimisant leur environnement鈥疘T, les entreprises pharmaceutiques r茅duisent le risque d鈥檈rreurs et boostent la performance des applications pour lib茅rer tout le potentiel de leurs syst猫mes. 脌 la cl茅, des op茅rations rationalis茅es et une productivit茅 accrue 脿 l鈥櫭ヽhelle de l鈥檕rganisation.听

En aidant leurs collaborateurs 脿 se recentrer sur leur c艙ur de m茅tier, ces entreprises acc茅l猫rent la mise sur le march茅 des m茅dicaments et augmentent ainsi leur chiffre d鈥檃ffaires.听

Recentrer l鈥櫭﹒uipe鈥疘T sur des projets 脿 forte valeur ajout茅e听听

Autrefois consid茅r茅e comme une simple fonction de support, l鈥橧T est devenue aujourd鈥檋ui un v茅ritable agent de transformation. Dans ce nouveau paradigme, investir dans une r茅solution des probl猫mes automatis茅e et pilot茅e par IA fait figure de priorit茅. Lib茅r茅es des t芒ches r茅p茅titives, les 茅quipes techniques se concentrent sur les projets 脿 forte valeur ajout茅e, plus gratifiants pour ces forces vives de l鈥檈ntreprise.听

En ce sens, l鈥檕bservabilit茅 unifi茅e peut r茅duire de 70鈥�% le temps moyen de r茅solution鈥�(MTTR), permettant ainsi aux entreprises de se focaliser sur d鈥檃utres enjeux鈥�: adoption des nouvelles technologies, recherche, processus de d茅veloppement, optimisation des activit茅s et initiatives de croissance.听

Qualit茅, RSE et r茅duction du risque鈥�: trois鈥痯iliers essentiels de la confiance听听

Les laboratoires pharmaceutiques doivent se recentrer sur l鈥檈xp茅rience patient et la communication pour 脿 la fois soigner leur image et pr茅server leur influence dans le secteur. Assurer l鈥檌nt茅grit茅 des donn茅es et cr茅er un socle technologique r茅silient pour prot茅ger l鈥檕rganisation n鈥檈st plus une option, c鈥檈st une n茅cessit茅 absolue.听

Le d茅veloppement durable et l鈥檕ptimisation de la supply鈥痗hain font 茅galement partie de ces nouvelles priorit茅s. Gr芒ce 脿 l鈥檕bservabilit茅 unifi茅e, les 茅quipes鈥疘T participent activement 脿 la concr茅tisation de ces objectifs. Elles op猫rent un suivi des 茅missions carbone du parc鈥痠nformatique, optimisent le renouvellement des postes de travail pour r茅duire le gaspillage, et limitent la consommation d鈥櫭﹏ergie li茅e au trafic sortant des syst猫mes鈥痗loud.听

脡crire l鈥檃venir de la pharmaceutique听听

V茅ritable levier d鈥檌nnovation et d鈥檈fficacit茅, 麻豆学生精品版 Unified鈥疧bservability acc茅l猫re la transformation digitale des entreprises pharmaceutiques. Bien au-del脿 de la seule am茅lioration de l鈥檌nfrastructure鈥疘T, cette solution donne aux scientifiques, aux techniciens et 脿 tous les intervenants de la R&D les informations et les outils indispensables 脿 leurs missions. Comme le dit le proverbe鈥�: le temps, c鈥檈st de l鈥檃rgent. Avec 麻豆学生精品版 Unified鈥疧bservability, vous savez que chaque seconde gagn茅e est r茅investie dans le progr猫s et l鈥檈xcellence. Pour d茅couvrir comment 麻豆学生精品版 transforme votre environnement鈥疘T et optimise votre activit茅, cliquez ici.听

Les dirigeants semblent conscients de ces enjeux, selon notre enqu锚te intitul茅e 芦听Exp茅rience digitale des collaborateurs听(DEX)听: 茅tude mondiale听2023听禄. Men茅e aupr猫s de 1听800听d茅cideurs des fonctions听IT et m茅tiers, r茅partis dans 10听pays et sept secteurs d鈥檃ctivit茅, cette 茅tude r茅v猫le que 98听% des dirigeants de la finance-assurance estiment qu鈥檜ne DEX irr茅prochable est importante pour rester comp茅titifs. Ils sont m锚me 62听% 脿 la consid茅rer comme 芦听extr锚mement importante听禄.

Banque en ligne, DAB, centres d鈥檃ppel, agences鈥� chaque canal g茅n猫re un flux continu de donn茅es stock茅es sur des syst猫mes silot茅s. D鈥檕霉 l鈥檌mpossibilit茅 de surveiller manuellement chaque transaction et d鈥檌dentifier les 茅ventuels probl猫mes. Sans parler du fait que l鈥檃nalyse manuelle des donn茅es co没te cher, tant en termes financiers que de productivit茅.

Et quand certains collaborateurs cl茅s quittent l鈥檈ntreprise ou partent en retraite apr猫s de nombreuses ann茅es, c鈥檈st toute une mine de connaissances qu鈥檌ls emportent avec eux. Pour les remplacer, les recrues des g茅n茅rations听Y et Z exigent quant 脿 elles des processus efficaces et des technologies avanc茅es. En tant que 芦听digital-natives听禄, elles sont habitu茅es 脿 utiliser les meilleurs outils qui soient. Si vous ne parvenez pas 脿 r茅pondre 脿 leurs attentes, vous risquez d鈥檈nclencher une spirale de d茅parts et de recrutements co没teux et chronophages, tout en creusant davantage le d茅ficit de comp茅tences.

Les conclusions de notre enqu锚te le prouvent. Selon les dirigeants du secteur de la finance et de l鈥檃ssurance, 69听% des collaborateurs seraient pr锚ts 脿 quitter l鈥檈ntreprise s鈥檌ls 茅taient insatisfaits de leur DEX. Pour 68听% des sond茅s, toute incapacit茅 脿 satisfaire ces attentes digitales pourrait perturber l鈥檃ctivit茅 de l鈥檈ntreprise, nuire 脿 sa r茅putation, 脿 sa productivit茅 et aux performances organisationnelles. En outre, si vous faites partie des 84听% de d茅cideurs interrog茅s qui reconnaissent l鈥檌mportance croissante de l鈥橧T au sein du Comex, vous assumez certainement une fonction plus centrale 脿 ce niveau hi茅rarchique depuis quelques ann茅es. Cette tendance s鈥檈st acc茅l茅r茅e depuis la pand茅mie, qui a pr茅cipit茅 la transition vers le travail hybride et promu la tech et la data au rang de leviers strat茅giques. Aujourd鈥檋ui, les m茅tiers se tournent donc vers les responsables听IT pour relever tous ces d茅fis.

Et c鈥檈st l脿 que les solutions d鈥檕bservabilit茅 unifi茅e interviennent听: des outils intelligents capables de simplifier votre infrastructure, r茅duire le risque, renforcer votre r茅putation, baisser les co没ts et fid茅liser vos meilleurs talents. L鈥檕bservabilit茅 unifi茅e s鈥檈st d茅j脿 rendue indispensable dans le secteur. Pour preuve, 94听% des sond茅s de la finance-assurance voudraient voir plus d鈥檌nvestissement dans l鈥檕bservabilit茅 unifi茅e, qui selon eux leur fournirait les informations indispensables pour am茅liorer les exp茅riences digitales des collaborateurs et des clients. Le portefeuille de solutions d鈥檕bservabilit茅 unifi茅e de 麻豆学生精品版 apporte des solutions uniques et diff茅renciantes.

D茅couvrez comment exploiter ces technologies pour sublimer les exp茅riences digitales de chaque utilisateur, 脿 chaque point de contact听:

Diagnostic des probl猫mes tout au long du parcours client

Difficile de penser strat茅gie 脿 long terme lorsque l鈥檕n est constamment en mode pompier. Une situation bien trop famili猫re pour Halkbank, l鈥檜ne des banques les plus importantes et les plus anciennes de Turquie. D猫s le d茅but de la pand茅mie de Covid-19, les clients se sont tourn茅s vers les canaux digitaux. Halkbank a alors d没 adapter sa plateforme de banque mobile pour g茅rer plus du double du trafic, pass茅 de 1听million de clients 脿 2,5听millions en tr猫s peu de temps.

芦听En cas d鈥檌ndisponibilit茅 de notre plateforme mobile pour ne serait-ce que quelques heures, les clients ne pourraient pas acc茅der 脿 leurs comptes ni effectuer des transactions,听禄 explique Nam谋k Kemal U莽kan, Responsable des op茅rations听IT chez Halkbank. 芦听Notre objectif est d鈥檃ssurer 100听% de disponibilit茅 sur tous nos services. Il nous faut donc une solution qui nous permette de g茅rer notre r茅seau en mode proactif plut么t que r茅actif.听禄

Aujourd鈥檋ui, la banque utilise la solution 麻豆学生精品版 Network Performance Management (NPM) pour surveiller les services critiques sur son r茅seau et son data center depuis Alluvio Portal, qui consolide et affiche les donn茅es dans des tableaux de bord intuitifs. L鈥檕util identifie toute baisse de performance sur les plus de 40 applications vitales de Halkbank, et ce avant m锚me que les utilisateurs ne soient impact茅s.

Suivi des tendances utilisateurs

En plus de d茅tecter les probl猫mes de mani猫re proactive, la solution d鈥檕bservabilit茅 unifi茅e de 麻豆学生精品版 permet de suivre les tendances en mati猫re de transactions (types, sch茅mas, etc.), de rep茅rer les processus trop longs dans le parcours client ou collaborateur, et de cr茅er des raccourcis automatiquement. Tous vos utilisateurs b茅n茅ficient ainsi de syst猫mes 脿 la fois 100听% disponibles, performants et ergonomiques, avec 脿 la cl茅 des gains de temps et une baisse des co没ts.

La visibilit茅 sur ces tendances vous aide 脿 prendre des d茅cisions plus strat茅giques et plus 茅clair茅es, fond茅es sur les donn茅es. Vous savez dans quels domaines de l鈥檈ntreprise accentuer ou r茅duire les investissements, sans les risques habituels associ茅s. Par exemple, vous constatez que les clients d鈥檜ne certaine r茅gion tendent 脿 abandonner les DAB au profit de services en agence. Vous pouvez alors d茅commissionner les distributeurs sous-utilis茅s et r茅investir les 茅conomies de maintenance dans le recrutement de charg茅s de client猫le ou dans l鈥檈xtension de l鈥檕ffre en agence.

Les 茅quipements ne sont pas les seuls 茅l茅ments concern茅s. Les outils d鈥檕bservabilit茅 unifi茅e de 麻豆学生精品版 offrent une perspective unique sur l鈥檜tilisation r茅elle des applications par vos utilisateurs. Vous pouvez identifier toutes les licences et logiciels sous-utilis茅s pour les supprimer ou les d茅sinstaller comme bon vous semble, r茅duisant ainsi consid茅rablement vos co没ts听IT.

Respect des r茅glementations

Le portefeuille 麻豆学生精品版 d鈥檕bservabilit茅 unifi茅e permet de r茅soudre les probl猫mes de transactions et de rep茅rer les anomalies potentielles. Autant de fonctionnalit茅s qui vous aideront 脿 respecter des r茅glementations de plus en plus strictes. C么t茅 utilisateurs, la d茅tection de toute activit茅 web suspecte assure leur protection en ligne.

C鈥檈st d鈥檃illeurs une fonctionnalit茅 pris茅e par Halkbank, comme le note Nam谋k Kemal U莽kan听: 芦听Nous sommes tr猫s satisfaits de nos nouveaux outils, notamment le suivi des certificats听SSL qui nous aide 脿 pr茅server la s茅curit茅 des donn茅es pendant la navigation sur Internet.听禄

Identification des machines sous-performantes

D鈥檃pr猫s notre 茅tude, 88听% des dirigeants de la finance-assurance estiment que les technologies vieillissantes, les syst猫mes lents et les applications sous-performantes impactent directement la croissance et les performances. Pourtant, quel que soit le secteur, les parcs informatiques suivent un cycle de renouvellement bas茅 sur la dur茅e de vie plut么t que sur la performance r茅elle. Les DAB n鈥櫭ヽhappent pas 脿 la r猫gle, tout comme les nombreuses machines install茅es au si猫ge de l鈥檈ntreprise.

Une vraie solution d鈥檕bservabilit茅 unifi茅e analyse la rapidit茅 et l鈥檈fficacit茅 de chaque mat茅riel, y compris les performances transactionnelles, afin de ne remplacer que les machines qui en ont vraiment besoin. En plus de r茅duire le gaspillage, vous offrez une exp茅rience fiable et homog猫ne 脿 vos clients et vos collaborateurs. C么t茅 logiciels, les solutions 麻豆学生精品版 Aternity Digital Experience Management aident 脿 茅tablir les co没ts et 脿 mesurer les effets de projets听IT strat茅giques (mobilit茅 cloud, transformation de data center, etc.), mais aussi d鈥檃ctivit茅s de routine comme les mises 脿 niveau de syst猫mes d鈥檈xploitation et d鈥檃pplications.

Vous cherchez 脿 optimiser votre infrastructure hybride tout en assurant la rapidit茅, l鈥檃gilit茅 et la s茅curit茅 de vos applications, quels que soient le r茅seau et l鈥檜tilisateur听? Rendez-vous sur notre site pour en savoir plus sur le portefeuille d鈥檕bservabilit茅 unifi茅e de 麻豆学生精品版.

Mais quelles sont les implications pour les soci茅t茅s de services financiers et autres compagnies d鈥檃ssurance听? Et comment r茅aliser les ambitions fix茅es dans votre plan RSE听? Dans une vid茅o consacr茅e 脿 ce sujet, Jaspreet听Sandhu, Ing茅nieur听solutions chez 麻豆学生精品版, nous donne un 茅l茅ment de r茅ponse听: 芦听Le d茅veloppement durable renvoie 脿 la conciliation des besoins de l鈥檋umain, de la plan猫te et des entreprises pour conjuguer les imp茅ratifs financiers et environnementaux.听禄

Les organisations du monde entier font du d茅veloppement durable une priorit茅 absolue. Selon un r茅cent rapport de Forrester, 51听% des entreprises du Fortune听Global听200 se sont ainsi fix茅 des objectifs de neutralit茅 carbone 脿 plus ou moins court terme. Malgr茅 ces engagements forts, nombre d鈥檈ntre elles peinent 脿 maintenir le cap, faute de donn茅es fiables pour 茅tayer leur reporting听RSE.

Pour les aider 脿 surmonter ces obstacles, 麻豆学生精品版 met 脿 leur disposition un portefeuille de solutions ax茅es sur l鈥檕bservabilit茅 unifi茅e, avec trois objectifs cl茅s听:

• Offrir des exp茅riences digitales d鈥檈xception
• Prot茅ger la plan猫te en r茅duisant la consommation d鈥櫭﹏ergie
• R茅aliser des 茅conomies tout en r茅pondant aux attentes des parties prenantes

Adapter le parc mat茅riel et logiciel pour r茅duire l鈥檈-gaspillage (et les co没ts)

Les syst猫mes cloisonn茅s et les donn茅es disparates ne permettent de dresser qu鈥檜n tableau parcellaire de l鈥檜tilisation des logiciels et mat茅riels informatiques de l鈥檈ntreprise. 脌 l鈥檌nverse, les outils d鈥檕bservabilit茅 unifi茅e de 麻豆学生精品版 s鈥檃ppuient sur des sources internes et externes pour corr茅ler d鈥櫭﹏ormes volumes de donn茅es sur l鈥檜tilisation des licences et des machines听鈥� des PC de vos collaborateurs jusqu鈥檃ux DAB.

Les outils 麻豆学生精品版 transforment ensuite ces donn茅es en insights actionnables et en workflows automatis茅s afin de favoriser une prise de d茅cision efficace. Vous avez d猫s lors toutes les cartes en main pour r茅cup茅rer les licences non utilis茅es et d茅commissionner, voire recycler le mat茅riel ancien ou inactif. Non seulement vous pourrez d茅sencombrer vos data centers et espaces de travail, mais aussi r茅duire votre empreinte carbone. Apr猫s tout, les data centers repr茅sentent 脿 eux seuls de la consommation mondiale d鈥櫭﹏ergie (et vous co没tent sans doute assez cher).

Notre premi猫re success story nous vient de Tate & Lyle. Cet acteur historique de l鈥檃groalimentaire a r茅alis茅 des 茅conomies substantielles gr芒ce 脿 搁颈惫别谤产别诲听础迟别谤苍颈迟测. L鈥檈ntreprise a en effet am茅lior茅 son retour sur investissement en se d茅lestant de licences logicielles co没teuses et inutiles.

Qu鈥檌mporte l鈥櫭e, pourvu qu鈥檕n ait la performance

Vous remplacez vos 茅quipements sur des cycles de deux, trois, quatre ou cinq ans, ind茅pendamment de leurs performances听? Dans ce cas, vous vous s茅parez sans doute pr茅matur茅ment de machines encore tout 脿 fait viables. 脌 l鈥檌nverse, vous auriez aussi tout 脿 gagner d鈥檜n remplacement anticip茅 des machines fatigu茅es, qui nuisent 脿 la productivit茅 et 脿 la satisfaction de vos collaborateurs. Gr芒ce aux solutions 麻豆学生精品版, vous b茅n茅ficiez d鈥檜ne visibilit茅 et de pr茅visions en temps r茅el sur les performances de tous les 茅quipements de votre parc. Des tableaux de bord clairs dressent ainsi un bulletin de sant茅 de chaque 茅quipement, ce qui vous permet de pr茅voir selon sa dur茅e de vie restante, et non plus de sa dur茅e de vie pass茅e.

搁颈惫别谤产别诲听础迟别谤苍颈迟测 a 茅galement aid茅 l鈥櫭﹒uipe听IT du Kent Community Health Foundation Trust 脿 prendre de meilleures d茅cisions en mati猫re d鈥檌nvestissement. 芦听Nous avons revu notre plan de renouvellement du parc en nous basant sur les performances des 茅quipements听禄, explique Darren听Spinks, responsable des op茅rations听IT. 芦听Aternity nous a montr茅 que nous n鈥檃vions besoin de remplacer que 42听% de notre parc de 1784听appareils datant de cinq听ans ou plus. Nous avons donc d茅j脿 rentabilis茅 notre investissement dans la solution 搁颈惫别谤产别诲听础迟别谤苍颈迟测.听禄

De son c么t茅, la filiale britannique d鈥�EDF utilise Aternity de la m锚me mani猫re. Donna听Lloyd, Senior Enterprise Manager of 麻豆学生精品版s & Enablement, pr茅cise听: 芦听Au moment de migrer vers Windows听10, nous avons dress茅 un 茅tat des lieux complet du parc pour cibler en priorit茅 les machines les plus lentes Une fois les nouveaux postes install茅s, les statistiques de performance nous ont permis de d茅montrer clairement la diff茅rence.听禄

Des probl猫mes qui disparaissent avant m锚me d鈥檃ppara卯tre

La plateforme d鈥檕bservabilit茅 unifi茅e de 麻豆学生精品版 a un autre avantage听: elle vous fait gagner du temps, 茅conomiser de l鈥檃rgent et 茅viter une bonne dose de stress en 茅liminant les probl猫mes 脿 la racine.

Par exemple, la solution Aternity permet au Kent Community Health Foundation Trust de mettre en place des actions correctives automatiques, qui r茅duisent le nombre d鈥檃ppels au helpdesk et r茅solvent les incidents en toute autonomie, avant m锚me que les utilisateurs se rendent compte du moindre dysfonctionnement. L鈥櫭﹒uipe听IT peut 茅galement suivre la consommation de ses machines et adapter les param猫tres d鈥檃limentation en cons茅quence afin de r茅duire son empreinte carbone. Cette d茅marche s鈥檌nscrit dans le cadre du programme de d茅veloppement durable du NHS, qui ambitionne de devenir le premier service de sant茅 au monde 脿 atteindre la neutralit茅 carbone.

Rappeler les bons gestes aux collaborateurs

Au rang des mauvaises habitudes qui peuvent co没ter cher sur votre facture et tr猫s cher pour la plan猫te, nous citerons notamment les collaborateurs qui s鈥檃bsentent sans 茅teindre leur ordinateur. 搁颈惫别谤产别诲听础迟别谤苍颈迟测 peut vous aider 脿 combattre ce fl茅au en surveillant l鈥檜tilisation des 茅quipements et en envoyant aux personnes concern茅es des notifications au moment opportun, comme 脿 l鈥檋eure du d茅jeuner ou en fin de journ茅e. En l鈥檃bsence de r茅action de leur part, Aternity vous permet 茅galement d鈥櫭﹖eindre les machines 脿 distance.

Garder un 艙il sur l鈥檈mpreinte carbone

Enfin, la solution Aternity de 麻豆学生精品版 int猫gre de nombreuses fonctionnalit茅s et fonctions qui peuvent vous aider 脿 agir en faveur du d茅veloppement durable par une meilleure connaissance des rouages de votre entreprise et des leviers 脿 actionner pour impulser le changement.

Le Princess Alexandra Hospital NHS Trust a fait le choix d鈥橝ternity pour r茅duire ses co没ts ainsi que son empreinte carbone. Cette fondation devrait ainsi r茅aliser une 茅conomie de l鈥檕rdre de 2,5 脿 3听millions de livres sterling sur une p茅riode de cinq ans. Mais ce n鈥檈st pas tout. La solution lui permet aussi de trouver dans ses donn茅es des pistes d鈥檃m茅lioration pour un num茅rique plus responsable.

Comme l鈥檈xplique Jeffrey听Wood, son directeur adjoint des solutions TIC听: 芦听Les soignants b茅n茅ficient d茅sormais d鈥檜ne source d鈥檌nformation centralis茅e. Nous avons 茅galement am茅lior茅 les performances applicatives et all茅g茅 nos d茅penses en听TIC, tout en r茅duisant notre empreinte carbone. 搁颈惫别谤产别诲听础迟别谤苍颈迟测 a donc d茅pass茅 mes attentes sur tous les fronts.听禄

N鈥檕ubliez pas de vous rendre sur notre page sp茅ciale d茅veloppement durable et contactez notre 茅quipe pour d茅couvrir comment atteindre voire surpasser les objectifs听RSE propres aux acteurs des services financiers et de l鈥檃ssurance.

Pour rester dans la course, attirer de nouveaux clients et multiplier les relais de croissance, les banques doivent engager une refonte totale de leur mod猫le autour de trois axes听: 1) moderniser leurs principaux processus internes, 2) acc茅l茅rer leur transformation digitale pour r茅pondre aux nouvelles exigences des clients et 3) accro卯tre leur rentabilit茅. Cet article vous invite 脿 d茅couvrir comment les banques peuvent actionner le triptyque donn茅es/information/action gr芒ce 脿 l鈥檕bservabilit茅 unifi茅e de 麻豆学生精品版. L鈥檕bjectif听: fluidifier les op茅rations, acc茅l茅rer et simplifier les d茅cisions de transformation, et am茅liorer l鈥檈xp茅rience omnicanale des collaborateurs et des clients.

R茅inventer les syst猫mes bancaires pour am茅liorer le pilotage op茅rationnel

La technologie qui sous-tend la banque mobile est celle-l脿 m锚me qui menace les mod猫les bancaires traditionnels. R茅duction des erreurs, am茅lioration des performances applicatives, efficacit茅 accrue des 茅quipes鈥� pour lib茅rer tout le potentiel de leurs syst猫mes bancaires, les 茅tablissements de cr茅dit doivent insuffler une nouvelle dynamique au sein de leurs agences et en optimiser les services.

Cela passe par des interactions plus efficaces entre les charg茅s de client猫le et les clients, par l鈥檌nstallation de bornes en libre-service et par le renforcement des canaux web et mobiles. Mais qui dit d茅pendance au digital, dit aussi obligation de fluidit茅 et de fiabilit茅 des syst猫mes. Une condition pas toujours facile 脿 tenir, 脿 l’heure o霉 les volumes de donn茅es explosent et o霉 les infrastructures traditionnelles contraignent les banques 脿 s’ancrer dans le pass茅 au lieu de se projeter vers l’avenir.

C鈥檈st l脿 qu鈥檌nterviennent l鈥檕bservabilit茅 unifi茅e et ses fonctionnalit茅s de correction automatique des dysfonctionnements. Gr芒ce 脿 elles, les banques r茅solvent facilement les probl猫mes sur l鈥檈nsemble de leur architecture avant que les clients ne soient impact茅s. Elles pr茅servent ainsi leur r茅putation tout en instaurant le climat de confiance n茅cessaire pour leurs d茅posants. Pour l鈥檜n de nos clients, ces outils proactifs ont d鈥檃illeurs r茅duit de 20 脿 30听% les tickets de support.

La d茅tection et la correction plus rapides des dysfonctionnements apportent de multiples avantages aux 茅tablissements bancaires听: optimisations strat茅giques, gains d鈥檈fficacit茅, acc茅l茅ration du temps moyen de r茅solution (MTTR) et r茅duction du temps pass茅 sur des probl猫mes mineurs. Pour vos 茅quipes, ces fonctionnalit茅s limitent le nombre de notifications 脿 traiter, r茅duisant ainsi l鈥檃ccoutumance aux alertes, le niveau de stress et le turnover. Autant d鈥檃vantages ind茅niables 脿 l鈥檋eure o霉 le secteur conna卯t une p茅nurie de talents et de comp茅tences.

Miser sur l鈥檕bservabilit茅 unifi茅e, c鈥檈st simplifier les processus, rationaliser les op茅rations et r茅duire directement les co没ts. Elle permet en effet d鈥檌dentifier les technologies sous-utilis茅es et d鈥檕ptimiser les r茅seaux, les appareils et les applications les plus sollicit茅s. Gr芒ce 脿 麻豆学生精品版, un autre client a 茅conomis茅 pr猫s de 600听000听拢 sur chaque application suivie par notre technologie. Dans une autre banque cliente, l鈥櫭﹒uipe听IT est parvenue 脿 allonger la dur茅e de vie de ses 茅quipements pour 茅viter un renouvellement non essentiel de mat茅riel qui lui aurait co没t茅 16听millions听$.

R茅inventer la modernisation des banques pour acc茅l茅rer leur transformation

Aujourd鈥檋ui, les consommateurs recherchent toujours plus de commodit茅. C鈥檈st pourquoi ils tendent 脿 privil茅gier une exp茅rience que seules la banque en ligne et les applications peuvent leur offrir. Mais m锚me si la pr茅sence physique des banques se r茅duit, l鈥檈xp茅rience en pr茅sentiel reste cruciale et ne doit pas 锚tre sous-estim茅e.

Pour les 茅tablissements de cr茅dit, l鈥檕bservabilit茅 unifi茅e sert 茅galement 脿 optimiser les interactions en agence听: reporting en direct sur les op茅rations des charg茅s de client猫le et des DAB, correction automatique gr芒ce aux outils pr茅cit茅s, validation des changements, et bien plus encore. L鈥檜n de nos clients a ainsi d茅couvert des disparit茅s dans les modes de fonctionnement de ses agences, notamment dans les niveaux de service 脿 la client猫le. Toujours gr芒ce 脿 nos outils, la banque a pu r茅tablir la situation en offrant une exp茅rience homog猫ne dans toutes ses agences. Un autre 茅tablissement s鈥檈st vu contraint de passer de 1听000听t茅l茅travailleurs 脿 22听000 en quatre semaines seulement. Pour ce faire, il s鈥檈st appuy茅 sur notre plateforme pour visualiser les r茅gions o霉 le t茅l茅travail 茅tait le plus pratiqu茅 et identifier les fermetures d鈥檃gences potentielles, r茅duisant ainsi les co没ts sans perdre en productivit茅.

Banque en ligne et mobile, agence traditionnelle, centre de contact, distributeurs automatiques鈥� 脿 l鈥檋eure du phygital, les banques doivent imp茅rativement cr茅er un environnement technologique propice 脿 des interactions efficaces et 脿 des services bancaires innovants, omnicanaux et centr茅s sur le client. En ce sens, une plateforme d鈥檕bservabilit茅 unifi茅e garantit que chaque application听鈥� sur n鈥檌mporte quel appareil ou canal听鈥� atteigne, voire d茅passe le niveau de service n茅cessaire pour impulser l鈥檃ctivit茅, et non la freiner.

R茅inventer le parcours bancaire pour parfaire l鈥檈xp茅rience

Les banques doivent optimiser chaque point de contact client, quelles que soient ses exigences, pour passer d’une approche purement transactionnelle 脿 une d茅marche centr茅e sur la qualit茅 de l’exp茅rience. Leurs 茅quipes peuvent ainsi g茅n茅rer de nouvelles opportunit茅s commerciales tout en am茅liorant l’accompagnement client, notamment gr芒ce 脿 des fonctionnalit茅s听IA qui offrent une visibilit茅 compl猫te sur l鈥檈xp茅rience omnicanale.

L鈥檕bservabilit茅 unifi茅e permet aux acteurs de la banque de convertir des donn茅es disparates en 茅clairages intelligents sur les utilisateurs, enclenchant ainsi un v茅ritable 茅lan de croissance de leurs revenus. Nombre de nos clients l鈥檕nt d茅j脿 adopt茅e pour axer leurs efforts sur l鈥檃m茅lioration de l鈥檈xp茅rience digitale par le biais de fonctionnalit茅s cl茅s听: identification des mises 脿 niveau potentielles pour les r茅seaux et les 茅quipements, comparaison des exp茅riences collaborateurs et des niveaux de productivit茅, et suivi du niveau de satisfaction au sein de chaque business unit avant, pendant et apr猫s l鈥檌mpl茅mentation de changements (nouvelles versions logicielles, par exemple).

R茅inventer la s茅curit茅 et impulser le d茅veloppement durable

Entre d茅pendance croissante aux applications cloud, au SaaS et au Shadow IT d’une part, et g茅n茅ralisation du travail hybride d’autre part, la surface de risque s’est consid茅rablement 茅largie dans le secteur bancaire, entra卯nant ainsi un durcissement du cadre r茅glementaire. C’est ainsi que les banques sont tenues de respecter des r猫gles strictes pour op茅rer en toute l茅galit茅, maintenir leur stabilit茅 financi猫re, g茅rer efficacement les risques, prot茅ger leur r茅putation et instaurer une relation de confiance avec les clients et les parties prenantes.

Forte des performances in茅gal茅es de son monitoring, notre plateforme d鈥檕bservabilit茅 unifi茅e aide les 茅tablissements bancaires 脿 renforcer leur image de marque. En plus d鈥檃ssurer leur conformit茅, ils peuvent identifier et corriger les vuln茅rabilit茅s de plusieurs mani猫res simples et innovantes听: modernisation des applications bancaires existantes gr芒ce 脿 l鈥檌ntelligence artificielle et 脿 l鈥檃utomatisation, transformation des r茅seaux de leurs agences, int茅gration d’outils de gouvernance et de contr么le, et d茅cisions bas茅es sur des donn茅es essentielles. Nos solutions examinent l鈥檜tilisation des applications, et capturent et stockent chaque paquet et flux pour passer au crible les comportements suspects du r茅seau.

En plus de mettre l鈥檃ccent sur la s茅curit茅, les banques tendent 脿 s’inscrire de plus en plus dans une d茅marche de d茅veloppement durable. En op茅rant ainsi, elles souhaitent rester en phase avec un monde o霉 la fid茅lit茅 des clients est de plus en plus fragile, et o霉 les enjeux de protection de l’environnement doivent prendre le pas sur le profit.

L鈥檕bservabilit茅 unifi茅e accompagne les strat茅gies de d茅veloppement durable et m猫ne les banques sur la voie de la neutralit茅 carbone de bien des mani猫res diff茅rentes. Un exemple听: la plateforme peut identifier les 茅quipements et les infrastructures les plus gourmands en 茅nergie, informer les collaborateurs de leur consommation, et leur rappeler d鈥櫭﹖eindre leur poste au lieu de le laisser en veille. Les appareils 茅nergivores, comme les ordinateurs portables, peuvent m锚me 锚tre 茅teints 脿 distance lorsqu鈥檌ls ne sont pas utilis茅s.

Prenez l’avenir de votre banque en main

En transformant les donn茅es en information, et l’information en actions, 麻豆学生精品版 aide les banques 脿 prendre des d茅cisions plus rapides et plus efficaces tout en am茅liorant continuellement l鈥檈xp茅rience omnicanale des collaborateurs et des clients. Contactez-nous pour d茅couvrir comment nos solutions d鈥檕bservabilit茅 unifi茅e peuvent vous aider 脿 cr茅er la banque de demain, une banque r茅solument plac茅e sous le signe de l鈥檈xp茅rience.

Cependant, m锚me en tenant compte de sa nature critique, l鈥橧T repr茅sente en r茅alit茅 une d茅pense importante pour de nombreuses entreprises. Heureusement, il existe souvent des moyens de r茅duire le budget IT sans sacrifier l鈥檈xp茅rience digitale, la productivit茅 des employ茅s ou la satisfaction des clients. La seule difficult茅 consiste 脿 d茅terminer o霉 effectuer ces r茅ductions budg茅taires et par o霉 commencer.

Dans ce blog, nous vous donnons trois conseils pour r茅duire vos co没ts IT听: comment identifier les bons 茅quipements 脿 mettre 脿 niveau, l鈥檌mportance de la budg茅tisation IT et une liste de contr么le pour la r茅duction des co没ts IT.

Identifier les bons 茅quipements 脿 mettre 脿 niveau

La premi猫re 茅tape de l鈥檕ptimisation des co没ts IT consiste 脿 茅valuer l鈥檌nfrastructure existante. Cette 茅valuation vous aidera 脿 d茅terminer les 茅quipements qui doivent doit 锚tre mis 脿 niveau ou remplac茅s.

Voici trois conseils pour vous aider 脿 identifier les bons 茅quipements 脿 mettre 脿 niveau听:

1. Prolonger la dur茅e de vie de l鈥櫭﹒uipement听: Alors que de nombreuses entreprises remplacent l鈥櫭﹒uipement en fonction de son 芒ge, vous pouvez 茅conomiser de l鈥檃rgent en vous concentrant sur les performances de l鈥櫭﹒uipement. Parfois, les anciens 茅quipements fonctionnent encore bien et n鈥檕nt pas besoin d鈥櫭猼re remplac茅s, ce qui permet de r茅aliser d鈥檌mportantes 茅conomies.
2. Un 茅quipement bien dimensionn茅 pour les employ茅s听: Assurez-vous de fournir 脿 vos employ茅s un 茅quipement ayant une puissance adapt茅e. Lors de l鈥檃ctualisation de l鈥櫭﹒uipement de vos employ茅s, 茅valuez leurs besoins. Si un employ茅 utilise principalement des applications l茅g猫res, il n鈥檃 peut-锚tre pas besoin d鈥檜n 茅quipement tr猫s puissant. En revanche, un employ茅 qui passe sa journ茅e 脿 utiliser des applications gourmandes en ressources aura besoin d鈥檜n 茅quipement capable de prendre en charge son cas d鈥檜tilisation.
3. Identifier les 茅quipements peu performants听: Tout comme il est possible de prolonger la dur茅e de service des 茅quipements anciens qui fonctionnent encore bien, certains 茅quipements plus r茅cents peuvent ne pas fonctionner aussi bien que pr茅vu. En identifiant ces 茅quipements, vous pouvez 锚tre en mesure de r茅soudre de mani猫re proactive les probl猫mes de performances afin de r茅duire les d茅penses.

Importance de la budg茅tisation IT

Une fois que vous avez identifi茅 les 茅quipements 脿 mettre 脿 niveau, l鈥櫭﹖ape suivante consiste 脿 茅laborer un budget IT. La budg茅tisation IT est essentielle pour g茅rer efficacement les co没ts IT.

Voici quelques b茅n茅fices cl茅s de la budg茅tisation IT听:

• Optimiser les licences logicielles听: 脡valuez les logiciels que vous utilisez et les licences dont vous disposez. Il est possible que vous payiez pour des licences inutilis茅es, que des employ茅s utilisent des logiciels redondants ou que des applications IT fant么mes augmentent vos co没ts logiciels.
• 脡valuer l鈥檌nfrastructure r茅seau听: 脡valuez l鈥檌nfrastructure r茅seau et identifiez les goulots d鈥櫭﹖ranglement. Cette 茅valuation vous aidera 脿 identifier les domaines dans lesquels vous pouvez mettre 脿 niveau ou rationaliser l鈥檌nfrastructure r茅seau afin de r茅duire les co没ts de la bande passante.
• 脡valuer les d茅penses li茅es au cloud听: Les co没ts du cloud peuvent augmenter rapidement lorsque vous passez 脿 des environnements cloud-native ou hybrides. Il est essentiel que vous examiniez attentivement et compreniez les factures de votre fournisseur cloud et que vous preniez des mesures pour r茅duire au minimum le trafic cloud inutile.
• 脡tablir des priorit茅s dans les d茅penses听: Identifiez les domaines d鈥檌nvestissement IT qui fourniront le meilleur ROI et concentrez-vous d鈥檃bord sur ces domaines de d茅penses. Mesurez l鈥檌mpact des changements planifi茅s et en cours sur des 茅l茅ments tels que l鈥檈xp茅rience digitale, les performances applicatives, la sant茅 de l鈥櫭﹒uipement et la performance r茅seau pour rentabiliser au maximum vos ressources.

Liste de contr么le pour la r茅duction des co没ts IT

Pour vous aider 脿 r茅duire les co没ts IT, suivez cette liste de contr么le rapide听:

• Aligner l鈥橧T sur les objectifs de l鈥檈ntreprise听: Veillez 脿 ce que vos investissements IT soient align茅s sur les objectifs de l鈥檈ntreprise, ce qui vous permet d鈥檕ptimiser les co没ts IT tout en stimulant la croissance de l鈥檈ntreprise.
• D茅terminer une strat茅gie d鈥檃ctualisation de l鈥櫭﹒uipement听: Identifiez l鈥櫭﹒uipement qui doit 锚tre remplac茅, celui qui peut 锚tre r茅par茅 et celui qui peut continuer 脿 锚tre utilis茅.
• Identifier les possibilit茅s d鈥櫭ヽonomiser听: Recherchez des moyens d鈥櫭ヽonomiser sur les d茅penses existantes dans des domaines tels que les licences logicielles, l鈥檜tilisation du cloud et la bande passante r茅seau.
• Automatiser les processus IT听: Automatisez les processus IT pour r茅duire le travail manuel et accro卯tre l鈥檈fficacit茅.

En conclusion, la r茅duction des co没ts IT est essentielle pour toutes les entreprises, et la cl茅 est d鈥檕ptimiser l鈥檌nfrastructure IT tout en minimisant les d茅penses inutiles.

La gestion de l鈥檈xp茅rience utilisateur est une consid茅ration importante pour les entreprises de toutes tailles, car elle peut avoir un impact significatif sur la productivit茅 du personnel, la satisfaction des clients et, en fin de compte, le succ猫s de l鈥檕rganisation. 脌 la base, la gestion de l鈥檈xp茅rience utilisateur s鈥檃ttache 脿 offrir une exp茅rience positive aux utilisateurs finaux, qu鈥檌l s鈥檃gisse d鈥檈mploy茅s, de clients ou de partenaires. Elle peut inclure tout un 茅ventail de capacit茅s, notamment la surveillance, l鈥檃nalyse et la mise en 艙uvre de strat茅gies visant 脿 am茅liorer les performances du syst猫me, de l鈥檃pplication et de l鈥櫭﹒uipement.

Aussi clair que cela puisse para卯tre, les fournisseurs et les leaders d鈥檕pinion du march茅 s猫ment la confusion en utilisant toute une s茅rie de termes apparent茅s pour d茅crire cet objectif. La surveillance de l鈥檈xp茅rience digitale, la gestion de l鈥檈xp茅rience digitale et la gestion de l鈥檈xp茅rience digitale des employ茅s sont autant de noms diff茅rents pour des cat茅gories de logiciels similaires. Le Market Guide de Gartner sur la surveillance de l鈥檈xp茅rience digitale donne une bonne vue d鈥檈nsemble des fournisseurs repr茅sentatifs.

Le r么le de la surveillance dans la gestion de l鈥檈xp茅rience utilisateur

La surveillance est un 茅l茅ment fondamental de la gestion de l鈥檈xp茅rience utilisateur. Elle vise 脿 suivre les performances des diff茅rents composants de l鈥檈nvironnement technologique qui influent sur l鈥檈xp茅rience utilisateur, notamment l鈥櫭﹒uipement, les serveurs, les applications et les ressources r茅seau. En collectant des donn茅es sur ces 茅l茅ments et en les mettant en corr茅lation, les entreprises peuvent mieux comprendre l鈥檕rigine des probl猫mes de performances qui nuisent 脿 l鈥檈xp茅rience utilisateur et identifier les possibilit茅s d鈥檃m茅lioration.

Par exemple, si les utilisateurs sont confront茅s 脿 de longs temps de chargement lorsqu鈥檌ls acc猫dent 脿 une application particuli猫re, le service IT peut utiliser des outils de surveillance de l鈥檈xp茅rience utilisateur pour suivre les performances de l鈥檃pplication et identifier les goulots d鈥櫭﹖ranglement ou autres probl猫mes susceptibles d鈥櫭猼re 脿 l鈥檕rigine du probl猫me. Les produits tels que notre plateforme de gestion de l鈥檈xp茅rience digitale听 Aternity permettent au service IT d鈥檌soler la source des ralentissements au niveau de l鈥櫭﹒uipement de l鈥檈mploy茅, du r茅seau ou du service d鈥檃pplication back-end. Le service IT peut alors approfondir la recherche de l鈥檕rigine du probl猫me et prendre les mesures appropri茅es pour l鈥檃m茅liorer. Il est important de noter que la surveillance des metrics indiquant la performance de l鈥櫭﹒uipement, des syst猫mes et des applications est n茅cessaire, mais pas suffisante pour une gestion efficace de l鈥檈xp茅rience utilisateur. La gestion des performances de l鈥櫭﹒uipement n鈥檈st pas la m锚me chose que la gestion de l鈥檈xp茅rience utilisateur. Ce n鈥檈st qu鈥檜n des facteurs.

L鈥檃nalyse au service de la gestion de l鈥檈xp茅rience utilisateur

Un autre 茅l茅ment important de la gestion de l鈥檈xp茅rience utilisateur est l鈥檃nalyse. En collectant et en analysant les donn茅es relatives 脿 l鈥檃ctivit茅 des utilisateurs et aux performances syst猫me, les entreprises affinent leur compr茅hension de la mani猫re dont leurs syst猫mes technologiques sont utilis茅s et identifier les possibilit茅s d鈥檃m茅lioration. Il peut s鈥檃gir d鈥檃nalyser des donn茅es sur le comportement des utilisateurs, comme la fr茅quence 脿 laquelle ils acc猫dent 脿 certaines applications ou le temps de r茅ponse de l鈥檃pplication qu鈥檌ls rencontrent lorsqu鈥檌ls effectuent certaines t芒ches au sein d鈥檜ne application m茅tier strat茅gique.

La plupart des produits de gestion de l鈥檈xp茅rience utilisateur permettent au service IT d鈥檌dentifier et de traiter les probl猫mes de mani猫re proactive avant qu鈥檌ls ne deviennent des probl猫mes majeurs. En surveillant les performances syst猫me et en analysant le comportement des utilisateurs, les entreprises peuvent identifier rapidement les probl猫mes potentiels et prendre des mesures pour 茅viter qu鈥檌ls n鈥檈ntra卯nent des perturbations importantes. Des produits comme 麻豆学生精品版 Aternity contiennent des capacit茅s de correction automatis茅e pour r茅soudre les probl猫mes les plus fr茅quents rencontr茅s par les utilisateurs finaux. Gr芒ce 脿 la correction automatis茅e, le service IT peut souvent rem茅dier 脿 un probl猫me d鈥檈xp茅rience utilisateur avant m锚me que les employ茅s ne s鈥檈n aper莽oivent. Regardez cette courte vid茅o pour d茅couvrir la correction automatis茅e en action听:

[embedyt] https://www.youtube.com/watch?v=cymqHOl3Nsg[/embedyt]

Avez-vous un exemple d鈥檈xp茅rience utilisateur听?

La performance d鈥檜ne application ou d鈥檜n site Web est un exemple courant d鈥檈xp茅rience utilisateur que tout le monde conna卯t. Les utilisateurs finaux attendent des applications et des sites Web qu鈥檌ls se chargent rapidement et qu鈥檌ls soient r茅actifs. Si une application prend beaucoup de temps 脿 charger ou est lente 脿 r茅pondre aux entr茅es de l鈥檜tilisateur, l鈥檈xp茅rience utilisateur en p芒tit. Cela peut avoir un impact majeur sur l鈥檈ntreprise. Par exemple, les montrent ce qui suit听:

• Le temps de chargement id茅al pour les sites Web mobiles est de 1 脿 2听secondes.
• 53听% des visites de sites mobiles sont abandonn茅es si les pages mettent plus de 3听secondes 脿 se charger.
• Un retard de 2听secondes dans le temps de chargement se traduit par des taux d鈥檃bandon allant jusqu鈥櫭� 87听%.

D鈥檃utres facteurs techniques peuvent avoir un impact sur l鈥檈xp茅rience utilisateur, notamment la connectivit茅 r茅seau, la disponibilit茅 du serveur et la qualit茅 de l鈥檌nterface utilisateur. Par exemple, si un utilisateur acc猫de 脿 une application via une connexion r茅seau lente ou peu fiable, cela peut entra卯ner des performances m茅diocres et de la frustration. De m锚me, si un serveur conna卯t des niveaux 茅lev茅s de trafic, cela peut entra卯ner des ralentissements au chargement et d鈥檃utres probl猫mes de performances.

Le d茅fi pour le service IT est qu鈥檃vec autant d鈥檈mploy茅s travaillant 脿 domicile, des facteurs tels que la puissance du signal Wi-Fi, la bande passante et les performances du fournisseur d鈥檃cc猫s 脿 Internet affectent 茅galement l鈥檈xp茅rience utilisateur. Mais ces facteurs 茅chappent au contr么le direct du service IT. L鈥橧T a besoin d鈥檜n syst猫me de surveillance tel que l鈥檕bservabilit茅 unifi茅e 麻豆学生精品版 , qui ing猫re des donn茅es t茅l茅m茅triques provenant de l鈥檈nsemble de l鈥檈nvironnement IT, pour mener des analyses et identifier les probl猫mes.

Pourquoi est-il important d鈥檃m茅liorer l鈥檈xp茅rience utilisateur听?

L鈥檜tilisation de la gestion de l鈥檈xp茅rience utilisateur pour fournir une exp茅rience utilisateur transparente et r茅active permet aux entreprises d鈥檃m茅liorer la productivit茅 de leur personnel et la satisfaction de leurs clients. Les b茅n茅fices sont les suivants听:

Pour les employ茅s听:

• Augmentation de la productivit茅听: Si les employ茅s ont acc猫s 脿 des syst猫mes technologiques rapides, fiables et faciles 脿 utiliser, ils accomplissent leurs t芒ches plus efficacement, ce qui am茅liore la productivit茅.
• R茅duction de la frustration et du stress听: Si les employ茅s sont en mesure d鈥檜tiliser les syst猫mes technologiques sans rencontrer de probl猫mes de performances, ils sont susceptibles de se sentir moins frustr茅s et moins stress茅s, ce qui peut am茅liorer le moral et la satisfaction au travail.
• Am茅lioration des performances au travail et de la r茅tention听: Les employ茅s qui sont satisfaits de leurs syst猫mes technologiques sont plus susceptibles de rester chez leur employeur actuel.

Pour les consommateurs听:

• Am茅lioration de la satisfaction et de la fid茅lit茅听: Si les consommateurs ont une exp茅rience positive lorsqu鈥檌ls utilisent les syst猫mes technologiques d鈥檜ne entreprise, ils sont plus susceptibles d鈥櫭猼re satisfaits des produits ou services de l鈥檈ntreprise et de devenir des clients fid猫les.
• Augmentation des ventes et du chiffre d鈥檃ffaires听: Les clients qui vivent une exp茅rience positive sont plus susceptibles de renouveler leurs achats et de recommander l鈥檈ntreprise 脿 d鈥檃utres personnes, ce qui peut entra卯ner une augmentation des ventes et du chiffre d鈥檃ffaires.
• Am茅lioration de la r茅putation de la marque听: Les entreprises qui accordent la priorit茅 脿 l鈥檈xp茅rience utilisateur et qui offrent une exp茅rience positive 脿 leurs clients sont susceptibles de se forger une solide r茅putation en mati猫re de qualit茅 et de service client, ce qui peut contribuer 脿 attirer de nouveaux clients et 脿 fid茅liser les clients existants.

Comment le travail hybride a-t-il modifi茅 l鈥檌mportance de la gestion de l鈥檈xp茅rience utilisateur听?

La pr茅valence du travail hybride ou 脿 distance a accru l鈥檌mportance de la gestion de l鈥檈xp茅rience utilisateur pour plusieurs raisons听:

D茅pendance accrue 脿 l鈥櫭ゞard de la technologie

Avec un nombre croissant d鈥檈mploy茅s travaillant 脿 distance, les entreprises s鈥檃ppuient sur les syst猫mes technologiques pour faciliter la communication, la collaboration et la productivit茅. L鈥檈xp茅rience utilisateur est donc devenue encore plus strat茅gique, car les employ茅s ont besoin de syst猫mes technologiques rapides, fiables et faciles 脿 utiliser pour accomplir leurs t芒ches efficacement.

Une plus grande complexit茅

Les environnements de travail hybrides ou 脿 distance peuvent 锚tre plus complexes que les environnements de bureau classiques, les employ茅s acc茅dant aux syst猫mes et aux applications 脿 partir de plusieurs endroits et appareils. Cette complexit茅 suppl茅mentaire peut rendre plus difficiles la gestion et l鈥檕ptimisation de l鈥檈xp茅rience utilisateur.

Probl猫mes de s茅curit茅 accrus

Le travail 脿 distance s鈥檃ccompagne 茅galement de probl猫mes de s茅curit茅 accrus, car les employ茅s peuvent acc茅der aux donn茅es sensibles de l鈥檈ntreprise 脿 partir de r茅seaux ou d鈥櫭﹒uipements non s茅curis茅s. Pour garantir une exp茅rience utilisateur positive tout en maintenant des mesures de s茅curit茅 robustes, les entreprises doivent trouver le bon 茅quilibre entre s茅curit茅 et facilit茅 d鈥檜tilisation.

Concurrence accrue pour les talents

Avec l鈥檈ssor du travail 脿 distance, les entreprises ne sont plus limit茅es 脿 l鈥檈mbauche d鈥檈mploy茅s dans leur r茅gion. Cela signifie que les entreprises sont en concurrence avec un plus grand nombre de soci茅t茅s pour attirer les meilleurs talents, et l鈥檈xp茅rience utilisateur peut 锚tre un facteur cl茅 pour attirer et retenir les employ茅s dans un march茅 o霉 le taux de ch么mage est faible.

Voici un aper莽u de la mani猫re dont 麻豆学生精品版 aide 脿 relever ces d茅fis du travail hybride.

Cinq 茅tapes pour am茅liorer l鈥檈xp茅rience utilisateur

Am茅liorer l鈥檈xp茅rience utilisateur peut s鈥檃v茅rer difficile lorsque les budgets IT sont serr茅s. Cependant, il existe plusieurs moyens pratiques pour permettre aux entreprises d鈥檃m茅liorer l鈥檈xp茅rience utilisateur tout en contr么lant les d茅penses.

1. Proc茅der 脿 un audit de l鈥檈xp茅rience utilisateur听: L鈥檃udit des syst猫mes et des processus actuels aide 脿 identifier les zones d鈥檌nefficacit茅 ou de frustration pour les utilisateurs finaux et fournit des renseignements sur la mani猫re d鈥檃m茅liorer l鈥檈xp茅rience globale. Les entreprises utilisent des enqu锚tes p茅riodiques pour recueillir des donn茅es sur l鈥檈xp茅rience des employ茅s, mais elles peuvent 茅galement faire de m锚me avec leurs outils de gestion de l鈥檈xp茅rience utilisateur.
2. Donner la priorit茅 aux commentaires des utilisateurs听: Les commentaires des utilisateurs sont un outil inestimable pour am茅liorer l鈥檈xp茅rience utilisateur. En donnant la priorit茅 aux commentaires des utilisateurs et en proc茅dant 脿 des changements sur la base de ces commentaires, les entreprises peuvent montrer qu鈥檈lles accordent de l鈥檌mportance 脿 l鈥檕pinion de leurs employ茅s et de leurs clients.
3. Optimiser les syst猫mes existants听: Souvent, les entreprises disposent de syst猫mes et de processus qui peuvent 锚tre optimis茅s pour am茅liorer l鈥檈xp茅rience utilisateur. Il peut s鈥檃gir de supprimer les 茅tapes inutiles d鈥檜n processus, de rationaliser les workflows ou d鈥檕ptimiser les performances des syst猫mes technologiques existants.
4. Mettre en place des outils en libre-service听: Les outils en libre-service, tels que les bases de connaissances ou les chatbots, contribuent 脿 r茅duire la frustration des utilisateurs finaux en leur offrant un acc猫s rapide et facile 脿 l鈥檌nformation ou 脿 l鈥檃ssistance. Ces outils sont relativement peu co没teux 脿 mettre en 艙uvre et contribuent 脿 am茅liorer l鈥檈xp茅rience utilisateur en r茅duisant les temps d鈥檃ttente et en augmentant l鈥檃ccessibilit茅.
5. Fournir une formation et une assistance听: La formation et l鈥檃ssistance aux utilisateurs finaux participent 茅galement 脿 am茅liorer l鈥檈xp茅rience globale. Il peut s鈥檃gir de proposer des sessions de formation sur les nouveaux syst猫mes ou processus ou de mettre 脿 disposition du personnel d鈥檃ssistance sp茅cialis茅 pour aider 脿 r茅soudre les probl猫mes techniques.

Dans l鈥檈nsemble, l鈥檃m茅lioration de l鈥檈xp茅rience utilisateur ne n茅cessite pas n茅cessairement un investissement financier important. En donnant la priorit茅 aux commentaires des utilisateurs, en optimisant les syst猫mes existants, en mettant en place des outils en libre-service et en fournissant une formation et une assistance, les entreprises peuvent apporter des am茅liorations significatives 脿 l鈥檈xp茅rience utilisateur, m锚me dans des environnements 脿 budget limit茅.

Faites le premier pas vers une meilleure exp茅rience utilisateur d猫s maintenant

Vous pouvez explorer la gestion de l鈥檈xp茅rience utilisateur d猫s maintenant en vous inscrivant 脿 une demo gratuite d鈥櫬槎寡钒� Aternity. T茅l茅chargez notre logiciel pour comprendre comment notre approche de la gestion de l鈥檈xp茅rience utilisateur vous aide 脿 r茅duire vos co没ts, 脿 am茅liorer votre productivit茅 et 脿 mieux satisfaire vos clients.

La surveillance consiste 脿 collecter et 脿 analyser les donn茅es relatives au r茅seau, aux applications, 脿 l鈥檌nfrastructure et 脿 l鈥檈xp茅rience utilisateur afin de d茅tecter des probl猫mes ou des anomalies. La surveillance implique g茅n茅ralement la mise en place de seuils d鈥檃lerte pour avertir les op茅rateurs ou les d茅veloppeurs en cas de probl猫me. L鈥檕bjectif de la surveillance est de fournir des informations sur la disponibilit茅, les performances et l鈥檜tilisation.

L鈥檕bservabilit茅 pousse la surveillance un peu plus loin en soulignant l鈥檌mportance de comprendre le fonctionnement interne d鈥檜n syst猫me, au lieu de se contenter de contr么ler ses entr茅es et sorties. L鈥檕bservabilit茅 implique la collecte et l鈥檃nalyse de donn茅es 脿 un niveau plus approfondi et n茅cessite des donn茅es haute fid茅lit茅 multi-domaines afin d鈥檕btenir une vision globale du comportement du syst猫me. L鈥檕bjectif de l鈥檕bservabilit茅 est de permettre une d茅tection et une r茅solution proactives des probl猫mes, plut么t qu鈥檜ne simple r茅solution r茅active.

En bref, l鈥檕bservabilit茅 et la surveillance repr茅sentent deux faces d鈥檜ne m锚me pi猫ce. La surveillance fournit un niveau de visibilit茅 de base sur le syst猫me, tandis que la visibilit茅 vise 脿 d茅gager une vue plus compl猫te des performances. L鈥檕bservabilit茅 va encore plus loin en soulignant la n茅cessit茅 de comprendre le fonctionnement interne d鈥檜n syst猫me afin d鈥檈n am茅liorer les performances et la fiabilit茅 globales.

Qu鈥檈st-ce que l鈥檕bservabilit茅听?

L鈥檕bservabilit茅 est un concept utilis茅 dans divers domaines, notamment l鈥檌ng茅nierie, l鈥檌nformatique et l鈥檃nalyse des syst猫mes. Il s鈥檃git de la capacit茅 脿 comprendre et 脿 analyser le fonctionnement interne d鈥檜n syst猫me ou d鈥檜n processus sur la base des donn茅es et des informations qu鈥檌l produit. Il correspond essentiellement 脿 la mesure dans laquelle nous pouvons observer et mesurer ce qui se passe dans un syst猫me.

En informatique, l鈥檕bservabilit茅 est souvent associ茅e au d茅veloppement de logiciels et d鈥檃pplications. Il s鈥檃git de la capacit茅 脿 surveiller et 脿 d茅boguer des syst猫mes logiciels complexes en collectant et en analysant des donn茅es provenant de diverses sources, telles que les journaux d鈥檃pplication, les metrics et les traces. Ce faisant, les d茅veloppeurs peuvent identifier et r茅soudre les probl猫mes au sein du logiciel et am茅liorer sa qualit茅 et ses performances globales.

L鈥檕bservabilit茅 unifi茅e 麻豆学生精品版 de 麻豆学生精品版 茅tend le concept d鈥檕bservabilit茅 脿 tous les syst猫mes IT, y compris le r茅seau, l鈥檌nfrastructure, les applications et l鈥檈xp茅rience utilisateur. Elle s鈥檃ppuie sur des donn茅es, des analyses et des corr茅lations haute fid茅lit茅, ainsi que sur l鈥檃utomatisation intelligente pour recueillir les donn茅es contextuelles qui permettent d鈥檌dentifier et de r茅soudre rapidement les probl猫mes de performance et de s茅curit茅.

Globalement, l鈥檕bservabilit茅 est un concept crucial qui nous permet de mieux comprendre le fonctionnement interne des syst猫mes et processus complexes, ce qui peut nous aider 脿 am茅liorer leurs performances, leur fiabilit茅 et leur efficacit茅 globale.

Qu鈥檈st-ce que la surveillance听?

La surveillance des performances est le processus de suivi et d鈥檃nalyse des metrics de performance d鈥檜n syst猫me ou d鈥檜n processus, tel qu鈥檜n syst猫me informatique, un r茅seau ou une application, afin de s鈥檃ssurer qu鈥檌l respecte les niveaux de performance requis ou les accords de niveaux de service (SLA). Il s鈥檃git de surveiller divers metrics, comme le temps de r茅ponse, le d茅bit et les taux d鈥檈rreur, et de les comparer 脿 des valeurs de r茅f茅rence ou 脿 des seuils pr茅d茅termin茅s.

L鈥檕bjectif de la surveillance des performances est d鈥檌dentifier et de diagnostiquer les probl猫mes de performances, tels que des temps de r茅ponse lents, une utilisation 茅lev茅e des ressources ou des pannes syst猫me, et de prendre les mesures appropri茅es pour les r茅soudre. Il peut s鈥檃gir d鈥檃juster les configurations syst猫me, de mettre 脿 niveau les composants mat茅riels ou logiciels, ou d鈥檕ptimiser le code ou les algorithmes.

La surveillance des performances est essentielle pour garantir le bon fonctionnement des syst猫mes et des processus, ainsi que pour assurer la satisfaction des clients et maintenir la continuit茅 de l鈥檃ctivit茅. Elle est couramment utilis茅e dans des secteurs tels que l鈥橧T, les t茅l茅communications, la finance, les soins de sant茅 et la fabrication pour superviser et optimiser les performances des syst猫mes et applications strat茅giques.

Observabilit茅 et surveillance听: quelle est la diff茅rence听?

L鈥檕bservabilit茅 et la surveillance sont deux concepts importants dans les op茅rations IT, mais ils ont des significations l茅g猫rement diff茅rentes.

La surveillance fait g茅n茅ralement r茅f茅rence au processus de collecte de donn茅es sur un syst猫me, telles que ses performances, sa disponibilit茅 et son utilisation, et 脿 l鈥檜tilisation de ces donn茅es pour identifier et diagnostiquer les probl猫mes ou pour optimiser les performances. La surveillance s鈥檈ffectue g茅n茅ralement 脿 l鈥檃ide d鈥檜ne t茅l茅m茅trie sp茅cialis茅e qui collecte et analyse des donn茅es provenant de diverses sources, telles que le r茅seau ou les applications.

L鈥檕bservabilit茅, quant 脿 elle, est un concept plus global qui renvoie 脿 la capacit茅 de comprendre et de d茅cortiquer le comportement et les performances d鈥檜n syst猫me 脿 partir des donn茅es qu鈥檌l produit. Un syst猫me observable est un syst猫me qui fournit suffisamment d鈥檌nformations pour permettre au service IT de comprendre son comportement et de diagnostiquer plus facilement les probl猫mes. Il poss猫de g茅n茅ralement une interface bien d茅finie qui permet au service IT de collecter et d鈥檃nalyser des donn茅es sur son comportement.

En r茅sum茅, la surveillance est un sous-ensemble de l鈥檕bservabilit茅, la surveillance 茅tant un moyen de collecter des donn茅es sur un syst猫me, tandis que l鈥檕bservabilit茅 est la capacit茅 de d茅cortiquer ce syst猫me 脿 partir de ses sorties de donn茅es.

Quels sont les b茅n茅fices de l鈥檕bservabilit茅听?

L鈥檕bservabilit茅 pr茅sente plusieurs b茅n茅fices, notamment听:

1. D茅tection plus rapide des probl猫mes听: Gr芒ce 脿 l鈥檕bservabilit茅, il devient plus facile de d茅tecter les probl猫mes au fur et 脿 mesure qu鈥檌ls se produisent, plut么t que d鈥檃ttendre les plaintes des utilisateurs ou les d茅faillances. Cela permet de r茅duire les interruptions et d鈥檃m茅liorer la fiabilit茅 globale.
2. R茅solution plus rapide des probl猫mes听: Lorsqu鈥檜n probl猫me est d茅tect茅, les outils d鈥檕bservabilit茅 peuvent aider 脿 identifier l鈥檕rigine du probl猫me. L鈥檕bservabilit茅 unifi茅e 麻豆学生精品版 utilise une automatisation intelligente pour rassembler les preuves et le contexte. Cela permet de r茅duire le temps n茅cessaire 脿 la r茅solution du probl猫me et 脿 la remise en service du syst猫me.
3. Performances sup茅rieures听: En surveillant les mesures et les indicateurs cl茅s, l鈥檕bservabilit茅 peut aider 脿 identifier les domaines de performance qui ne sont pas optimaux. Cela permet d鈥檃m茅liorer les performances des r茅seaux, des applications et de l鈥檈xp茅rience utilisateur, et de pr茅venir les probl猫mes potentiels avant qu鈥檌ls ne surviennent.
4. Am茅lioration de la collaboration听: Les outils d鈥檕bservabilit茅 peuvent fournir une visibilit茅 sur l鈥櫭﹖at interne d鈥檜n syst猫me 脿 plusieurs 茅quipes au sein d鈥檜ne organisation. Ils contribuent 脿 am茅liorer la collaboration entre les 茅quipes et aident tout un chacun 脿 艙uvrer vers un objectif commun d鈥檃m茅lioration des performances et de la fiabilit茅.
5. Meilleure exp茅rience pour les clients听: En d茅tectant et en r茅solvant les probl猫mes plus rapidement, l鈥檕bservabilit茅 peut contribuer 脿 am茅liorer l鈥檈xp茅rience digitale des utilisateurs, ce qui se traduit par une satisfaction et une fid茅lit茅 accrues des clients.

Qu鈥檈st-ce que l鈥檕bservabilit茅 unifi茅e 麻豆学生精品版 ?

麻豆学生精品版 IQ, service d鈥檕bservabilit茅 unifi茅e fourni par SaaS, fait ressortir les probl猫mes ayant le plus d鈥檌mpact avec leur contexte afin de les r茅soudre rapidement. Il s鈥檃ppuie sur les mesures cl茅s d鈥檜ne gamme compl猫te de t茅l茅m茅trie de surveillance (du r茅seau, de l鈥檌nfrastructure, des applications et des utilisateurs finaux) pour fournir les bases d鈥檜ne observabilit茅 unifi茅e. Il applique une multitude d鈥檃nalyses et de corr茅lations en cinq dimensions afin de regrouper les indicateurs connexes en un seul incident, menant 脿 des alertes plus pr茅cises et une identification plus rapide des probl猫mes. Il utilise ensuite l鈥檃utomatisation intelligente qui reproduit les bonnes pratiques des experts IT afin de recueillir des preuves, 茅tablir un contexte et d茅finir des priorit茅s. Le service IT peut ainsi r茅soudre les probl猫mes plus rapidement et plus efficacement.

Pour plus d鈥檌nformations sur l鈥檕bservabilit茅 unifi茅e 麻豆学生精品版 et la surveillance, cliquez ici.