IT Teams Can Turn Insights into Action with Unified Observability Technology

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Read more about author Mike Marks.

Today IT teams are woefully understaffed and overwhelmed with dozens of pressing daily demands from across their organizations. They are under pressure to drive the performance, accessibility, and security of IT systems, services, and applications at a time when the uptick in remote work has made it even more challenging to support those areas.  

Their jobs have become more layered and complex as they must manage a highly distributed infrastructure that comprises on-premise systems and public, private, and hybrid clouds. Working with a mix of self-hosted and managed applications, as-a-service apps, and serverless cloud-native applications makes troubleshooting issues across multiple locations and home networks even more cumbersome than ever.  


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At the same time, IT teams are being asked to secure the attack surface when their organizations are juggling even more data than ever. This is data that is siloed across enterprise infrastructures, existing without proper context and yielding little to no actionable insights. This has created an overload of alerts that overburden IT, and security teams must prioritize the most pressing ones that need immediate responses.  

Existing monitoring tools cannot help them, as providing more visibility and alerts without context into the infrastructure does not solve the problem. Organizations desperately need to turn data into actionable insights that enable them to act fast, and these tools cannot support that critical function. 

Overwhelmed IT teams require a new approach to solve these challenges: Enter unified observability.  

While monitoring tools deliver end-to-end transparency into the customer and employee journeys, they only work according to preset metrics and thresholds. Simply put, they only work when the user knows what they are looking for. Most organizations don’t know where to mine the real data gems that will provide the insight “gold” they need for actionable results. That’s why observability tools are so important. They take the next step by incorporating artificial intelligence (AI) and automation to deliver results and enable teams to understand the collected data, leverage it to prioritize initiatives, and prevent IT problems from happening in the first place.

Observability tools go above and beyond by letting users measure the internal states of a system by examining its outputs. They let IT teams have insight into the unknown by correlating information across the enterprise and putting it into the most appropriate and relevant context.  This helps IT teams not only find the reasons behind problems or unexpected issues on IT systems but also act on them and fix issues in real time, often through automated responses.  

This type of unified observability has become increasingly important as more organizations support remote work, and IT teams must work harder to support a hybrid, highly distributed dynamic environment. Therefore, IT teams must look for next-generation tools that support higher levels of monitoring and visibility as these infrastructures become more complex.

Most traditional tools are designed to address specific areas such as DevOps or cloud-native use case issues. While they are effective, they provide only limited data, thereby yielding context-free alerts that require time-consuming manual investigation from already overburdened IT teams. That’s where unified observability tools play a vital role: They provide busy IT professionals a complete picture of the environment and the context required to derive actionable insights without asking them to investigate events that prove to be inconsequential. 

In essence, unified observability tools provide a single source of truth for beleaguered IT teams, helping them capture every transaction, packet, and flow across the enterprise, rather than looking at only the sample data. These tools capture the user experience for all web and mobile applications and leverage automated AI and machine learning (ML) to view full-fidelity data, giving teams a 360-degree view of what’s happening across the enterprise. This gives teams the immediate context required to help them prioritize actions and work more efficiently.  Furthermore, these tools ensure that all IT teams work with the same data, delivering a single source of trust that enables cross-domain coordination and collaboration.

IT teams report that unified observability tools deliver four potent benefits that improve organizational performance:  

  • The tools deliver seamless business continuity by gathering full-fidelity data from a complete range of sources including devices, networks, servers, applications, and cloud-native environments, as well as data from users and third parties. This delivers filtered and prioritized insights that allow IT teams to provide vastly improved digital service quality that boosts customer service and employee performance.
  • They also boost agility and performance because the automated prioritization of insights drawn from the data is invaluable to IT teams. The automation reduces alert fatigue while prioritizing issues that must be addressed first.  
  • IT teams also benefit from key efficiencies such as improved service availability and reduced IT costs. These tools reduce the time and effort it takes to discover root causes and accelerate or automate remediation.
  • Lastly, these tools eliminate data silos and create a single source of truth that enables IT teams to work more seamlessly together. A unified approach empowers cross-domain collaboration and reduces misunderstandings.  

In the face of a looming recession and inflation, IT teams are more challenged than ever to deliver more support to an increasingly distributed workforce. Moreover, other issues, including the reliance on SaaS and the persistent use of shadow IT, demand that IT teams have one clear enterprise-wide view of IT performance. At this critical time, they need unified observability tools to produce full-fidelity telemetry from the enterprise and provide AI-and ML-enabled analysis to drive automated remediation. This is the most effective way to boost enterprise IT operations, including security and overall performance. 

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