The role of observability in accelerating problem resolution

Across the IT and networking landscape of modern enterprises with dynamic infrastructures and distributed applications, just knowing how a system is running is not sufficient. Organizations need to understand why the systems are behaving in a certain way, what is causing performance degradation, and how issues can be prevented before they impact users. These requirements are contributing to the evolution of observability from “monitoring”, which merely addressed ‘known unknowns to something much more powerful.

Network glitches must be addressed before they disrupt banking systems, ground aircraft, or delay life-saving surgeries. Every second of downtime matters in our digitally hyperconnected world.

Need for Observability

According to a NETSCOUT Survey at CiscoLive 2025, with 319 IT professionals who were actively involved in problem resolution processes, 50.8% discovered performance problems when employees reported them to the IT department. By the time the problems were reported, it was already too late. The Survey also revealed that more than 80% of the time, the respondents felt that problems took several hours to a week to resolve.

Observability plays a key role in moving from reactive response to proactive control and predictive insights. This helps organizations in reducing network disruptions, driving better user experiences, achieving higher productivity, and driving increased revenues. Complex multivendor environments that lack visibility makes resolving performance degradations and outages complicated. This means long and unacceptable incident resolution times ranging few hours or worse. In the realm of solving problems, IT has long championed the concept of “mean time to resolution” (MTTR). When you further break MTTR down and examine the sub-components and elements, identifying what the problem is and having the knowledge and understanding of what needs to be fixed, where and why are critical stages that take up precious time before you can declare victory and solve the problem.

Identifying Problems Faster: Detecting issues before users notice

The initial stage of rapid incident resolution is directly connected to reducing the Mean Time to Identify (MTTI), which involves determining what went wrong. To achieve this, IT teams can leverage proactive synthetic testing and monitor user experience, 24×7. In doing so, they can detect disruptions before these issues begin to impact users and evaluate user experience for remote sites. Performance trends can be tracked continuously by implementing configurable, consistent, and transaction testing across key applications and services, even after business hours when users are not active. Any deviation identified is notified and alerted to the IT team at the earliest stages. In other words, the issue is detected even before users realize the existence of a problem.

If a VPN gateway at an organization fails at 2.00 am at a colocation (co-lo) site that enables access to corporate applications from an organization’s most profitable region, the resulting problem is going to hurt and have a negative financial and operational impact that could extend into negative business impact. However, with the implementation of automated, intelligent detection powered by synthetic business transaction testing from the remote sales offices, the IT teams would have identified the VPN unavailability issue at 2.00 am when it began. This early warning would provide the team a head start to investigate, isolate, and resolve the issue before the workday starts. This ensures uninterrupted employee productivity while delivering a stronger, more resilient digital experience.

Getting Knowledge Faster: Beyond uncovering the ‘why’ and ‘where’

Although identifying the problem and knowing the ‘what’ is important, this does not pinpoint the cause and provide the solution. What is more crucial is how fast the issue can be resolved by uncovering the ‘why’ and ‘where’ behind the disruption, where the Mean Time to Knowledge (MTTK) is significantly reduced. To get to the root cause of the problem, IT teams need to know ‘why’ and ‘where’ the disruption is occurring by leveraging real-world, data-driven insights. This high-visibility deep packet intelligence (DPI) comes from real-time monitoring of the inbound and outbound traffic across remote locations.

By enabling vendor-independent ecosystem-wide observability between remote offices and the location where applications or communications services are hosted, IT teams have the smart data and analytics they require to understand the true root cause of user-impacting degradations. Only a system-wide observability solution that offers a unified view of the entire infrastructure, including remote locations, private and public cloud, and essential connectivity, can pinpoint the problem.

Fixing and Validating Faster: Enabling proactive and preventative strategies

The final two stages of reducing the MTTR include implementing a fix and verifying that it works. The mean time to fix (MTTF) and mean time to verify (MTTV) depend largely on the nature of the issue. While stages are operationally independent, it is observability that continues to play a key role in reducing MTTR, ensuring a rapid and reliable verification process immediately after the corrective actions are implemented.

Network glitches must be addressed before they disrupt banking systems, ground aircraft, or delay life-saving surgeries. Every second of downtime matters in our digitally hyperconnected world. Organizations cannot afford blind spots across their digital ecosystems and need end-to-end observability to significantly reduce MTTR and strengthen resilience. For deeper visibility, IT teams can leverage Deep Packet Intelligence (DPI), which delivers real-time, granular insights into network behavior and pinpoints the accurate root cause. DPI empowers IT teams to shift from reactive firefighting to proactive resolution and more predictive insights that ultimately leads to preventative problem avoidance.