Operations | Monitoring | ITSM | DevOps | Cloud

Your users are complaining about slow application performance. Your monitoring dashboard shows all devices are green, routers operational, switches functioning, and bandwidth utilization is normal. Yet something is clearly wrong. The problem isn't your equipment; it's the path between your users and their destinations. This is where network path monitoring comes in.

What approaches exist, and how to use automation to benefit the overall business processes.

Across the IT and observability landscape, enterprise leaders are facing a troubling pattern. A trusted vendor announces a “modernization initiative,” often following a major acquisition or a shift in ownership. Overnight, pricing structures change, license models disappear, and long-time customers are pressured into multi-year bundles under the banner of innovation. What’s being framed as progress often feels more like pressure.

Testing ecosystems contain massive amounts of data, including outlined test scenarios, prerequisite configurations, and the tests themselves. As a result, these ecosystems are prone to data sprawl. This makes it difficult to prevent configuration drift and quickly spin up new tests, especially at the frequency needed to support a fast-growing application. Teams can handle these challenges by treating their tests as part of their application infrastructure.

As AI workloads and cloud-native applications expand, organizations are generating more log data than ever. Each service, container, and model inference produces continuous telemetry that must be stored, secured, and analyzed. As telemetry grows more complex, teams must balance full visibility with new retention and residency needs.