Operations | Monitoring | ITSM | DevOps | Cloud

Debugging errors in distributed systems can be a challenging task, as it involves tracing the flow of operations across numerous microservices. This complexity often leads to difficulties in pinpointing the root cause of performance issues or errors. OpenTelemetry provides instrumentation libraries in most programming languages for tracing.

In my previous post I made a bold, sweeping statement that APM is not - in the most specific sense - a subset of observability. Still standing by it I stand by that because words matter and - like many "monitoring engineers" (IT folks who make monitoring and observability their specialty) - I, too, bear scars from the flame-wars on Twitter back in the 2020's where we fought internecine battles over the proper definition of (and number of pillars in) “observability”.

For every SaaS leader, engineer, and operations professional, growth is always the main goal. You’re expected to release features quickly, keep user experiences smooth, and manage everything within a limited budget. But behind the scenes, your application may have hidden issues such as slow performance, unnoticed errors, and laggy transactions that quietly eat away at revenue, reduce customer trust, and exhaust your engineering team.

In 2022, we had three different query interfaces. Logs had a custom search syntax with no autocomplete. Traces only had predefined filters - no query builder at all. Metrics had a raw PromQL input box where you'd paste queries from somewhere else and hope they worked. Each system spoke a different language. An engineer debugging a production issue had to context-switch not just between data types, but between entirely different mental models of how to query data.

As organizations modernize, most applications don’t fit neatly into one category—they span both traditional three-tier architectures and cloud-native microservices. To monitor these hybrid environments effectively, teams need APM tools that can seamlessly connect the two worlds.

For years, organizations have relied on Application Performance Monitoring (APM) as the backbone of their observability strategy. The idea was simple: collect as many logs, metrics, and traces as possible, then sift through the data to uncover insights. But as applications have shifted to the cloud and become increasingly API-driven, that model has broken down.

Your dashboard shows a latency spike. To investigate it, you copy the query, open logs in a new tab, paste and modify the query, lose your dashboard filters, and repeat for traces. By the time you find the issue, you have 15 tabs open. Starting today, you can click any panel and investigate right there. All your filters and variables carry over. No more tab juggling.