Debugging a consistently failing unit test is easy; you set a breakpoint and you fix it. But how do you debug a "random" failure in a massive microservices landscape or a distributed monolith?
How do you catch a ghost in the system?

During an interview, I was once told, "You are more of a debugger than a coder." I think the interviewer was right. I thrive on the bugs that make others give up: the nasty, intermittent issues hidden under the carpet.
But you cannot solve these issues with `System.out.println()` or a simple debugger attached to localhost.
Debugging at scale requires a shift in both mindset and tooling. It requires moving from the paradigm of "5 Whys" and `logger.info` to a structured observational approach.

How do you debug issues at the scale of a vast landscape of services, whether it consists of cloud-native services, (legacy) applications, or monoliths?
Based on real-life examples, I'll share how I uncovered the problems, the lessons I learned, and how you can use observability tooling like OpenTelemetry and the Grafana toolset to gain deeper insights.

Join this session to learn how to apply a debugging mindset at scale.