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Understanding Request Latency with Profiling | Richard Startin’s Blog
It can be hard to figure out why response times are high in Java applications. In my experience, people either apply a process of elimination to a set of recent commits, or might sometimes use profiles of the system to explain changes in metrics. Making guesses about recent commits can be frustrating for a number of reasons, but mostly because even if you pinpoint the causal change, you still might not know why it was a bad change and are left in limbo. In theory, using a profiler makes root cause analysis a part of the triage process, so adopting continuous profiling should make this whole process easier, but using profilers can be frustrating because you’re using the wrong type of profile for analysis. Lots of
Understanding Request Latency with Profiling | Richard Startin’s Blog
It can be hard to figure out why response times are high in Java applications. In my experience, people either apply a process of elimination to a set of recent commits, or might sometimes use profiles of the system to explain changes in metrics. Making guesses about recent commits can be frustrating for a number of reasons, but mostly because even if you pinpoint the causal change, you still might not know why it was a bad change and are left in limbo. In theory, using a profiler makes root cause analysis a part of the triage process, so adopting continuous profiling should make this whole process easier, but using profilers can be frustrating because you’re using the wrong type of profile for analysis. Lots of
https://richardstartin.github.io/posts/wallclock-profiler
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