Question 1

How to integrate Riemann JVM Profiler with a Spring Boot application?

Accepted Answer

You can add it as a Java agent using the -javaagent flag in the JVM options, similar to the examples in the README, or include it as a library dependency and call start-global! in your initialization code, though Spring-specific configuration isn't detailed.

Question 2

What is the performance overhead of using Riemann JVM Profiler?

Accepted Answer

Overhead is controlled by the :load parameter, targeting a fraction of a core, typically resulting in 10-100 samples per second. However, it adds CPU usage and may impact latency-sensitive applications if not tuned carefully.

Question 3

Can Riemann JVM Profiler be used for memory leak detection?

Accepted Answer

No, it focuses on CPU profiling via stack sampling and does not track memory allocations or garbage collection events. For memory analysis, tools like Java Flight Recorder or VisualVM are more appropriate.

Question 4

Riemann JVM Profiler vs Java Flight Recorder for CPU analysis?

Accepted Answer

Riemann JVM Profiler is better for distributed, real-time aggregation into Riemann, while JFR is more comprehensive for single JVM profiling with lower overhead and built-in JDK integration. Choose based on your monitoring stack and scale needs.

Question 5

How to interpret the metrics sent to Riemann by the profiler?

Accepted Answer

Metrics represent CPU time in seconds/second per function, aggregated across hosts. Use Riemann streams to sum and rank functions, as shown in the README example, to identify top hotspots in your distributed system.

Question 6

Is Riemann JVM Profiler suitable for production environments?

Accepted Answer

Yes, with careful tuning of the :load parameter to minimize overhead, but it requires a stable Riemann server and may introduce deployment complexity in clustered setups, as noted in the Hadoop integration section.

Riemann JVM Profiler

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