breedx-splk / iguanodon Goto Github PK

Use-Case
We used iguanodon tests, to see the overhead by Open telemetry agent (latest-1.0) on the spring pet clinic app with k6 load. We increased number of users from 5 to 500. (All requests successful). We tabulated the results as shown in image. It is observed that app instrumented with OTEL agent has ~20% more memory footprint as looked from the JFR used heap memory metrics.

Question to the community
Is this behaviour expected ? What are the results you are getting ?

Instead of one giant workflow, once things are mostly stable it would be nice to have the container builds in their own workflow that maybe runs only when stuff changes or nightly or something so that the runs themselves are faster.

The output json files are rather large. The data should be aggregated.

start at like 6 or 12 hours to start?

Get the splunk-specific stuff out of the docker command described in the readme.