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feat: expose worker Prometheus metrics for matching and eval ingest #1184
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c4b8b1e
feat: collect performance metrics for garbage collection
DarshanCode2005 316a4c7
feat: collect performace metrics for CVE delta ingest
DarshanCode2005 0a31b91
feat: add Grafana panels for GC and CVE delta metrics
DarshanCode2005 a25baf1
fix: make delta and GC metrics files readable by node_exporter
DarshanCode2005 394afb4
fix: include node_exporter in Grafana Instance variable
DarshanCode2005 b2efc10
feat: add worker Prometheus metrics helpers and HTTP server
DarshanCode2005 b1fa9c2
feat: observe matching duration and candidates
DarshanCode2005 8b10ed9
feat: observe eval batch ingest duration and size
DarshanCode2005 93391b3
feat: wire worker and evaluator metrics endpoints in nix
DarshanCode2005 95f3b81
feat: add Grafana panels for matching and eval ingest metrics
DarshanCode2005 b650c24
style: format worker metrics test for ruff
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My hunch is this could be an ad hoc more-or-less-inline Python HTTP server here, which we put behind the proxy. Seems kind of wrong to weave this into the application code.
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we need the sidecar because evaluator workers use multiprocess mode: each process must serve
MultiProcessCollector. Putting that inwst-managekeeps Django settings/METRICS_HTTP_PORTthe same as the worker path. An inline Python one-lineer in nix is possible, but it would still need the sameprometheus_client+ multiproc wiring, and would drift from how the worker exposes metrics. Happy to extract a thinner entrypoint if you want it out of Django management commands , but "serve aggregated multiproc metrics" still has to live somewhere next to the app that writes those files.