feat(grafana): add inference and traffic grafana templates for OGL#903
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tibo-pdn wants to merge 1 commit into
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feat(grafana): add inference and traffic grafana templates for OGL#903tibo-pdn wants to merge 1 commit into
tibo-pdn wants to merge 1 commit into
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Overview
Resolves #766 — Monitoring: add Grafana dashboard templates into the OGL repository.
This PR adds two ready-to-import Grafana dashboard templates under a new
grafana/directory, providing out-of-the-box observability for an OpenGateLLM deployment based on the metrics exposed through Prometheus:grafana/inference.json— Inference dashboard (tags:llm,inference,opengatellm). Organized into rows covering Traffic (total requests, request rate, success rate, requests by model, error rate by model & status code), Latency (request duration by model), Time To First Token (TTFT), Tokens (prompt/completion/total tokens and token rates by model) and Output Generation Speed (tokens/s, overall and by model). Includes template variables fordatasource,model,endpointandpercentileso panels can be filtered interactively.grafana/traffic.json— Traffic dashboard with HTTP-level panels: total requests, request count, average duration, percentage of 2xx / 5xx responses, P99 request duration, request rate, plus Python process resident memory and CPU usage. Includesapp_nameandDS_PROMETHEUStemplate variables.Both dashboards rely on a Prometheus datasource and are importable as-is into any Grafana instance.
DoD criteria for this PR:
Breaking changes:
Check lists
Review checklist
api/sql/models.pyhas not been modified — no Alembic migration required.Deployment checklist
No new environment variables and no special deployment steps are required. To use the dashboards, import
grafana/inference.jsonandgrafana/traffic.jsoninto Grafana and select the Prometheus datasource that scrapes OpenGateLLM metrics.Additional Notes
This change is documentation/observability-only: it adds JSON dashboard templates and does not touch any application code, database schema, configuration or runtime behavior. Reviewers may want to confirm that the panel queries match the metric names currently exposed by the OGL Prometheus exporter (request, TTFT, token and output-speed metrics) so the dashboards render correctly against a live instance.