integrations/jetstream/documentation.yaml (39 lines of code) (raw):

exporter_type: included app_name_short: JetStream app_name: {{app_name_short}} app_site_name: {{app_name_short}} app_site_url: https://github.com/AI-Hypercomputer/JetStream exporter_name: {{app_name_short}} exporter_repo_url: https://github.com/AI-Hypercomputer/JetStream/blob/main/docs/observability-prometheus-metrics-in-jetstream-server.md gke_setup_url: /kubernetes-engine/docs/tutorials/serve-llm-tpu-jetstream-pytorch additional_prereq_info: | To collect Prometheus-format metrics from {{app_name_short}}, you must first [build and upload a {{app_name_short}} PyTorch server image](https://github.com/AI-Hypercomputer/jetstream-pytorch/tree/main/docker/jetstream-pytorch-server). additional_install_info: | To verify that {{exporter_name}} is emitting metrics on the expected endpoints, do the following: 1. Set up port forwarding by using the following command: <pre class="devsite-click-to-copy"> kubectl -n {{namespace_name}} port-forward {{pod_name}} 9090 </pre> 2. Access the endpoint `localhost:9090/metrics` by using the browser or the `curl` utility in another terminal session. podmonitoring_config: | apiVersion: monitoring.googleapis.com/v1 kind: PodMonitoring metadata: name: jetstream labels: app.kubernetes.io/name: jetstream app.kubernetes.io/part-of: google-cloud-managed-prometheus spec: endpoints: - port: 9090 scheme: http interval: 30s path: /metrics selector: matchLabels: app: jetstream-pytorch-server sample_promql_query: up{job="jetstream", cluster="{{cluster_name}}", namespace="{{namespace_name}}"} dashboard_available: true multiple_dashboards: false dashboard_display_name: {{app_name}} Prometheus Overview