Traffic Metrics

A user can enable traffic metrics by editing a Mesh resource and providing the desired Mesh-wide configuration. If necessary, metrics configuration can be customized for each Dataplane individually, e.g. to override the default metrics port that might be already in use on that particular machine.

Out-of-the-box, Kuma provides full integration with Prometheus:

  • if enabled, every dataplane will expose its metrics in Prometheus format
  • furthemore, Kuma will make sure that Prometheus can automatically find every dataplane in the mesh

To collect metrics from Kuma, you need to first expose metrics from Dataplanes and then configure Prometheus to collect them.

To expose Prometheus metrics from every dataplane in the mesh, configure a Mesh resource as follows:

which is a convenient shortcut for

  1. apiVersion: kuma.io/v1alpha1
  2. kind: Mesh
  3. metadata:
  4.   name: default
  5. spec:
  6.   metrics:
  7.     enabledBackend: prometheus-1
  8.     backends:
  9.     - name: prometheus-1
  10.       type: prometheus
  11.       conf:
  12.         skipMTLS: false
  13.         port: 5670
  14.         path: /metrics
  15.         tags: # tags that can be referred in Traffic Permission when metrics are secured by mTLS  
  16.           kuma.io/service: dataplane-metrics
  1. type: Mesh
  2. name: default
  3. metrics:
  4.   enabledBackend: prometheus-1
  5.   backends:
  6.   - name: prometheus-1
  7.     type: prometheus
  8.     conf:
  9.       skipMTLS: true # by default mTLS metrics are also protected by mTLS. Scraping metrics with mTLS without transparent proxy is not supported at the moment.

which is a convenient shortcut for

  1. type: Mesh
  2. name: default
  3. metrics:
  4.   enabledBackend: prometheus-1
  5.   backends:
  6.   - name: prometheus-1
  7.     type: prometheus
  8.     conf:
  9.       skipMTLS: true
  10.       path: /metrics
  11.       tags: # tags that can be referred in Traffic Permission when metrics are secured by mTLS  
  12.         kuma.io/service: dataplane-metrics

Both snippets from above instruct Kuma to configure every dataplane in the mesh default to expose an HTTP endpoint with Prometheus metrics on port 5670 and URI path /metrics.

Override Prometheus settings per Dataplane

To override Mesh-wide defaults for a particular Pod, use Kuma-specific annotations:

  • prometheus.metrics.kuma.io/port - to override Mesh-wide default port
  • prometheus.metrics.kuma.io/path - to override -wide default path

E.g.,

As a result, dataplane for this particular Pod will expose an HTTP endpoint with Prometheus metrics on port 1234 and URI path /non-standard-path.

To override Mesh-wide defaults on a particular machine, configure Dataplane resource as follows:

  1. type: Dataplane
  2. mesh: default
  3. name: example
  4. metrics:
  5.   type: prometheus
  6.   conf:
  7.     skipMTLS: true
  8.     port: 1234
  9.     path: /non-standard-path

As a result, this particular dataplane will expose an HTTP endpoint with Prometheus metrics on port 1234 and URI path /non-standard-path.

Configure Prometheus

To help Prometheus to automatically discover dataplanes, Kuma provides a tool - kuma-prometheus-sd. kuma-prometheus-sd is meant to run alongside Prometheus instance. It knows location of Kuma Control Plane is and can fetch an up-to-date list of dataplanes from it. It then transforms that information into a format that Prometheus can understand, and saves it into a file on disk. Prometheus watches for changes to that file and updates its scraping configuration accordingly.

Use kumactl install metrics | kubectl apply -f - to deploy configured Prometheus with Grafana.

If you’ve got Prometheus deployment already, you can use to bring Kuma metrics to your main Prometheus cluster.

First, you need to run kuma-prometheus-sd, e.g. by using the following command:

  1. kuma-prometheus-sd run \
  2.   --cp-address=grpcs://kuma-control-plane.internal:5676 \
  3.   --output-file=/var/run/kuma-prometheus-sd/kuma.file_sd.json

The above configuration tells kuma-prometheus-sd to talk to Kuma Control Plane at grpcs://kuma-control-plane.internal:5676 and save the list of dataplanes to /var/run/kuma-prometheus-sd/kuma.file_sd.json.

Then, you need to set up Prometheus to read from that file, e.g. by using prometheus.yml config with the following contents:

  1. scrape_configs:
  2. - job_name: 'kuma-dataplanes'
  3.   scrape_interval: 15s
  4.   file_sd_configs:
  5.   - files:
  6.     - /var/run/kuma-prometheus-sd/kuma.file_sd.json

and running

Now, if you check Targets page on Prometheus UI, you should see a list of dataplanes from your mesh, e.g.

A screenshot of Targets page on Prometheus UI

Kuma lets you expose Dataplane metrics in a secure way by leveraging mTLS. Prometheus needs to be a part of the Mesh for this feature to work, which is the default deployment model when kumactl install metrics is used on Kubernetes.

Make sure that mTLS is enabled in the Mesh.

  1. apiVersion: kuma.io/v1alpha1
  2. kind: Mesh
  3. metadata:
  4.   name: default
  5. spec:
  6.   mtls:
  7.     enabledBackend: ca-1
  8.     backends:
  9.     - name: ca-1
  10.       type: builtin
  11.   metrics:
  12.     enabledBackend: prometheus-1
  13.     backends:
  15.       type: prometheus
  16.       conf:
  17.         port: 5670
  18.         path: /metrics
  19.         skipMTLS: false
  20.         tags: # tags that can be referred in Traffic Permission  
  21.           kuma.io/service: dataplane-metrics

Allow the traffic from Grafana to Prometheus Server and from Prometheus Server to Dataplane metrics and for other Prometheus components:

  1. apiVersion: kuma.io/v1alpha1
  2. kind: TrafficPermission
  3. metadata:
  4.   name: metrics-permissions
  5. spec:
  6.   sources:
  7.     - match:
  8.        kuma.io/service: prometheus-server_kuma-metrics_svc_80
  9.   destinations:
  10.     - match:
  11.        kuma.io/service: dataplane-metrics
  12.     - match:
  13.        kuma.io/service: "prometheus-alertmanager_kuma-metrics_svc_80"
  14.     - match:
  15.        kuma.io/service: "prometheus-kube-state-metrics_kuma-metrics_svc_80"
  16.     - match:
  17.        kuma.io/service: "prometheus-kube-state-metrics_kuma-metrics_svc_81"
  18.     - match:
  19.        kuma.io/service: "prometheus-pushgateway_kuma-metrics_svc_9091"
  20. ---
  21. apiVersion: kuma.io/v1alpha1
  22. kind: TrafficPermission
  23. mesh: default
  24. metadata:
  25.   name: grafana-to-prometheus
  26. spec:
  27.    sources:
  28.    - match:
  29.       kuma.io/service: "grafana_kuma-metrics_svc_80"
  30.    destinations:
  31.    - match:
  32.       kuma.io/service: "prometheus-server_kuma-metrics_svc_80"

In addition to exposing metrics from Dataplane, you may want to expose metrics from application next to Kuma DP.

Use standard prometheus.io annotations either on Pod or Service

  1. apiVersion: apps/v1
  2. kind: Deployment
  3. metadata:
  4.   namespace: kuma-example
  5.   name: kuma-tcp-echo
  6. spec:
  7.   ...
  8.   template:
  9.     metadata:
  10.       ...
  11.       annotations:
  12.         prometheus.io/scrape: "true"
  13.         prometheus.io/port: "1234"
  14.         prometheus.io/path: "/non-standard-path"
  15.     spec:
  16.       containers:

Use Discovery Service of . In the future Kuma will help to expose metrics in more native way.

Remember that in order to consume paths protected by mTLS, you need Traffic Permission that lets Prometheus consume applications.

Kuma ships with 4 default dashboards that are available to import from Grafana Labs repositoryTraffic Metrics - 图4 (opens new window).

This dashboards lets you investigate the status of a single dataplane in the mesh.

Kuma Dataplane dashboard

Kuma Mesh

This dashboard lets you investigate the aggregated statistics of a single mesh.

Kuma Mesh dashboard

This dashboard lets you investigate aggregated statistics from dataplanes of given source service to dataplanes of given destination service.

Kuma CP

This dashboard lets you investigate statistics of the control plane.