Traffic Metrics

Kuma facilitates consistent traffic metrics across all dataplanes in your mesh.

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

On Universal

Enable Prometheus metrics per Mesh

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

  1. type: Mesh
  2. name: default
  3. metrics:
  4.   prometheus: {}

which is a convenient shortcut for

  1. type: Mesh
  2. name: default
  3. metrics:
  4.   prometheus:
  5.     port: 5670
  6.     path: /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 on a particular machine, configure Dataplane resource as follows:

  1. type: Dataplane
  2. mesh: default
  3. name: example
  4. metrics:
  5.   prometheus:
  6.     port: 1234
  7.     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 dataplane discovery by Prometheus

Although dataplane metrics are now exposed, Prometheus doesn’t know anything about it just yet.

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 where Kuma Control Plane is, how to talk to it and how to 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.

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

  1. kuma-prometheus-sd run \
  2.   --cp-address=http://kuma-control-plane.internal:5681 \
  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 http://kuma-control-plane.internal:5681Traffic Metrics - 图1 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

  1. prometheus --config.file=prometheus.yml

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

On Kubernetes

Enable Prometheus metrics per Mesh

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

  1. apiVersion: kuma.io/v1alpha1
  2. kind: Mesh
  3. metadata:
  4.   name: default
  5. spec:
  6.   metrics:
  7.     prometheus: {}

which is a convenient shortcut for

  1. apiVersion: kuma.io/v1alpha1
  2. kind: Mesh
  3. metadata:
  4.   name: default
  5. spec:
  6.   metrics:
  7.     prometheus:
  8.       port: 5670
  9.       path: /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 Mesh-wide default path

E.g.,

  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.metrics.kuma.io/port: "1234"               # override Mesh-wide default port
  13.         prometheus.metrics.kuma.io/path: "/non-standard-path" # override Mesh-wide default path
  14.     spec:
  15.       containers:
  16.       ...

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.

Configure dataplane discovery by Prometheus

To configure dataplane discovery by Prometheus you have to deploy kuma-prometheus-sd container next to you Prometheus instance just like in Universal setup.

First, add a volume to your Prometheus deployment to which kuma-prometheus-sd will write a file with the list of the dataplanes and from which Prometheus will read the list.

  1. volumes:
  2. - name: kuma-prometheus-sd-volume
  3.   emptyDir: {}

Then add a new container with kuma-prometheus-sd. It will connect to the control plane at given address and produce file to /var/run/kuma.io/prometheus-sd/kuma.file_sd.json in created volume.

  1.   containers:
  2. - name: kuma-prometheus-sd
  3.   image: kong-docker-kuma-docker.bintray.io/kuma-prometheus-sd:0.4.0
  4.   imagePullPolicy: Always
  5.   args:
  6.     - run
  7.     - --name=kuma-prometheus-sd
  8.     - --cp-address=http://kuma-control-plane.kuma-system:5681
  9.     - --output-file=/var/run/kuma.io/prometheus-sd/kuma.file_sd.json
  10.   volumeMounts:
  11.     - mountPath: "/var/run/kuma.io/prometheus-sd"
  12.       name: kuma-prometheus-sd-volume

Next step is to mount the volume to the Prometheus container

  1. volumeMounts:
  2. - mountPath: "/var/run/kuma.io/prometheus-sd"
  3.   name: kuma-prometheus-sd-volume

Finally, modify your Prometheus config to use generated file

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

Refer to full example of the deployment and the configuration.

If you are starting from scratch, consider using kumactl install metrics | kubectl apply -f - to deploy configured Prometheus with Grafana.

Grafana Dashboards

Kuma ships with 3 default dashboards that are available to import from Grafana Labs repositoryTraffic Metrics - 图3.

Kuma Dataplane

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

Kuma Dataplane dashboard Kuma Dataplane dashboard Kuma Dataplane dashboard

Kuma Mesh

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

Kuma Mesh dashboard

Kuma Service to Service

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

Kuma Service to Service dashboard