Basic rate limit policy

Control the rate of requests to destinations within the service mesh. The following example shows you how to create a basic rate limit policy that applies to a destination, based on a generic key.

For more in-depth examples of the Envoy and Set-style rate limiting APIs, see More rate limit policy examples.

Before you begin link

1. Complete the multicluster getting started guide to set up the following testing environment.

   • Three clusters along with environment variables for the clusters and their Kubernetes contexts.
   • The Gloo meshctl CLI, along with other CLI tools such as kubectl and istioctl.
   • The Gloo management server in the management cluster, and the Gloo agents in the workload clusters.
   • Istio installed in the workload clusters.
   • A simple Gloo workspace setup.
2. Install Bookinfo and other sample apps.

3. Make sure that the rate limiting service is installed and running. If not, install the rate limiting service.

     kubectl get pods --context ${REMOTE_CONTEXT1} -A -l app=rate-limiter
     

4. To use rate limiting policies, you must create the required RateLimitServerConfig, RateLimitServerSettings, and RateLimitClientConfig resources. To create these resources you can either follow the Rate limit server setup guide, or use the example resources in step 2 of the Verify rate limit policies section.

Configure rate limit policies link

You can apply a rate limit policy at the destination level. For more information, see Applying policies.

Review the following sample configuration files. Continue to the Verify rate limit policies section for example steps on how to check that rate limiting is working.

  apiVersion: trafficcontrol.policy.gloo.solo.io/v2
kind: RateLimitPolicy
metadata:
  annotations:
    cluster.solo.io/cluster: ""
  name: rl-policy
  namespace: bookinfo
spec:
  applyToDestinations:
  - port:
      number: 9080
    selector:
      labels:
        app: reviews
  config:
    ratelimitClientConfig:
      name: rl-client-config
    ratelimitServerConfig:
      name: rl-server-config
      namespace: gloo-mesh-addons
    serverSettings:
      name: rl-server
  

Review the following table to understand this configuration.

Verify rate limit policies link

1. Make sure that the rate limit server is installed and running. If not, install the rate limiter.

     kubectl get pods --context ${REMOTE_CONTEXT1} -A -l app=rate-limiter
     

2. Create the rate limit server resources that are required to use rate limiting policies. For more information these resources, see Rate limit server setup. Note: Change cluster-1 as needed to your cluster’s actual name.

      kubectl --context ${REMOTE_CONTEXT1} apply -f - <<EOF
      apiVersion: admin.gloo.solo.io/v2
      kind: RateLimitServerConfig
      metadata:
        annotations:
          cluster.solo.io/cluster: ""
        name: rl-server-config
        namespace: gloo-mesh-addons
      spec:
        destinationServers:
        - port:
            number: 8083
          ref:
            cluster: cluster-1
            name: rate-limiter
            namespace: gloo-mesh-addons
        raw:
          descriptors:
          - key: generic_key
            rateLimit:
              requestsPerUnit: 1
              unit: DAY
            value: counter
      ---
      apiVersion: admin.gloo.solo.io/v2
      kind: RateLimitServerSettings
      metadata:
        annotations:
          cluster.solo.io/cluster: ""
        name: rl-server
        namespace: bookinfo
      spec:
        destinationServer:
          port:
            number: 8083
          ref:
            cluster: cluster-1
            name: rate-limiter
            namespace: gloo-mesh-addons
      ---
      apiVersion: trafficcontrol.policy.gloo.solo.io/v2
      kind: RateLimitClientConfig
      metadata:
        annotations:
          cluster.solo.io/cluster: ""
        name: rl-client-config
        namespace: bookinfo
      spec:
        raw:
          rateLimits:
          - actions:
            - genericKey:
                descriptorValue: counter
            limit:
              dynamicMetadata:
                metadataKey:
                  key: envoy.filters.http.ext_authz
                  path:
                  - key: opa_auth
                  - key: rateLimit
      EOF
      

3. Apply the example rate limit policy in your example setup.

      kubectl --context ${REMOTE_CONTEXT1} apply -f - <<EOF
      apiVersion: trafficcontrol.policy.gloo.solo.io/v2
      kind: RateLimitPolicy
      metadata:
        annotations:
          cluster.solo.io/cluster: ""
        name: rl-policy
        namespace: bookinfo
      spec:
        applyToDestinations:
        - port:
            number: 9080
          selector:
            labels:
              app: reviews
        config:
          ratelimitClientConfig:
            name: rl-client-config
          ratelimitServerConfig:
            name: rl-server-config
            namespace: gloo-mesh-addons
          serverSettings:
            name: rl-server
      EOF
      

4. Send a request to the reviews app from within a curl pod to test east-west rate limiting.

   Use the kubectl debug command to create an ephemeral curl container in the deployment. This way, the curl container inherits any permissions from the app that you want to test. If you don’t run Kubernetes 1.23 or later, you can deploy a separate curl pod or manually add the curl container as shown in the other tab.

     kubectl --context ${REMOTE_CONTEXT1} -n bookinfo debug -i pods/$(kubectl get pod --context ${REMOTE_CONTEXT1} -l app=reviews -A -o jsonpath='{.items[0].metadata.name}') --image=curlimages/curl -- curl -v http://reviews:9080/reviews/1
     

   If the output has an error about EphemeralContainers, see Ephemeral containers don’t work when testing Bookinfo.

   Create a temporary curl pod in the bookinfo namespace, so that you can test the app setup. You can also use this method in Kubernetes 1.23 or later, but an ephemeral container might be simpler, as shown in the other tab.

   1. Create the curl pod.

        kubectl run -it -n bookinfo --context $REMOTE_CONTEXT1 curl \
        --image=curlimages/curl:7.73.0 --rm  -- sh
        

   2. Send a request to the reviews app.

        curl http://reviews:9080/reviews/1 -v
        

      Example output:

        {"id": "1","podname": "reviews-v2-65c4dc6fdc-6xlhj","clustername": "null","reviews": [{  "reviewer": "Reviewer1",  "text": "An extremely entertaining play by Shakespeare. The slapstick humour is refreshing!", "rating": {"stars": 5, "color": "black"}},{  "reviewer": "Reviewer2",  "text": "Absolutely fun and entertaining. The play lacks thematic depth when compared to other plays by Shakespeare.", "rating": {"stars": 4, "color": "black"}}]}
        

5. Repeat the request. Because the rate limit policy limits requests to 1 per day, the request results in a 429 - Too Many Requests error.

6. Exit from the curl pod.

7. Optional: Clean up the Gloo resources that you created to test this policy.

     kubectl --context $REMOTE_CONTEXT1 -n gloo-mesh-addons delete RateLimitServerConfig rl-server-config
   kubectl --context $REMOTE_CONTEXT1 -n bookinfo delete RateLimitServerSettings rl-server
   kubectl --context $REMOTE_CONTEXT1 -n bookinfo delete RateLimitClientConfig rl-client-config
   kubectl --context $REMOTE_CONTEXT1 -n bookinfo delete RateLimitPolicy rl-policy