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

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 Platform CLI, meshctl, 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
   

Configure rate limit policies

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:
  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

Verify rate limit policies

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.

   kubectl --context ${REMOTE_CONTEXT1} apply -f - <<EOF
   apiVersion: admin.gloo.solo.io/v2
   kind: RateLimitServerConfig
   metadata:
     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:
     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:
     name: rl-client-config
     namespace: bookinfo
   spec:
     raw:
       rateLimits:
       - actions:
         - genericKey:
             descriptorValue: counter
   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:
     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.
   • Kubernetes 1.22 or earlier
   • Kubernetes 1.23 or later

   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 ratings app.

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

      Example output:

      {"id":1,"ratings":{"Reviewer1":5,"Reviewer2":4}}200
      

   Use the kubernetes 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.

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