** This tutorial was originally published on Datawire.io in 2017. As a result, some of the tools mentioned may no longer be actively maintained. Please join our Slack if you have any questions.

Monitoring Envoy and Ambassador on Kubernetes with the Prometheus Operator

In the Kubernetes ecosystem, one of the emerging themes is how applications can best take advantage of the various capabilities of Kubernetes. The Kubernetes community has also introduced new concepts such as Custom Resources to make it easier to build Kubernetes-native software.

In late 2016, CoreOS introduced the Operator pattern and released the Prometheus Operator as a working example of the pattern. The Prometheus Operator automatically creates and manages Prometheus monitoring instances.

The operator model is especially powerful for cloud-native organizations deploying multiple services. In this model, each team can deploy their own Prometheus instance as necessary, instead of relying on a central SRE team to implement monitoring.

Envoy, Ambassador, and Prometheus

In this tutorial, we'll show how the Prometheus Operator can be used to monitor an Envoy proxy deployed at the edge. Envoy is an open source L7 proxy. One of the (many) reasons for Envoy's growing popularity is its emphasis on observability. Envoy uses statsd as its output format.

Instead of using Envoy directly, we'll use Ambassador. Ambassador is a Kubernetes-native API Gateway built on Envoy. Similar to the Prometheus Operator, Ambassador configures and manages Envoy instances in Kubernetes, so that the end user doesn't need to do that work directly.

Prerequisites

This tutorial assumes you're running Kubernetes 1.8 or later, with RBAC enabled.

Note: If you're running on Google Kubernetes Engine, you'll need to grant cluster-admin privileges to the account that will be installing Prometheus and Ambassador. You can do this with the commands below:

Copy $ gcloud info | grep Account Account: [username@example.org] $ kubectl create clusterrolebinding my-cluster-admin-binding --clusterrole=cluster-admin --user=username@example.org

Deploy the Prometheus Operator

The Prometheus Operator is configured as a Kubernetes deployment . We'll first deploy the Prometheus operator.

Copy apiVersion: rbac.authorization.k8s.io/v1beta1 kind: ClusterRoleBinding metadata: name: prometheus-operator roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: prometheus-operator subjects: - kind: ServiceAccount name: prometheus-operator namespace: default --- apiVersion: rbac.authorization.k8s.io/v1beta1 kind: ClusterRole metadata: name: prometheus-operator rules: - apiGroups: - extensions resources: - thirdpartyresources verbs: - "*" - apiGroups: - apiextensions.k8s.io resources: - customresourcedefinitions verbs: - "*" - apiGroups: - monitoring.coreos.com resources: - alertmanagers - prometheuses - servicemonitors verbs: - "*" - apiGroups: - apps resources: - statefulsets verbs: ["*"] - apiGroups: [""] resources: - configmaps - secrets verbs: ["*"] - apiGroups: [""] resources: - pods verbs: ["list", "delete"] - apiGroups: [""] resources: - services - endpoints verbs: ["get", "create", "update"] - apiGroups: [""] resources: - nodes verbs: ["list", "watch"] - apiGroups: [""] resources: - namespaces verbs: ["list"] --- apiVersion: v1 kind: ServiceAccount metadata: name: prometheus-operator --- apiVersion: extensions/v1beta1 kind: Deployment metadata: labels: k8s-app: prometheus-operator name: prometheus-operator spec: replicas: 1 template: metadata: labels: k8s-app: prometheus-operator spec: containers: - args: - --kubelet-service=kube-system/kubelet - --config-reloader-image=quay.io/coreos/configmap-reload:v0.0.1 image: quay.io/coreos/prometheus-operator:v0.15.0 name: prometheus-operator ports: - containerPort: 8080 name: http resources: limits: cpu: 200m memory: 100Mi requests: cpu: 100m memory: 50Mi serviceAccountName: prometheus-operator

kubectl apply -f prom-operator.yaml

We'll also want to create an additional ServiceAccount s for the actual Prometheus instances.

Copy apiVersion: v1 kind: ServiceAccount metadata: name: prometheus --- apiVersion: rbac.authorization.k8s.io/v1beta1 kind: ClusterRole metadata: name: prometheus rules: - apiGroups: [""] resources: - nodes - services - endpoints - pods verbs: ["get", "list", "watch"] - apiGroups: [""] resources: - configmaps verbs: ["get"] - nonResourceURLs: ["/metrics"] verbs: ["get"] --- apiVersion: rbac.authorization.k8s.io/v1beta1 kind: ClusterRoleBinding metadata: name: prometheus roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: prometheus subjects: - kind: ServiceAccount name: prometheus namespace: default

kubectl apply -f prom-rbac.yaml

The Operator functions as your virtual SRE. At all times, the Prometheus operator insures that you have a set of Prometheus servers running with the appropriate configuration.

Deploy Ambassador

Ambassador also functions as your virtual SRE. At all times, Ambassador insures that you have a set of Envoy proxies running the appropriate configuration.

We're going to deploy Ambassador into Kubernetes. On each Ambassador pod, we'll also deploy an additional container that runs the Prometheus statsd exporter. The exporter will collect the statsd metrics emitted by Envoy over UDP, and proxy them to Prometheus over TCP in Prometheus metrics format.

Copy --- apiVersion: v1 kind: Service metadata: labels: service: ambassador-admin name: ambassador-admin spec: type: NodePort ports: - name: ambassador-admin port: 8877 targetPort: 8877 selector: service: ambassador --- apiVersion: rbac.authorization.k8s.io/v1beta1 kind: ClusterRole metadata: name: ambassador rules: - apiGroups: [""] resources: - services verbs: ["get", "list", "watch"] - apiGroups: [""] resources: - configmaps verbs: ["create", "update", "patch", "get", "list", "watch"] - apiGroups: [""] resources: - secrets verbs: ["get", "list", "watch"] --- apiVersion: v1 kind: ServiceAccount metadata: name: ambassador --- apiVersion: rbac.authorization.k8s.io/v1beta1 kind: ClusterRoleBinding metadata: name: ambassador roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: ambassador subjects: - kind: ServiceAccount name: ambassador namespace: default --- apiVersion: extensions/v1beta1 kind: Deployment metadata: name: ambassador spec: replicas: 1 template: metadata: labels: service: ambassador spec: serviceAccountName: ambassador containers: - name: ambassador image: datawire/ambassador:0.21.0 imagePullPolicy: Always resources: limits: cpu: 1 memory: 400Mi requests: cpu: 200m memory: 100Mi env: - name: AMBASSADOR_NAMESPACE valueFrom: fieldRef: fieldPath: metadata.namespace livenessProbe: httpGet: path: /ambassador/v0/check_alive port: 8877 initialDelaySeconds: 3 periodSeconds: 3 readinessProbe: httpGet: path: /ambassador/v0/check_ready port: 8877 initialDelaySeconds: 3 periodSeconds: 3 - name: statsd-sink image: datawire/prom-statsd-exporter:0.6.0 restartPolicy: Always

kubectl apply -f ambassador-rbac.yaml

Ambassador is typically deployed as an API Gateway at the edge of your network. We'll deploy a service to map to the Ambassador deployment . Note: if you're not on AWS or GKE, you'll need to update the service below to be a NodePort instead of a LoadBalancer .

Copy --- apiVersion: v1 kind: Service metadata: labels: service: ambassador name: ambassador spec: type: LoadBalancer ports: - name: ambassador port: 80 targetPort: 80 selector: service: ambassador

kubectl apply -f ambassador.yaml

You should now have a working Ambassador and StatsD/Prometheus exporter that is accessible from outside your cluster.

Configure Prometheus

We now have Ambassador/Envoy running, along with the Prometheus Operator. How do we hook this all together? Logically, all the metrics data flows from Envoy to Prometheus in the following way:

So far, we've deployed Envoy and the StatsD exporter, so now it's time to deploy the other components of this flow.

We'll first create a Kubernetes service that points to the StatsD exporter. We'll then create a ServiceMonitor that tells Prometheus to add the service as a target.

Copy --- apiVersion: v1 kind: Service metadata: name: ambassador-monitor labels: service: ambassador-monitor spec: selector: service: ambassador type: ClusterIP clusterIP: None ports: - name: prometheus-metrics port: 9102 targetPort: 9102 protocol: TCP --- apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: ambassador-monitor labels: ambassador: monitoring spec: selector: matchLabels: service: ambassador-monitor endpoints: - port: prometheus-metrics

kubectl apply -f statsd-sink-svc.yaml

Next, we need to tell the Prometheus Operator to create a Prometheus cluster for us. The Prometheus cluster is configured to collect data from any ServiceMonitor with the ambassador:monitoring label.

Copy apiVersion: monitoring.coreos.com/v1 kind: Prometheus metadata: name: prometheus spec: serviceAccountName: prometheus serviceMonitorSelector: matchLabels: ambassador: monitoring resources: requests: memory: 400Mi

kubectl apply -f prometheus.yaml

Finally, we can create a service to expose Prometheus to the rest of the world. Again, if you're not on AWS or GKE, you'll want to use a NodePort instead.

Copy apiVersion: v1 kind: Service metadata: name: prometheus spec: type: NodePort ports: - name: web port: 9090 protocol: TCP targetPort: web selector: prometheus: prometheus

kubectl apply -f prom-svc.yaml

Testing

We've now configured Prometheus to monitor Envoy, so now let's test this out. Get the external IP address for Prometheus.

Copy $ kubectl get services NAME CLUSTER-IP EXTERNAL-IP PORT(S) AGE ambassador 10.11.255.93 35.221.115.102 80:32079/TCP 3h ambassador-admin 10.11.246.117 <nodes> 8877:30366/TCP 3h ambassador-monitor None <none> 9102/TCP 3h kubernetes 10.11.240.1 <none> 443/TCP 3h prometheus 10.11.254.180 35.191.39.173 9090:32134/TCP 3h prometheus-operated None <none> 9090/TCP 3h

In the example above, this is 35.191.39.173 . Now, go to http://$PROM_IP:9090 to see the Prometheus UI. You should see a number of metrics automatically populate in Prometheus.

Troubleshooting

If the above doesn't work, there are a few things to investigate:

Make sure all your pods are running ( kubectl get pods )

) Check the logs on the Prometheus cluster ( kubectl logs $PROM_POD prometheus )

) Check Ambassador diagnostics to verify Ambassador is working correctly

Get a service running in Envoy

The metrics so far haven't been very interesting, since we haven't routed any traffic through Envoy. We'll use Ambassador to set up a route from Envoy to the httpbin service. Ambassador is configured using Kubernetes annotations, so we'll do that here.

Copy apiVersion: v1 kind: Service metadata: name: httpbin annotations: getambassador.io/config: | --- apiVersion: ambassador/v0 kind: Mapping name: httpbin_mapping prefix: /httpbin/ service: httpbin.org:80 host_rewrite: httpbin.org spec: ports: - port: 80

kubectl apply -f httpbin.yaml

Now, if we get the external IP address of Ambassador, we can route requests through Ambassador to the httpbin service:

Copy $ kubectl get services NAME CLUSTER-IP EXTERNAL-IP PORT(S) AGE ambassador 10.11.255.93 35.221.115.102 80:32079/TCP 3h ambassador-admin 10.11.246.117 <nodes> 8877:30366/TCP 3h ambassador-monitor None <none> 9102/TCP 3h kubernetes 10.11.240.1 <none> 443/TCP 3h prometheus 10.11.254.180 35.191.39.173 9090:32134/TCP 3h prometheus-operated None <none> 9090/TCP 3h $ curl http://35.221.115.102/httpbin/ip { "origin": "35.214.10.110" }

Run a curl command a few times, as shown above. Going back to the Prometheus dashboard, you'll see that a bevy of new metrics that contain httpbin have appeared. Pick any of these metrics to explore further. For more information on Envoy stats, Matt Klein has written a detailed overview of Envoy's stats architecture. If you are interested in setting up a Grafana dashboard, Alex Gervais has published a sample Grafana/Ambassador dashboard.

Conclusion

Microservices, as you know, are distributed systems. The key to scaling distributed systems is creating loose coupling between each of the components. In a microservices architecture, the most painful source of coupling is actually organizational and not architectural. Design patterns such as the Prometheus Operator enable teams to be more self-sufficient, and reduce organizational coupling, enabling teams to code faster.

Next Steps