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:
$ 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.
kubectl apply -f prom-operator.yaml
We'll also want to create an additional ServiceAccount
s for the actual Prometheus instances.
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.
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
.
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.
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.
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.
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.
$ 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.
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:
$ 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.
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.
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