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Layer 7 Observability with Consul Service Mesh, Prometheus, Grafana, and Kubernetes

  • 15 min
  • Products Usedconsul

Consul service mesh deploys an Envoy sidecar proxy alongside each service instance in a datacenter. The sidecar proxy brokers traffic between the local service instance and other services registered with Consul. The proxy is aware of all traffic that passes through it. In addition to securing inter-service communication, the proxy can also collect and expose data about the service instance. Starting with version 1.5, Consul service mesh is able to configure Envoy to expose layer 7 metrics, such as HTTP status codes or request latency, to monitoring tools like Prometheus.

In this tutorial, you will:

  • Configure Consul to expose Envoy metrics to Prometheus
  • Deploy Consul using the official helm chart.
  • Deploy Prometheus and Grafana using their official Helm charts.
  • Deploy a multi-tier demo application that is configured to be scraped by Prometheus.
  • Start a traffic simulation deployment, and observe the application traffic in Grafana.

»Prerequisites

If you already have a Kubernetes cluster running with Helm and kubectl installed, you can start on the tutorial right away. If not, set up a Kubernetes cluster using your favorite method that supports persistent volume claims, or install and start Minikube or kind.

This guide was tested with:

  • Kubernetes v1.18.2
  • Minikube v1.10.1
  • kind v0.8.1
  • Helm v3.2.1

If you use Minikube, you may want to start it with a little bit of extra memory.

$ minikube start --memory 4096 --kubernetes-version v1.18.2

You must also install kubectl, and both install and initialize Helm.

Also, ensure you have the latest helm charts for Consul, Prometheus, and Grafana.

helm repo add stable https://kubernetes-charts.storage.googleapis.com && \
helm repo add hashicorp https://helm.releases.hashicorp.com && \
helm repo update

Next, clone the GitHub repository that contains the files you'll use with this tutorial.

$ git clone https://github.com/hashicorp/consul-k8s-prometheus-grafana-hashicups-demoapp.git

Now, change directories into the repository you just cloned.

$ cd consul-k8s-prometheus-grafana-hashicups-demoapp

Now, checkout the tagged version verified for this tutorial.

git checkout tags/0.0.2

We'll refer to this directory as your working directory, and you'll run the rest of the commands in this tutorial from this directory.

»Deploy Consul service mesh using Helm

Once you have set up the prerequisites, you're ready to install Consul.

Open the file in your working directory called helm/consul-values.yaml and review the settings. You can override many of the values in Consul's values file using annotations on specific services.

# specify a name for your Consul installation & datacenter
global:
  name: consul
  datacenter: dc1

server:
  # specify that this Consul datacenter should run one server
  replicas: 1
  bootstrapExpect: 1
  disruptionBudget:
    enabled: true
    maxUnavailable: 0

client:
  enabled: true
  # enable grpc on your client to support Consul service mesh
  grpc: true
# enable the Consul web UI
ui:
  enabled: true

connectInject:
  enabled: true
  # inject an envoy sidecar into every new pod,
  # except for those with annotations that prevent injection
  default: true
  # these settings enable L7 metrics collection and were added in 1.5
  centralConfig:
    enabled: true
    # set the default protocol (can be overwritten with annotations)
    defaultProtocol: 'http'
    # proxyDefaults is a raw json string that will be applied to all service mesh
    # proxy sidecar pods that can include any valid configuration for the
    # configured proxy.
    proxyDefaults: |
      {
        "envoy_prometheus_bind_addr": "0.0.0.0:9102"
      }

Note the proxyDefaults entry. This entry injects a proxy-defaults Consul configuration entry for the envoy_prometheus_bind_addr setting that is applied to all Envoy proxy instances. Consul then uses that setting to configure where Envoy will publish Prometheus metrics. This is important because you will need to annotate your pods with this port so that Prometheus can scrape them. We will cover this in more detail later in the tutorial.

Now install Consul in your Kubernetes cluster and give Kubernetes a name for your Consul installation.

$ helm install -f helm/consul-values.yaml consul hashicorp/consul --version "0.23.1" --wait

The output will be a list of all the Kubernetes resources created. The output has been abbreviated, but will look similar to the following.

NAME: consul
LAST DEPLOYED: Thu Aug 13 07:52:03 2020
NAMESPACE: default
STATUS: deployed
...

  $ helm status consul
  $ helm get all consul

Check that Consul is running in your Kubernetes cluster using kubectl.

$ watch kubectl get pods

Consul setup is complete when all pods have a status of Running, as illustrated in the following output.

NAME                                                         READY   STATUS    RESTARTS   AGE
consul-9p9jf                                                 1/1     Running   0          31m
consul-connect-injector-webhook-deployment-b797f6fd4-2cwvm   1/1     Running   0          31m
consul-server-0                                              1/1     Running   0          31m

Leave the watch running and open a new terminal.

»Deploy the metrics pipeline

Consul service mesh can integrate with a variety of metrics tooling, but in this tutorial, you will use Prometheus and Grafana to collect and visualize metrics.

»Deploy Prometheus with Helm

Install the official Prometheus Helm chart using the values in helm/prometheus-values.yaml.

$ helm install -f helm/prometheus-values.yaml prometheus stable/prometheus --version "11.7.0" --wait

The output has been abbreviated, but will look similar to the following.

NAME: prometheus
LAST DEPLOYED: Thu Aug 13 07:52:32 2020
NAMESPACE: default
STATUS: deployed
...

For more information on running Prometheus, visit:
https://prometheus.io/

Switch back to the terminal where the kubectl watch is running. Prometheus setup is complete when all pods have a status of Running, as illustrated in the following output.

consul-9p9jf                                                 1/1     Running   0          43m
consul-connect-injector-webhook-deployment-b797f6fd4-2cwvm   1/1     Running   0          43m
consul-server-0                                              1/1     Running   0          43m
prometheus-kube-state-metrics-c65b87574-4zjb7                3/3     Running   0          42m
prometheus-node-exporter-cq7lb                               3/3     Running   0          42m
prometheus-pushgateway-697b8c46cd-rjq4q                      3/3     Running   0          42m
prometheus-server-64c7484778-hwtmg                           4/4     Running   0          42m

»Deploy Grafana with Helm

Installing Grafana will follow a similar process. Install the official Grafana Helm chart using the values in helm/grafana-values.yaml. This configuration will tell Grafana to use Prometheus as a datasource, and set the admin password to password.

$ helm install -f helm/grafana-values.yaml grafana stable/grafana --version "5.3.6" --wait

The output has been abbreviated, but will look similar to the following.

NAME: grafana
LAST DEPLOYED: Thu Aug 13 07:53:43 2020
NAMESPACE: default
STATUS: deployed
...
#################################################################################
######   WARNING: Persistence is disabled!!! You will lose your data when   #####
######            the Grafana pod is terminated.                            #####
#################################################################################

Switch back to the terminal where the kubectl watch is running. Grafana setup is complete when the Grafana pod has a status of Running, as illustrated in the following output.

NAME                                                         READY   STATUS    RESTARTS   AGE
consul-9p9jf                                                 1/1     Running   0          117m
consul-connect-injector-webhook-deployment-b797f6fd4-2cwvm   1/1     Running   0          117m
consul-server-0                                              1/1     Running   0          117m
grafana-7d6f454b75-pb687                                     3/3     Running   0          115m
prometheus-kube-state-metrics-c65b87574-4zjb7                3/3     Running   0          117m
prometheus-node-exporter-cq7lb                               3/3     Running   0          117m
prometheus-pushgateway-697b8c46cd-rjq4q                      3/3     Running   0          117m
prometheus-server-64c7484778-hwtmg                           4/4     Running   0          117m

The output includes shell-specific instructions to access your Grafana UI and admin password. You specified the admin password in the helm/grafana-values.yaml file as password. To expose the Grafana UI outside the cluster, issue the following command.

$ export POD_NAME=$(kubectl get pods --namespace default -l "app.kubernetes.io/name=grafana,app.kubernetes.io/instance=grafana" -o jsonpath="{.items[0].metadata.name}") && \
  kubectl --namespace default port-forward $POD_NAME 3000

You should receive output similar to the following.

Forwarding from 127.0.0.1:3000 -> 3000
Forwarding from [::1]:3000 -> 3000

Leave this port-forward session active so that you can visit the UI again later once metrics are being collected.

Navigate to localhost:3000 in a browser tab and log in to the Grafana UI. Once you have logged into the Grafana UI, hover over the dashboards icon (four squares in the left hand menu) and then click the "Manage" option.

Add a dashboard using the Grafana GUI

This will take you to a page that gives you some choices about how to upload Grafana dashboards. Click the "Import" button on the right hand side of the screen. Open the file called grafana/hashicups-dashboard.json and copy the contents into the JSON window of the Grafana UI. Click through the rest of the options, and you will end up with a dashboard waiting for data to display.

»Deploy a demo application on Kubernetes

Now that your monitoring pipeline is set up, deploy a demo application that will generate data. We will be using HashiCups, an application that emulates an online order app for a coffee shop. For this tutorial, the HashiCups application includes a React front end, a GraphQL API, a REST API and a Postgres database.

All the files defining HashiCups are in the app directory. Open the app/frontend.yaml file. Notice that the Deployment has been annotated with the following Prometheus configuration.

prometheus.io/scrape: 'true'
prometheus.io/port: '9102'

All of the other resources have been similarly annotated. This allows Prometheus to discover resources in the Kubernetes cluster that should be exposing metrics, and tells Prometheus what port to the metrics are exposed at. Recall that earlier in the tutorial you configured the proxyDefaults entry in the consul-values.yaml file, and set the envoy_prometheus_bind_addr to 0.0.0.0:9102. By setting this annotation on each resource, you are configuring the other side of the feedback loop. It may be helpful to think of this as a publish/subscribe pattern, where you told Consul to configure Envoy to publish metrics on port 9102, and now have told Prometheus to subscribe on each proxy at port 9102. You will verify this configuration is applied later in the tutorial.

Open a new terminal, and deploy the demo application.

$ kubectl apply -f app

You should receive the following output.

service/frontend-service created
configmap/nginx-configmap created
deployment.apps/frontend created
service/products-api-service created
serviceaccount/products-api created
configmap/db-configmap created
deployment.apps/products-api created
service/postgres created
deployment.apps/postgres created
service/public-api-service created
deployment.apps/public-api created

HashiCups will take a few minutes to deploy. Switch back to the terminal where the kubectl watch is running. Grafana setup is complete when all pods have a status of Running, as illustrated in the following output.

NAME                                                         READY   STATUS    RESTARTS   AGE
consul-9p9jf                                                 1/1     Running   0          122m
consul-connect-injector-webhook-deployment-b797f6fd4-2cwvm   1/1     Running   0          122m
consul-server-0                                              1/1     Running   0          122m
frontend-6454bd57f-v958p                                     3/3     Running   0          120m
grafana-7d6f454b75-pb687                                     3/3     Running   0          120m
postgres-55899dddd-5z4hx                                     3/3     Running   0          120m
products-api-9cd5bbb69-j8x69                                 3/3     Running   0          120m
prometheus-kube-state-metrics-c65b87574-4zjb7                3/3     Running   0          122m
prometheus-node-exporter-cq7lb                               3/3     Running   0          122m
prometheus-pushgateway-697b8c46cd-rjq4q                      3/3     Running   0          122m
prometheus-server-64c7484778-hwtmg                           4/4     Running   0          122m
public-api-5f698b886-rfnh7                                   3/3     Running   0          120m

Test the application by viewing the React front end. You can do this by forwarding the frontend deployment's port 80 to your development host.

$ kubectl port-forward deploy/frontend 8080:80

You will receive the following output.

Forwarding from 127.0.0.1:8080 -> 80
Forwarding from [::1]:8080 -> 80

Navigate to localhost:8080 in a browser window. You should observe the following screen.

View the HashiCups Front End

Now that the application is running let's verify that Consul did, in fact, configure Envoy to publish metrics at port 9102. The Envoy side-car proxy can be reached at port 19000. Open a new terminal, and issue the following command.

$ kubectl port-forward deploy/frontend 19000:19000

You will receive the following output.

Forwarding from 127.0.0.1:19000 -> 19000
Forwarding from [::1]:19000 -> 19000

Navigate to http://localhost:19000/config_dump in a browser window. You should see what looks like a raw JSON document dumped to the screen. This is the Envoy configuration. Search for 9102 and you should find two different stanzas that reference this port. One of them is included next for reference.

{
  "name": "envoy_prometheus_metrics_listener",
  "address": {
  "socket_address": {
    "address": "0.0.0.0",
    "port_value": 9102
  }
}

Notice that the configuration matches the values you specified in the proxyDefaults stanza in the helm/consul-values.yaml file. This confirms that Consul has configured Envoy to publish Prometheus metrics. Enter CTRL-C to stop the port-forward session from the side-car proxy. You will not need to reference it again for the remainder of the tutorial.

»Visualize application metrics

While Grafana is optimized for at a glance observability, the Prometheus UI can be useful as well. Issue the following command to expose the Prometheus UI to your development host.

$ kubectl port-forward deploy/prometheus-server 9090:9090

You will receive the following output.

Forwarding from 127.0.0.1:9090 -> 9090
Forwarding from [::1]:9090 -> 9090

»Discover available metrics with Prometheus

Navigate to localhost:9090 in a browser window, and you should observe the default Prometheus UI. In the textbox at the top of the screen paste sum by(__name__)({app="products-api"}) and then click the button labeled "Execute". Your screen will now look similar to the following.

Discover products-api available metrics

You have now performed a PromQL query that will list all available metrics for resources that have the product-api label. In this case, that is the REST API resource you deployed from the app folder. This list of metrics can be used as constraints for further PromQL queries both here and in the Grafana UI.

Next, from within the Prometheus UI, click the dropdown menu item labeled "Status" in the menu bar at the top of the screen, and click on the option labeled "Targets". This will navigate the UI to the Targets screen where you can review all of the resources that Prometheus is monitoring. The Prometheus Helm chart you installed earlier is configured to monitor all of the Kubernetes infrastructure as well as Prometheus itself.

Click on the button labeled "show less" next to each section header except the one labeled "kubernetes-pods". Your screen should appear similar to the following.

View Prometheus targets

Notice that four pods are running, and have a State of "UP". Look at the first label for each pod in the Label column. You should have entries for app="frontend", app="postgres", app="products-api", and app="public-api". This confirms that Prometheus is collecting metrics from all of your annotated resources, and that they are all up and running.

Go back to the terminal where your port-forward session for the Prometheus UI is running, and type CTRL-C to end the session. You will not need to access the Prometheus UI for the remainder of the tutorial.

»Simulate traffic

Now that you know the application is running, start generating some load so that you will have some metrics to look at in Grafana.

$ kubectl apply -f traffic.yaml

You will receive the following output.

configmap/k6-configmap created
deployment.apps/traffic created

Envoy exposes a huge number of metrics. Which metrics are important to monitor will depend on your application. For this tutorial we have preconfigured a HashiCups-specific Grafana dashboard with a couple of basic metrics, but you should systematically consider what others you will need to collect as you move from testing into production.

»View Grafana dashboard

Now that you have metrics flowing through your pipeline, and a traffic simulation deployment running, navigate back to your Grafana dashboard in the Grafana UI at localhost:3000, and you should observe a screen similar to the following.

View Prometheus targets

Notice that once you started the traffic simulation deployment Prometheus started to log active connections. This dashboard is simplistic, but illustrates that metrics are flowing through the pipeline, and should give you a reasonable starting point for setting up your own observability tooling.

»Clean up

If you've been using Minikube, you can tear down your environment by issuing the following command.

$ minikube delete

If you want to get rid of the configuration files and Consul Helm chart, recursively remove the consul-k8s-prometheus-grafana-hashicups-demoapp directory. `

$ cd ..

$ rm -rf consul-k8s-prometheus-grafana-hashicups-demoapp

»Next steps

In this tutorial, you set up layer 7 metrics collection and visualization in a Kubernetes cluster using Consul service mesh, Prometheus, and Grafana, all deployed via Helm charts. Specifically, you:

  • Configured Consul and Envoy to expose application metrics to Prometheus.
  • Deployed Consul using the official helm chart.
  • Deployed Prometheus and Grafana using their official Helm charts.
  • Deployed a multi-tier demo application that was configured to be scraped by Prometheus.
  • Started a traffic simulation deployment, and observed the metrics in Prometheus and Grafana.

Because all of these programs can run outside of Kubernetes, you can set this pipeline up in any environment or collect metrics from workloads running on mixed infrastructure.

To learn more about the configuration options in Consul that enable layer 7 metrics collection with or without Kubernetes, refer to our documentation. For more information on centrally configuring Consul, take a look at the centralized configuration documentation.

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