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Example: Add logging and metrics to the PHP / Redis Guestbook example

This tutorial builds upon the PHP Guestbook with Redis tutorial. Lightweight log, metric, and network data open source shippers, or Beats, from Elastic are deployed in the same Kubernetes cluster as the guestbook. The Beats collect, parse, and index the data into Elasticsearch so that you can view and analyze the resulting operational information in Kibana. This example consists of the following components:

• A running instance of the PHP Guestbook with Redis tutorial
• Elasticsearch and Kibana
• Filebeat
• Metricbeat
• Packetbeat

• Objectives
• Before you begin
• Start up the PHP Guestbook with Redis
• Add a Cluster role binding
• Install kube-state-metrics
• Clone the Elastic examples GitHub repo
• Create a Kubernetes Secret
• Managed service
• Deploy the Beats
• View in Kibana
• Scale your deployments and see new pods being monitored
• View the changes in Kibana
• Cleaning up
• What's next

Objectives

• Start up the PHP Guestbook with Redis.
• Install kube-state-metrics.
• Create a Kubernetes secret.
• Deploy the Beats.
• View dashboards of your logs and metrics.

Before you begin

You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. If you do not already have a cluster, you can create one by using Minikube, or you can use one of these Kubernetes playgrounds:

• Katacoda
• Play with Kubernetes

To check the version, enter kubectl version.

Additionally you need:

• A running deployment of the PHP Guestbook with Redis tutorial.

• A running Elasticsearch and Kibana deployment. You can use Elasticsearch Service in Elastic Cloud, run the download files on your workstation or servers, or the Elastic Helm Charts.

Start up the PHP Guestbook with Redis

This tutorial builds on the PHP Guestbook with Redis tutorial. If you have the guestbook application running, then you can monitor that. If you do not have it running then follow the instructions to deploy the guestbook and do not perform the Cleanup steps. Come back to this page when you have the guestbook running.

Add a Cluster role binding

Create a cluster level role binding so that you can deploy kube-state-metrics and the Beats at the cluster level (in kube-system).

kubectl create clusterrolebinding cluster-admin-binding \
 --clusterrole=cluster-admin --user=<your email associated with the k8s provider account>

Install kube-state-metrics

Kubernetes kube-state-metrics is a simple service that listens to the Kubernetes API server and generates metrics about the state of the objects. Metricbeat reports these metrics. Add kube-state-metrics to the Kubernetes cluster that the guestbook is running in.

Check to see if kube-state-metrics is running

kubectl get pods --namespace=kube-system | grep kube-state

Install kube-state-metrics if needed

git clone https://github.com/kubernetes/kube-state-metrics.git kube-state-metrics
kubectl create -f examples/standard
kubectl get pods --namespace=kube-system | grep kube-state-metrics

Verify that kube-state-metrics is running and ready

kubectl get pods -n kube-system -l app.kubernetes.io/name=kube-state-metrics

Output:

NAME                                 READY   STATUS    RESTARTS   AGE
kube-state-metrics-89d656bf8-vdthm   2/2     Running     0          21s

Clone the Elastic examples GitHub repo

git clone https://github.com/elastic/examples.git

The rest of the commands will reference files in the examples/beats-k8s-send-anywhere directory, so change dir there:

cd examples/beats-k8s-send-anywhere

Create a Kubernetes Secret

A Kubernetes SecretStores sensitive information, such as passwords, OAuth tokens, and ssh keys. is an object that contains a small amount of sensitive data such as a password, a token, or a key. Such information might otherwise be put in a Pod specification or in an image; putting it in a Secret object allows for more control over how it is used, and reduces the risk of accidental exposure.

Note: There are two sets of steps here, one for self managed Elasticsearch and Kibana (running on your servers or using the Elastic Helm Charts), and a second separate set for the managed service Elasticsearch Service in Elastic Cloud. Only create the secret for the type of Elasticsearch and Kibana system that you will use for this tutorial.

vi ELASTICSEARCH_HOSTS

<yoursecretpassword>

vi ELASTICSEARCH_PASSWORD

<your ingest username for Elasticsearch>

vi ELASTICSEARCH_USERNAME

vi KIBANA_HOST

kubectl create secret generic dynamic-logging \
  --from-file=./ELASTICSEARCH_HOSTS \
  --from-file=./ELASTICSEARCH_PASSWORD \
  --from-file=./ELASTICSEARCH_USERNAME \
  --from-file=./KIBANA_HOST \
  --namespace=kube-system

devk8s:ABC123def456ghi789jkl123mno456pqr789stu123vwx456yza789bcd012efg345hijj678klm901nop345zEwOTJjMTc5YWQ0YzQ5OThlN2U5MjAwYTg4NTIzZQ==

elastic:VFxJJf9Tjwer90wnfTghsn8w

vi ELASTIC_CLOUD_ID
vi ELASTIC_CLOUD_AUTH

kubectl create secret generic dynamic-logging \
  --from-file=./ELASTIC_CLOUD_ID \
  --from-file=./ELASTIC_CLOUD_AUTH \
  --namespace=kube-system

Deploy the Beats

Manifest files are provided for each Beat. These manifest files use the secret created earlier to configure the Beats to connect to your Elasticsearch and Kibana servers.

About Filebeat

Filebeat will collect logs from the Kubernetes nodes and the containers running in each pod running on those nodes. Filebeat is deployed as a DaemonSetEnsures a copy of a Pod is running across a set of nodes in a cluster. . Filebeat can autodiscover applications running in your Kubernetes cluster. At startup Filebeat scans existing containers and launches the proper configurations for them, then it will watch for new start/stop events.

Here is the autodiscover configuration that enables Filebeat to locate and parse Redis logs from the Redis containers deployed with the guestbook application. This configuration is in the file filebeat-kubernetes.yaml:

- condition.contains:
    kubernetes.labels.app: redis
  config:
    - module: redis
      log:
        input:
          type: docker
          containers.ids:
            - ${data.kubernetes.container.id}
      slowlog:
        enabled: true
        var.hosts: ["${data.host}:${data.port}"]

This configures Filebeat to apply the Filebeat module redis when a container is detected with a label app containing the string redis. The redis module has the ability to collect the log stream from the container by using the docker input type (reading the file on the Kubernetes node associated with the STDOUT stream from this Redis container). Additionally, the module has the ability to collect Redis slowlog entries by connecting to the proper pod host and port, which is provided in the container metadata.

Deploy Filebeat:

kubectl create -f filebeat-kubernetes.yaml

Verify

kubectl get pods -n kube-system -l k8s-app=filebeat-dynamic

About Metricbeat

Metricbeat autodiscover is configured in the same way as Filebeat. Here is the Metricbeat autodiscover configuration for the Redis containers. This configuration is in the file metricbeat-kubernetes.yaml:

- condition.equals:
    kubernetes.labels.tier: backend
  config:
    - module: redis
      metricsets: ["info", "keyspace"]
      period: 10s

      # Redis hosts
      hosts: ["${data.host}:${data.port}"]

This configures Metricbeat to apply the Metricbeat module redis when a container is detected with a label tier equal to the string backend. The redis module has the ability to collect the info and keyspace metrics from the container by connecting to the proper pod host and port, which is provided in the container metadata.

Deploy Metricbeat

kubectl create -f metricbeat-kubernetes.yaml

Verify

kubectl get pods -n kube-system -l k8s-app=metricbeat

About Packetbeat

Packetbeat configuration is different than Filebeat and Metricbeat. Rather than specify patterns to match against container labels the configuration is based on the protocols and port numbers involved. Shown below is a subset of the port numbers.

Note: If you are running a service on a non-standard port add that port number to the appropriate type in filebeat.yaml and delete / create the Packetbeat DaemonSet.

packetbeat.interfaces.device: any

packetbeat.protocols:
- type: dns
  ports: [53]
  include_authorities: true
  include_additionals: true

- type: http
  ports: [80, 8000, 8080, 9200]

- type: mysql
  ports: [3306]

- type: redis
  ports: [6379]

packetbeat.flows:
  timeout: 30s
  period: 10s

Deploy Packetbeat

kubectl create -f packetbeat-kubernetes.yaml

Verify

kubectl get pods -n kube-system -l k8s-app=packetbeat-dynamic

View in Kibana

Open Kibana in your browser and then open the Dashboard application. In the search bar type Kubernetes and click on the Metricbeat dashboard for Kubernetes. This dashboard reports on the state of your Nodes, deployments, etc.

Search for Packetbeat on the Dashboard page, and view the Packetbeat overview.

Similarly, view dashboards for Apache and Redis. You will see dashboards for logs and metrics for each. The Apache Metricbeat dashboard will be blank. Look at the Apache Filebeat dashboard and scroll to the bottom to view the Apache error logs. This will tell you why there are no metrics available for Apache.

To enable Metricbeat to retrieve the Apache metrics, enable server-status by adding a ConfigMap including a mod-status configuration file and re-deploy the guestbook.

Scale your deployments and see new pods being monitored

List the existing deployments:

kubectl get deployments

The output:

NAME            READY   UP-TO-DATE   AVAILABLE   AGE
frontend        3/3     3            3           3h27m
redis-master    1/1     1            1           3h27m
redis-slave     2/2     2            2           3h27m

Scale the frontend down to two pods:

kubectl scale --replicas=2 deployment/frontend

The output:

deployment.extensions/frontend scaled

View the changes in Kibana

See the screenshot, add the indicated filters and then add the columns to the view. You can see the ScalingReplicaSet entry that is marked, following from there to the top of the list of events shows the image being pulled, the volumes mounted, the pod starting, etc.

Cleaning up

Deleting the Deployments and Services also deletes any running Pods. Use labels to delete multiple resources with one command.

1. Run the following commands to delete all Pods, Deployments, and Services.

     kubectl delete deployment -l app=redis
     kubectl delete service -l app=redis
     kubectl delete deployment -l app=guestbook
     kubectl delete service -l app=guestbook
     kubectl delete -f filebeat-kubernetes.yaml
     kubectl delete -f metricbeat-kubernetes.yaml
     kubectl delete -f packetbeat-kubernetes.yaml
     kubectl delete secret dynamic-logging -n kube-system

2. Query the list of Pods to verify that no Pods are running:

     kubectl get pods

   The response should be this:

     No resources found.
   

What's next

• Learn about tools for monitoring resources
• Read more about logging architecture
• Read more about application introspection and debugging
• Read more about troubleshoot applications

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