Workload Monitoring

Apart from infrastructure metrics like CPU, memory, disk IO, etc., applications generate metrics based on their app logic. For example, DB applications can have several queries, several pending transactions, and so on; message broker applications can have several topics, several messages not delivered, and so on. These metrics are essential in debugging and finding out root-causing issues.

Kubernetes 2.0 provides a mechanism to display both application/workload metrics and the infrastructure metrics of pods.

ConfigMap

All workload ConfigMaps share a consistent syntax. Below is a detailed explanation of user configurations, such as targetPodSelector, auth, and more. Additionally, an example is provided to demonstrate how workloads can be defined in the opsramp-workload-metric-user-config ConfigMap.

Sample ConfigMap

apiVersion: v1
kind: ConfigMap
metadata:
  name: opsramp-workload-metric-user-config
  namespace: opsramp-agent
data:
  workloads: |
    mysql:
      - name: mysql1 
        collectionFrequency: 1m
        auth: credentials
        userName:
          source: value 
          value: root 
        password:
          source: value 
          value: password 
        targetPodSelector:
          matchLabels: 
            - key: app.kubernetes.io/name
              operator: == 
              value:
                - mysql

Field Descriptions

Common Configuration for All Workloads

This is a common configuration settings that apply to all workloads.

  userName: 
    source: configmap 
    value: default/nginx-cm/user 
  password: 
    source: secret 
    value: default/nginx-secret/password 

End-to-End Guide: Monitoring a Redis Instance in Kubernetes 2.0

This example demonstrates how to monitor a Redis application instance running in a Kubernetes 2.0 cluster using a ConfigMap. The provided ConfigMap supports multiple authentication methods for seamless integration.

Step 1: Retrieve the ConfigMap

To check the existing workload configuration, use the following command:

kubectl get configmap workload-master -n <agent-installed-namespace>

Step 2: Create the ConfigMap

If this is your first time setting up workload monitoring, create a new ConfigMap named workload-master in the <agent-installed-namespace>. Use the following manifest as a template:

apiVersion: v1
kind: ConfigMap
metadata:
  name: workload-master
  namespace: opsramp-agent
data:
  workloads: |
    redis:
      - name: redis
        auth: none
        port: 6379
        collectionFrequency: 2m
        targetPodSelector:
          matchLabels:
            - key: app
              operator: ==
              value:
                - redis
      - name: redis-with-tls
        auth: tls
        certFile:
          source: secret
          value: default/redis-tls-client/redis-client.crt
        keyFile:
          source: secret
          value: default/redis-tls-client/redis-client.key
        port: 6379
        collectionFrequency: 2m
        targetPodSelector:
          matchLabels:
            - key: app
              operator: ==
              value:
                - redis-tls
      - name: redis-with-credentials
        auth: credentials
        userName:
          source: value
          value: sri
        password:
          source: configmap
          value: default/redis-config/REDIS_PASSWORD
        port: 6379
        collectionFrequency: 2m
        targetPodSelector:
          matchLabels:
            - key: app
              operator: ==
              value:
                - redis-creds

Step 3: Apply the ConfigMap

Once you have created or updated the manifest with all desired workloads, apply it using the following command:

kubectl apply -f <path-to-your-manifest-file>

Step 4: View Metrics in OpsRamp Portal

After a few minutes, you will be able to see the metrics in the OpsRamp portal under Dashboards > Dashboard.

Step 5: Create Alerts and Availability Rules

With metrics flowing into the OpsRamp portal, you can create alerts and availability rules based on these workload or application-specific metrics by editing the respective K8s ConfigMaps. This version provides clear steps and maintains a logical flow, making it easy for users to follow along.

The configuration of the Redis application has been successfully completed, and you can now monitor the Redis instances effectively.

You can monitor other application instances within a Kubernetes 2.0 cluster by utilizing a ConfigMap. Refer to the next page for the list of supported applications.