Expand your Kubernetes knowledge with techniques to make your clusters dynamic and resilient.

DevOps for Developers

The world of DevOps has exploded with the help of technologies like Kubernetes and Docker.
In this course, you will learn about more advanced Kubernetes features such as monitoring, alerting, logging, and scaling - crucial concepts for any DevOps professional. You will learn how to monitor clusters, how to send alerts when potential issues arise, and how to query the whole system’s metrics and logs.
By the end of this course, you will have the required knowledge to make your clusters and applications truly dynamic and resilient, so that they require minimal manual involvement and are self-adaptive.

Kubernetes Monitoring, Logging and Auto-Scaling

# Short recap of the chapter

We explored the simplest way to scale our Deployments and StatefulSets. It's simple because the mechanism is baked into Kubernetes. All we had to do is define a `HorizontalPodAutoscaler` with target memory and CPU. While this method for auto-scaling is commonly used, it is often not sufficient. Not all applications increase memory or CPU usage when under stress. Even when they do, those two metrics might not be enough.

In one of the following chapters, we'll explore how to extend `HorizontalPodAutoscaler` to use a custom source of metrics. For now, we'll destroy what we created, and we'll start the next chapter fresh.

# Remove the previous resources

If you are planning to keep the cluster running, please execute the commands that follow to remove the resources we created.

```shell
# If NOT GKE or AKS

helm delete metrics-server \
    --namespace metrics

kubectl delete namespace metrics

kubectl delete ns go-demo-5
```

Otherwise, please delete the whole cluster if you created it only for the purpose of this chapter and you're not planning to dive into the next chapter right away.


In this lesson, we will first revise and test our concepts through a short quiz.

Revise and Test the Concepts

Short recap of the chapter