Delve into advanced Kubernetes features like monitoring, alerting, logging, and auto-scaling. Gain insights into creating resilient, self-adaptive clusters and applications with minimal manual intervention.

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.

Advanced Kubernetes Techniques: Monitoring, Logging, Auto-Scaling

I don't believe that we need many other examples of instrumented metrics. They are not any different than those we are collecting through exporters. I'll leave it up to you to start instrumenting your applications. Start small, see what works well, improve and extend.

# Remove the previous resources

Yet another chapter is finished. Destroy your cluster and start the next one fresh, or keep it. If you choose the latter, please execute the commands that follow to remove the *go-demo-5* application.

```shell
helm delete go-demo-5 \
    --namespace go-demo-5

kubectl delete ns go-demo-5
```

In this lesson, we will revise and test the concepts we have learned in this chapter through a small quiz.

Before Getting Started

Autoscaling Deployments and StatefulSets

Auto-Scaling Nodes Of A Kubernetes Cluster

Collecting and Querying Metrics and Sending Alerts

Debugging Issues Discovered Through Metrics and Alerts

Extending HorizontalPodAutoscaler With Custom Metrics

Visualizing Metrics And Alerts

Collecting And Querying Logs

Conclusion

Revise and Test the Concepts