Summary
To summarize, we've covered key Kubernetes components, as well as the metrics and events that can help you track their health and performance over time. We have also covered how to collect all of the metrics using built-in Kubernetes APIs and utilities, allowing you to gain comprehensive visibility into your container infrastructure and workloads.
We looked at Prometheus, Grafana, and Alertmanager as tools for setting up a monitoring and alerting stack. We've also looked at how to set up a centralized, cluster-level logging stack with the EFK toolset, which can handle massive amounts of log data. Finally, we went over the essential indicators that should be watched in order to successfully manage your infrastructure and apps.
We'll look at how to develop and deploy a machine learning model using the Kubeflow MLOps platform in the next chapter. Kubeflow and MicroK8s deliver reliable and efficient operations as well as infrastructure optimization.
