In this chapter, we've covered many topics relating to scaling Kubernetes clusters. We discussed how the horizontal pod autoscaler can automatically manage the number of running pods-based CPU utilization or other metrics, how to perform rolling updates correctly and safely in the context of auto-scaling, and how to handle scarce resources via resource quotas. Then we moved on to overall capacity planning and management of the cluster's physical or virtual resources. Finally, we delved into a real-world example of scaling a single Kubernetes cluster to handle 5,000 nodes.
At this point, you have a good understanding of all the factors that come into play when a Kubernetes cluster is facing dynamic and growing workloads. You have multiple tools to choose from for planning and designing your own scaling strategy.
In the next chapter, we will dive into advanced...
