Automated Placement  is the core function of the Kubernetes scheduler for assigning new Pods to nodes satisfying container resource requests and honoring scheduling policies. This pattern describes the principles of Kubernetes’ scheduling algorithm and the way to influence the placement decisions from the outside. A reasonably sized microservices-based system consists of tens or even hundreds of isolated processes. Containers and Pods do provide nice abstractions for packaging and deployment but do not solve the problem of placing these processes on suitable nodes. With a large and ever-growing number of microservices, assigning and plac‐ ing them individually to nodes is not a manageable activity. Containers have dependencies among themselves, dependencies to nodes, and resource demands, and all of that changes over time too. The resources available on a cluster also vary over time, through shrinking or extending the cluster, or by having it consumed by already placed containers. The way we place containers impacts the availability, performance, and capacity of the distributed systems as well. All of that makes scheduling containers to nodes a moving target that has to be shot on the move. In Kubernetes, assigning Pods to nodes is done by the scheduler. It is an area that is highly configurable, still evolving, and changing rapidly as of this writing. In this chapter, we cover the main scheduling control mechanisms, driving forces that affect the placement, why to choose one or the other option, and the resulting conse‐ quences. The Kubernetes scheduler is a potent and time-saving tool. It plays a funda‐ 47 Problem Solution CHAPTER 6 Automated Placement