Application scheduling

Now that we understand how to run containers in pods and even recover from failure, it may be useful to understand how new containers are scheduled on our cluster nodes.

As mentioned earlier, the default behavior for the Kubernetes scheduler is to spread container replicas across the nodes in our cluster. In the absence of all other constraints, the scheduler will place new pods on nodes with the least number of other pods belonging to matching services or replication controllers.

Additionally, the scheduler provides the ability to add constraints based on resources available to the node. Today, this includes minimum CPU and memory allocations. In terms of Docker, these use the CPU-shares and memory limit flags under the covers.

When additional constraints are defined, Kubernetes will check a node for available resources. If a node does not meet all the constraints, it will move to the next. If no nodes can be found that meet the criteria, then we will see a scheduling error in the logs.

The Kubernetes roadmap also has plans to support networking and storage. Because scheduling is such an important piece of overall operations and management for containers, we should expect to see many additions in this area as the project grows.