How Container Clusters Like Kubernetes Change Operations

Containers have been at the core of how many web-scale companies build their distributed systems for years. More recently containers have become an increasingly popular tool for developers everywhere. As containers are moved from a developer's workstation to production, they are generally managed by cluster management systems like Kubernetes or Omega.

These cluster management systems offer significant opportunities to improve operations across the data center. In particular, they offer the following opportunities. By separating concerns along a variety of axis (developers from managing machines, applications from the OS on which they run, etc.) container cluster management systems enable ops specialization. Different operations teams can focus on kernel and machine maintenance, cluster operations, and application operations, and they can do these jobs in relative isolation. This focus and isolation means that the teams are significantly more productive, and less likely to make mistakes due to inexperience or interactions that they don't fully understand.

Additionally, the homgenization of the container cluster, and the presence of the cluster management system, make management tools (roll outs, monitoring, health maintenance) a property of the cluster environment, not each individual application. This means that these tools are deployed once for an entire cluster, and they are designed and deployed by experts who are, again, specialized to their specific task.

Finally, container clusters and cluster management apis enable the switch to immutable infrastructure and the development of patterns that make it possible to do operations without manual manipulating individual machines.

Brendan Burns is a Staff Software Engineer at Google, Inc and a founder of the Kubernetes project. He works in the Google Cloud Platform, leading engineering efforts to make the Google Cloud Platform the best place to run containers. He also has managed several other cloud teams, including the Managed VMs team and Cloud DNS. Prior to Cloud, he was a lead engineer in Google's web search infrastructure, building backends that powered social and personal search. Prior to working at Google, he was a professor at Union College in Schenectady, NY. He received a PhD in Computer Science from the University of Massachusetts Amherst, and a BA in Computer Science and Studio Art from Williams College.