Extending Kubernetes with Operators (sponsored by Red Hat)
Kubernetes scales and manages stateless applications quite easily—but handling complex, stateful workloads can often be a challenge. Databases, distributed caches, and file storage systems frequently include their own notions about clustering, which can turn basic management tasks like scaling or autorecovery into a difficult and complicated effort.
Operators are Kubernetes agents that include custom support for complex, stateful workload management tasks, including deployments, scaling, backups, and even upgrades. Ryan Jarvinen offers an overview of the Operator pattern, including architecture, implementation, and a few popular solutions. You’ll learn how to extend the default collection of API resources—allowing users to install and interact with these advanced, Kubernetes-aware solutions via a simple declarative interface.
With an understanding of Operators in place, you’ll go on to detail the Operator Framework and its main components: the Operator SDK and Operator Lifecycle Manager (OLM). You’ll learn how to extend Kubernetes to support your own custom workload-management strategies and tactics while establishing higher-order interfaces that represent the logical domain expertise (and perhaps the ideal product output) of a Kubernetes SRE.
This session is sponsored by Red Hat.
- Familiarity with Kubernetes
What you'll learn
- Learn about the Operator Framework
Ryan Jarvinen is a developer advocate at Red Hat, who focuses on developer experience and usability in the cloud native ecosystem. Previously, he was at CoreOS. He’s a frequent conference speaker and workshop leader who enjoys discussing distributed solutions architecture and helping teams develop strategies for maximizing their productivity using Kubernetes. He works remotely from Sacramento, CA, as a part of Red Hat’s OpenShift team; you can reach him online as RyanJ via Twitter, GitHub, or IRC.
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