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Authors: Rashmi Gottipati, Varsha Prasad Narsing, Tony J, Bryce Palmer, Camila Macedo
2023-04-19

tldr - powered by Generative AI

Phase 2 plugins in Cube Builder and Operator SDK allow for extensible CLI and scaffolding through external plugins
  • Cube Builder simplifies building a Kubernetes operator and allows for extensible CLI and scaffolding through plugins
  • Phase 2 plugins allow for external plugins to be discovered and used without needing to be compiled with the Cube Builder binary
  • Plugins can modify Cube Builder's base scaffolding before files are written to disk
  • Plugins can be written in any language
  • External plugins allow for customization of Cube Builder's workflow for non-GoLang operators
Authors: Amine Hilaly, Scott Rigby, Niki Manoledaki, Somtochi Onyekwere, Soulé Ba
2022-10-26

Kubernetes controllers are responsible for making the current state of your cluster continue to become closer to your desired state. Have you ever wondered how these built-in controllers work? Or have you ever wanted to write your own controller to manage Custom Resources? In this 90 minute tutorial, we'll walk you through building your own controller using controller runtime, the set of common libraries on which core controllers are built. We'll use Kubebuilder, a framework for building APIs using custom resource definitions (CRDs). We'll also explain lesser-documented best practices and conventions for writing controllers that the community has developed through trial and error learning, through projects such as Flux and Cluster API. Attendees will gain an understanding of what Kubernetes conditions are, how to set and respond to them, and why they matter. We’ll review common pitfalls and additional helper libraries to make writing these easier, more reliable, and enjoyable!
Authors: Jay Pipes, Amine Hilaly
2022-10-26

tldr - powered by Generative AI

Building a controller factory with code generation tools and automation to keep controllers up to date with evolving API schemas
  • Developers still have a lot of logic to write and implement despite having great tooling
  • Building a controller factory with code generation tools and automation was necessary to avoid manually maintaining and developing artifacts for 200+ AWS services
  • APIs evolve over time and integrating changes to upstream service APIs in a smooth and consistent fashion was a challenge
  • The controller factory takes AWS API models and a generator.yaml configuration file as inputs to generate a full controller implementation
  • Centralizing code through co-generation from a model definition removes a whole classification of common failures and bugs
Authors: Michael Hrivnak, Austin Macdonald
2022-10-26

tldr - powered by Generative AI

Lessons learned in designing and implementing operators for Kubernetes
  • API anti-patterns to avoid in operator design
  • Challenges in bridging the gap between imperative infrastructure management and declarative Kubernetes API
  • Maximizing usefulness of client's cache and avoiding memory bloat
  • Efficiently interacting with multiple clusters from a single operator instance
  • Minimizing load imposed on the API server