Kubernetes API caching layer according to Stable Diffusion

Make it faster!

There are use cases that put the Kubernetes API under heavy load - using Rancher at scale can be one of them.

Also, there are use cases in which a connection to the Kubernetes API might not always be present, or with good bandwidth - using Rancher for edge use cases can be one of them.

This project aims to create a local cache serving data from the Kubernetes API - with good performance and displaying last-good-results on a flaky connection.

Goal for this Hackweek

Implement Proof-Of-Concept client-go components backed by SQLite.

https://github.com/moio/vai

Resources

Golang and ideally Kubernetes hackers are more than welcome!

Looking for hackers with the skills:

kubernetes k8s api golang go performance testautomation scalability

This project is part of:

Hack Week 22

Activity

  • almost 3 years ago: lizhang liked this project.
  • almost 3 years ago: moio added keyword "k8s" to this project.
  • almost 3 years ago: moio added keyword "api" to this project.
  • almost 3 years ago: moio added keyword "golang" to this project.
  • almost 3 years ago: moio added keyword "go" to this project.
  • almost 3 years ago: moio added keyword "performance" to this project.
  • almost 3 years ago: moio added keyword "testautomation" to this project.
  • almost 3 years ago: moio added keyword "scalability" to this project.
  • almost 3 years ago: moio added keyword "kubernetes" to this project.
  • almost 3 years ago: moio liked this project.
  • almost 3 years ago: paulgonin liked this project.
  • almost 3 years ago: moio started this project.
  • almost 3 years ago: moio originated this project.

  • Comments

    • moio
      almost 3 years ago by moio | Reply

      Day 1 question: is a separate daemon design better than creating an Informer backed by a SQL cache.Store?

    • moio
      almost 3 years ago by moio | Reply

      Day 1 answer: no. Pivoting project to the creation of a SQL-based Indexer

    • moio
      almost 3 years ago by moio | Reply

      Day 2 progress: SQL-backed Store works. https://github.com/moio/vai

    • moio
      almost 3 years ago by moio | Reply

      Day 3 progress: SQL-backed Indexer works

    • moio
      almost 3 years ago by moio | Reply

      Day 4 question: where would it fit best? Steve or Lasso, and where?

    • moio
      almost 3 years ago by moio | Reply

      Day 4 answer: Steve, as an alternative to the current LRU cache of k8s API responses

    • moio
      almost 3 years ago by moio | Reply

      Day 5 progress: SQL-backed ThreadSafeStore works. History-preserving VersionedStore also works

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              -0     [005] d..2. 20310.270702: sched_switch:         swapper/5:0 [120] R ==> WaylandProxy:46380 [120]
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    4. Benchmark: Create a benchmarking script (e.g., using k6, ab, or a custom tool) that simulates the high-concurrency registration load from thousands of clients.
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    Resources

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      • https://github.com/SUSE/rmt
    • RMT Documentation:
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      • Rust development environment (rustup, cargo)
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      • Magnus: https://github.com/matsadler/magnus
    • Benchmarking Tools:
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      • ab (ApacheBench)


    RMT.rs: High-Performance Registration Path for RMT using Rust by gbasso

    Description

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    • Potential Integration Libraries:
      • rb-sys: https://github.com/oxidize-rb/rb-sys
      • Magnus: https://github.com/matsadler/magnus
    • Benchmarking Tools:
      • k6 (https://k6.io/)
      • ab (ApacheBench)