Add lambda-g plugin v1.0.0 — 6D K8s resource imbalance scanner

[0x-auth]

New Plugin: kubectl lambda-g

Scans your Kubernetes cluster for stranded resources across 6 dimensions: CPU, RAM, GPU Core, GPU Memory, IOPS, Network.

Detects nodes where one resource is maxed while others sit idle — the kind of cross-dimensional imbalance that kubectl top misses.

kubectl krew install lambda-g
kubectl lambda-g scan
kubectl lambda-g scan --detailed
kubectl lambda-g watch

• Self-contained Go binary, no dependencies
• All platforms: linux/darwin/windows × amd64/arm64
• Homepage: https://github.com/0x-auth/lambda-g-auditor
• Open source (MIT)

[ahmetb]

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/kind new-plugin

[linux-foundation-easycla]

The committers listed above are authorized under a signed CLA.

• ✅ login: 0x-auth / name: 0x-auth (1b8bc9b, 25cda88)
• ✅ login: ahmetb / name: Ahmet Alp Balkan (1e55b75)

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[ahmetb]

Hi @0x-auth, thanks for submitting lambda-g to the krew index!

A few things to be aware of for new plugin submissions:

• Reviews take time — we're receiving a large volume of new plugin submissions (including many "vibe coded" plugins), so initial reviews can take a while as maintainers assess fit and quality.
• Reviewers evaluate uniqueness — part of the review process is determining whether the plugin fills a gap not already covered by existing plugins in the index.
• Please don't ping reviewers directly — this index is maintained on a best-effort basis, and pinging individuals doesn't speed up the process.

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Before this proceeds further, please take a look at several existing plugins that appear to overlap with what lambda-g does:

• resource-capacity — robscott/kube-capacity: "Provides an overview of resource requests, limits, and utilization" — shows CPU and memory requests, limits, and utilization across nodes and pods.
• view-utilization — etopeter/kubectl-view-utilization: "Shows cluster cpu and memory utilization" — collects pod requests and node available resources to report utilization metrics.
• view-allocations — davidB/kubectl-view-allocations: "List allocations per resources, nodes, pods" — lists CPU, memory, and GPU allocations (requested, limit, allocatable) across nodes and pods.
• popeye — derailed/popeye: "Scans your clusters for potential resource issues" — scans live clusters for misconfigurations and resource over/under-allocation issues.

These existing plugins collectively cover CPU, memory, and GPU resource monitoring and imbalance detection. We'd encourage you to try them out and consider whether your use case (multi-dimensional imbalance detection) could instead be contributed as a feature to one of these established projects rather than introducing a new separate plugin.

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Generated by Claude Code

[0x-auth]

@ahmetb Thanks for the detailed review. I've looked at all four plugins you mentioned. The distinction is that lambda-g doesn't report utilization per resource , it detects cross-dimensional imbalance: nodes where CPU is saturated but RAM is idle, or GPU is maxed but compute is free. This is a different problem. resource-capacity and view-utilization show you numbers. lambda-g tells you which nodes are structurally misallocated across dimensions simultaneously. popeye flags misconfigurations; lambda-g flags imbalance patterns that waste budget. Happy to add a comparison table to the README if that would help

[ahmetb]

/lgtm
/approve
Thanks!
Also, please consider setting up Krew release automation which helps you skip manually making updates to your Krew manifests on each new version and send a pull request. It’s a GitHub workflow bot that can run every time you push a new tag. Those PRs are automatically approved.

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