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)

[k8s-ci-robot]

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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.

[k8s-ci-robot]

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: 0x-auth, ahmetb

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[omerXfaruq]

@0x-auth it seems some time has passed, are you still interested in pursuing this PR?

[kubernetes-prow]

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: 0x-auth, ahmetb

The full list of commands accepted by this bot can be found here.

The pull request process is described here

Details

Needs approval from an approver in each of these files:

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Approvers can indicate their approval by writing /approve in a comment
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[0x-auth]

Hi @omerXfaruq, yes - still very much interested, apologies for the long silence (had some personal matters to deal with).

I will get the CLA signed immediately via the EasyCLA link.

To address the overlap question raised earlier by @ahmetb - lambda-g is meaningfully different from resource-capacity, view-utilization, view-allocations, and popeye:

• Those plugins report what resources are used or allocated - they output utilization percentages, request/limit ratios, and flag misconfigurations.
• lambda-g computes a structural imbalance score across 6 dimensions simultaneously (CPU, memory, pods, storage, network, GPU) using a symmetry-based model. The output is not a utilization table - it is a ranked list of nodes where resource distribution is asymmetric relative to the cluster's expected equilibrium. The goal is to surface nodes that are candidates for rescheduling before they become a problem, not to report what is currently used.

The closest analogue would be a center-of-mass calculation for your cluster - resource-capacity shows you the weight on each scale, lambda-g tells you whether the scales are balanced.

Happy to clarify further or make any manifest changes needed. Thanks for keeping the PR open.

[ahmetb]

Given the differences are sufficient to warrant a new plugin, I'm happy to accept it. Please look at the failing validation.

[kubernetes-prow]

New changes are detected. LGTM label has been removed.

[0x-auth]

Hi @ahmetb — sorry for the extra push. Had to force-push to add GPG signatures to the commits (krew requires verified signatures). The lgtm label was dropped as a result. Could you re-run /lgtm when you get a chance? CI is green. Thank you!