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k8s-deploy

k8s-deploy provides deployment workflows for Kubernetes using kubectl-mcp-server tools, supporting standard deployments via manifests or Helm alongside progressive delivery through Argo Rollouts and Flagger. It covers canary promotions, blue-green strategies, rolling updates, scaling, and rollback operations across single and multi-cluster environments.

k8s-deploy handles Kubernetes workload deployments using progressive delivery strategies like canary and blue-green releases.

AI-generated summary based on this skill's SKILL.md

934 177 MITupdated by rohitg00

Decision gist · record as of 2026-04-08

k8s-deploy handles Kubernetes workload deployments using progressive delivery strategies like canary and blue-green releases. k8s-deploy provides deployment workflows for Kubernetes using kubectl-mcp-server tools, supporting standard deployments via manifests or Helm alongside progressive delivery through Argo Rollouts and Flagger. It covers canary promotions, blue-green strategies, rolling updates, scaling, and rollback operations across single and multi-cluster environments.

manual: git clone https://github.com/rohitg00/kubectl-mcp-server → cp -r kubectl-mcp-server/kubernetes-skills/claude/k8s-deploy ~/.claude/skills/k8s-deploy
kubernetes-skills/claude/k8s-deploy/SKILL.md · version 0e04f83a

Use it when

  • k8s-deploy enables canary and blue-green deployments through Argo Rollouts integration.
  • Yes, k8s-deploy supports multi-cluster Kubernetes deployments.

Verify before relying

Read SKILL.md below before installing (6 files). Open directory: indexed for reading, not audited.

Same gist for agents: .md · .json

Install

rohitg00/kubectl-mcp-server/k8s-deploy · repository language: Python

Open directory. Skills are indexed for reading, not audited. Review a skill's body before installing it.

Frequently asked questions

AI-generated answers based on this skill's SKILL.md and metadata

What deployment strategies does k8s-deploy support?

k8s-deploy supports multiple Kubernetes deployment strategies including standard deployments via manifests or Helm, progressive delivery through Argo Rollouts and Flagger, canary promotions, blue-green strategies, and rolling updates. These approaches enable safe, controlled rollouts with health verification and rollback capabilities.

How can I execute canary and blue-green deployments using k8s-deploy?

k8s-deploy enables canary and blue-green deployments through Argo Rollouts integration. You can configure progressive delivery strategies that gradually shift traffic between versions, monitor rollout health in real time, and automatically rollback if issues are detected. This ensures zero-downtime releases with minimal risk.

Can k8s-deploy deploy applications across multiple Kubernetes clusters?

Yes, k8s-deploy supports multi-cluster Kubernetes deployments. You can manage workloads across multiple cluster environments, enabling distributed application delivery and cluster-spanning release management strategies.

What should I do if a kubernetes deployment needs to be rolled back?

k8s-deploy provides rollback operations to safely revert failed deployments. You can abort failed rollouts and return to previous stable versions. The skill includes rollout status checking to verify deployment health and detect issues requiring rollback.

How does k8s-deploy handle scaling and updating Kubernetes pods?

k8s-deploy enables safe pod scaling and image updates through its deployment management capabilities. Combined with progressive delivery strategies, you can scale workloads and update container images while maintaining service availability and monitoring rollout progress.

What tools does k8s-deploy use for Kubernetes deployment workflows?

k8s-deploy leverages kubectl-mcp-server tools for deployment workflows, supporting manifest-based deployments, Helm chart deployments, and progressive delivery via Argo Rollouts and Flagger. It provides comprehensive release management across single and multi-cluster Kubernetes environments.

SKILL.md

Rendered from the published skill. Quoted content, verbatim.

Kubernetes Deployment Workflows

Comprehensive deployment strategies using kubectl-mcp-server tools, including Argo Rollouts and Flagger for progressive delivery.

When to Apply

Use this skill when: - User mentions: "deploy", "release", "rollout", "scale", "update", "upgrade" - Operations: creating deployments, updating images, scaling replicas - Strategies: canary, blue-green, rolling update, recreate - Keywords: "new version", "push to production", "traffic shifting"

Priority Rules

Priority Rule Impact Tools
1 Preview with template before apply CRITICAL template_helm_chart
2 Check existing state first CRITICAL get_pods, list_helm_releases
3 Use progressive delivery for prod HIGH rollout_* tools
4 Verify health after deployment HIGH get_pod_metrics, get_endpoints
5 Keep

(truncated - see the full file via the links below)

File tree — 6 files
kubernetes-skills/claude/k8s-deploy/ROLLOUTS.md
kubernetes-skills/claude/k8s-deploy/SKILL.md
kubernetes-skills/claude/k8s-deploy/examples/blue-green.yaml
kubernetes-skills/claude/k8s-deploy/examples/canary-rollout.yaml
kubernetes-skills/claude/k8s-deploy/examples/hpa-deployment.yaml
kubernetes-skills/claude/k8s-deploy/references/STRATEGIES.md

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Tags
progressive-deliveryrelease-strategytraffic-shiftingdeployment-automationzero-downtimemulti-clusterworkload-managementhealth-verificationrollback-recovery