kubernetes-deployment

Kubernetes deployment workflow for container orchestration, Helm charts, service mesh, and production-ready K8s configurations.

31,355 stars
Complexity: medium

About this skill

This AI agent skill provides a comprehensive, multi-phase workflow for automating the deployment of applications to Kubernetes clusters. It covers critical aspects of modern container orchestration, including intelligent container preparation leveraging prerequisite skills like `docker-expert`, automated Helm chart generation for standardized and repeatable deployments, and meticulous configuration of service meshes (e.g., Istio, Linkerd) to manage traffic, security, and observability. Furthermore, the skill incorporates production-ready Kubernetes patterns, ensuring robust networking configurations, strong security policies, and optimized resource management. It streamlines the path to reliable, scalable, and secure application deployments by guiding the AI agent through each necessary step from containerization to full cluster integration.

Best use case

Automating the deployment of containerized applications to Kubernetes, standardizing Helm chart creation across projects, configuring service mesh capabilities for microservices, and ensuring K8s deployments adhere to production-grade security and networking best practices.

Kubernetes deployment workflow for container orchestration, Helm charts, service mesh, and production-ready K8s configurations.

A successfully deployed application on a Kubernetes cluster, packaged with a generated Helm chart, with its service mesh fully configured, and adhering to specified production-ready K8s networking and security patterns. The agent will confirm the deployment status and provide relevant details.

Practical example

Example input

Deploy the 'user-management-api' application to our 'production-eu' Kubernetes cluster. The Docker image is `myregistry.com/org/user-management-api:v2.1.0`. Generate a new Helm chart for it, ensuring high availability with 3 replicas, and configure it to integrate with the existing Istio service mesh for mutual TLS and traffic routing.

Example output

```json
{
  "status": "success",
  "message": "Application 'user-management-api' successfully deployed to 'production-eu' cluster.",
  "details": {
    "application_name": "user-management-api",
    "cluster_name": "production-eu",
    "docker_image": "myregistry.com/org/user-management-api:v2.1.0",
    "helm_chart_generated": "user-management-api-2.1.0.tgz",
    "helm_release_name": "user-management-api-prod",
    "kubernetes_namespace": "user-management",
    "replicas_configured": 3,
    "service_mesh_configured": "Istio (mTLS enabled, traffic rules applied)",
    "deployment_url": "https://k8s-dashboard.prod-eu.example.com/deployments/user-management-api-prod",
    "k8s_manifests_storage": "s3://k8s-configs/user-management-api/v2.1.0/manifests.zip",
    "next_steps": "Verify health checks and monitor service logs via Prometheus/Grafana."
  }
}
```

When to use this skill

  • When deploying new applications or updates to a Kubernetes cluster.
  • When generating or updating Helm charts for application packaging and deployment.
  • When configuring or modifying service mesh settings (e.g., Istio, Linkerd) for traffic management, observability, or security.
  • When setting up or verifying Kubernetes networking configurations.

When not to use this skill

  • When deploying applications to non-Kubernetes environments (e.g., bare metal, serverless, traditional VMs).
  • For very simple, local deployments where advanced container orchestration, Helm, or service mesh are not required.
  • When you need to perform actions *outside* the scope of Kubernetes deployment (e.g., source code analysis, database administration).

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/kubernetes-deployment/SKILL.md --create-dirs "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/kubernetes-deployment/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/kubernetes-deployment/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How kubernetes-deployment Compares

Feature / Agentkubernetes-deploymentStandard Approach
Platform SupportClaudeLimited / Varies
Context Awareness High Baseline
Installation ComplexitymediumN/A

Frequently Asked Questions

What does this skill do?

Kubernetes deployment workflow for container orchestration, Helm charts, service mesh, and production-ready K8s configurations.

Which AI agents support this skill?

This skill is designed for Claude.

How difficult is it to install?

The installation complexity is rated as medium. You can find the installation instructions above.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Kubernetes Deployment Workflow

## Overview

Specialized workflow for deploying applications to Kubernetes including container orchestration, Helm charts, service mesh configuration, and production-ready K8s patterns.

## When to Use This Workflow

Use this workflow when:
- Deploying to Kubernetes
- Creating Helm charts
- Configuring service mesh
- Setting up K8s networking
- Implementing K8s security

## Workflow Phases

### Phase 1: Container Preparation

#### Skills to Invoke
- `docker-expert` - Docker containerization
- `k8s-manifest-generator` - K8s manifests

#### Actions
1. Create Dockerfile
2. Build container image
3. Optimize image size
4. Push to registry
5. Test container

#### Copy-Paste Prompts
```
Use @docker-expert to containerize application for K8s
```

### Phase 2: K8s Manifests

#### Skills to Invoke
- `k8s-manifest-generator` - Manifest generation
- `kubernetes-architect` - K8s architecture

#### Actions
1. Create Deployment
2. Configure Service
3. Set up ConfigMap
4. Create Secrets
5. Add Ingress

#### Copy-Paste Prompts
```
Use @k8s-manifest-generator to create K8s manifests
```

### Phase 3: Helm Chart

#### Skills to Invoke
- `helm-chart-scaffolding` - Helm charts

#### Actions
1. Create chart structure
2. Define values.yaml
3. Add templates
4. Configure dependencies
5. Test chart

#### Copy-Paste Prompts
```
Use @helm-chart-scaffolding to create Helm chart
```

### Phase 4: Service Mesh

#### Skills to Invoke
- `istio-traffic-management` - Istio
- `linkerd-patterns` - Linkerd
- `service-mesh-expert` - Service mesh

#### Actions
1. Choose service mesh
2. Install mesh
3. Configure traffic management
4. Set up mTLS
5. Add observability

#### Copy-Paste Prompts
```
Use @istio-traffic-management to configure Istio
```

### Phase 5: Security

#### Skills to Invoke
- `k8s-security-policies` - K8s security
- `mtls-configuration` - mTLS

#### Actions
1. Configure RBAC
2. Set up NetworkPolicy
3. Enable PodSecurity
4. Configure secrets
5. Implement mTLS

#### Copy-Paste Prompts
```
Use @k8s-security-policies to secure Kubernetes cluster
```

### Phase 6: Observability

#### Skills to Invoke
- `grafana-dashboards` - Grafana
- `prometheus-configuration` - Prometheus

#### Actions
1. Install monitoring stack
2. Configure Prometheus
3. Create Grafana dashboards
4. Set up alerts
5. Add distributed tracing

#### Copy-Paste Prompts
```
Use @prometheus-configuration to set up K8s monitoring
```

### Phase 7: Deployment

#### Skills to Invoke
- `deployment-engineer` - Deployment
- `gitops-workflow` - GitOps

#### Actions
1. Configure CI/CD
2. Set up GitOps
3. Deploy to cluster
4. Verify deployment
5. Monitor rollout

#### Copy-Paste Prompts
```
Use @gitops-workflow to implement GitOps deployment
```

## Quality Gates

- [ ] Containers working
- [ ] Manifests valid
- [ ] Helm chart installs
- [ ] Security configured
- [ ] Monitoring active
- [ ] Deployment successful

## Related Workflow Bundles

- `cloud-devops` - Cloud/DevOps
- `terraform-infrastructure` - Infrastructure
- `docker-containerization` - Containers

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