/kubernetes-deployment
Deploy, manage, and scale containerized applications on Kubernetes clusters with best practices for production workloads, resource management, and rolling updates.
$ npx -y skills add aj-geddes/useful-ai-prompts --skill kubernetes-deployment --agent claude-codeHow it fires
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- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/kubernetes-deployment
Context preview
The summary Claude sees to decide when to auto-load this skill.
Deploy, manage, and scale containerized applications on Kubernetes clusters with best practices for production workloads, resource management, and rolling updates.
SKILL.md
kubernetes-deployment.SKILL.mdname: kubernetes-deployment
description: >
Deploy, manage, and scale containerized applications on Kubernetes clusters
with best practices for production workloads, resource management, and rolling
updates.
Kubernetes Deployment
Table of Contents
- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#best-practices)
Overview
Master Kubernetes deployments for managing containerized applications at scale, including multi-container services, resource allocation, health checks, and rolling deployment strategies.
When to Use
- Container orchestration and management
- Multi-environment deployments (dev, staging, prod)
- Auto-scaling microservices
- Rolling updates and blue-green deployments
- Service discovery and load balancing
- Resource quota and limit management
- Pod networking and security policies
Quick Start
Minimal working example:
# kubernetes-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: api-service
namespace: production
labels:
app: api-service
version: v1
spec:
replicas: 3
strategy:
type: RollingUpdate
rollingUpdate:
maxSurge: 1
maxUnavailable: 0
selector:
matchLabels:
app: api-service
template:
metadata:
labels:
app: api-service
version: v1
annotations:
// ... (see reference guides for full implementation)Reference Guides
Detailed implementations in the `references/` directory:
| Guide | Contents | |---|---| | [Complete Deployment with Resource Management](references/complete-deployment-with-resource-management.md) | Complete Deployment with Resource Management | | [Deployment Script](references/deployment-script.md) | Deployment Script | | [Service Account and RBAC](references/service-account-and-rbac.md) | Service Account and RBAC |
Best Practices
✅ DO
- Use resource requests and limits
- Implement health checks (liveness, readiness)
- Use ConfigMaps for configuration
- Apply security context restrictions
- Use service accounts and RBAC
- Implement pod anti-affinity
- Use namespaces for isolation
- Enable pod security policies
❌ DON'T
- Use latest image tags in production
- Run containers as root
- Set unlimited resource usage
- Skip readiness probes
- Deploy without resource limits
- Mix configurations in container images
- Use default service accounts
Read more
name: kubernetes-deployment description: > Deploy, manage, and scale containerized applications on Kubernetes clusters with best practices for production workloads, resource management, and rolling updates.
Kubernetes Deployment
Table of Contents
- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#best-practices)
Overview
Master Kubernetes deployments for managing containerized applications at scale, including multi-container services, resource allocation, health checks, and rolling deployment strategies.
When to Use
- Container orchestration and management
- Multi-environment deployments (dev, staging, prod)
- Auto-scaling microservices
- Rolling updates and blue-green deployments
- Service discovery and load balancing
- Resource quota and limit management
- Pod networking and security policies
Quick Start
Minimal working example:
# kubernetes-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: api-service
namespace: production
labels:
app: api-service
version: v1
spec:
replicas: 3
strategy:
type: RollingUpdate
rollingUpdate:
maxSurge: 1
maxUnavailable: 0
selector:
matchLabels:
app: api-service
template:
metadata:
labels:
app: api-service
version: v1
annotations:
// ... (see reference guides for full implementation)Reference Guides
Detailed implementations in the `references/` directory:
| Guide | Contents | |---|---| | [Complete Deployment with Resource Management](references/complete-deployment-with-resource-management.md) | Complete Deployment with Resource Management | | [Deployment Script](references/deployment-script.md) | Deployment Script | | [Service Account and RBAC](references/service-account-and-rbac.md) | Service Account and RBAC |
Best Practices
✅ DO
- Use resource requests and limits
- Implement health checks (liveness, readiness)
- Use ConfigMaps for configuration
- Apply security context restrictions
- Use service accounts and RBAC
- Implement pod anti-affinity
- Use namespaces for isolation
- Enable pod security policies
❌ DON'T
- Use latest image tags in production
- Run containers as root
- Set unlimited resource usage
- Skip readiness probes
- Deploy without resource limits
- Mix configurations in container images
- Use default service accounts
488 production-ready AI prompts, all following a standardized template with validated quality gates. Transform ChatGPT, Claude, and other AI assistants into expert consultants.
Repo: aj-geddes/useful-ai-prompts
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