kubernetes-orchestration
Kubernetes deployment and orchestration patterns
Works with
---
name: kubernetes-orchestration
description: Kubernetes deployment and orchestration patterns
license: MIT
---
# Kubernetes Orchestration
Best practices for Kubernetes deployments and operations.
## When to Use
- Deploying applications to Kubernetes
- Writing or reviewing K8s manifests
- Setting up clusters and workloads
## Core Concepts
### Deployment
```yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: app
spec:
replicas: 3
selector:
matchLabels:
app: myapp
template:
metadata:
labels:
app: myapp
spec:
containers:
- name: app
image: myapp:1.0.0
ports:
- containerPort: 8080
resources:
requests:
memory: "128Mi"
cpu: "100m"
limits:
memory: "256Mi"
cpu: "200m"
livenessProbe:
httpGet:
path: /health
port: 8080
initialDelaySeconds: 30
periodSeconds: 10
```
### Service
```yaml
apiVersion: v1
kind: Service
metadata:
name: app-service
spec:
selector:
app: myapp
ports:
- port: 80
targetPort: 8080
type: ClusterIP
```
### ConfigMap & Secrets
```yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: app-config
data:
LOG_LEVEL: "info"
MAX_CONNECTIONS: "100"
---
apiVersion: v1
kind: Secret
metadata:
name: app-secret
type: Opaque
stringData:
DATABASE_URL: "postgresql://user:pass@db:5432/app"
```
## Best Practices
- Use labels consistently
- Set resource requests and limits
- Implement health checks (liveness, readiness, startup probes)
- Use ConfigMaps and Secrets for configuration
- Implement horizontal pod autoscaling (HPA)
- Use namespaces for environment separation
## Resources
- [Kubernetes Docs](https://kubernetes.io/docs/)
- [Kubernetes Best Practices](https://kubernetes.io/docs/concepts/configuration/overview/)More Deployment & CI/CD skills
azure-enterprise-infra-planner
microsoft/azure-skills
Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.
azure-kubernetes-app-deploy
microsoft/azure-skills
Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.
finetuning
microsoft/azure-skills
Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).

