kubernetes-deployment-patterns

Kubernetes Deployment Patterns

Expert guidance for production-grade Kubernetes deployments covering deployment strategies, workload types, configuration management, resource optimization, and autoscaling patterns for cloud-native applications.

When to Use This Skill

• Implementing deployment strategies (rolling updates, blue-green, canary releases)
• Choosing appropriate workload types (Deployment, StatefulSet, DaemonSet, Job)
• Designing rollout strategies for zero-downtime deployments
• Implementing configuration management with ConfigMaps and Secrets
• Setting up resource management and autoscaling (HPA, VPA)
• Configuring health checks and probe strategies
• Designing highly available applications on Kubernetes
• Implementing batch processing and scheduled jobs

Core Concepts

Deployment Strategies

Rolling Update: Gradually replace old pods with new ones (zero-downtime, default) Recreate: Terminate all old pods before creating new ones (brief downtime) Blue-Green: Run two environments, switch traffic instantly (2x resources) Canary: Gradually shift traffic to new version while monitoring (risk mitigation)

Workload Types

Deployment: Stateless applications (web servers, APIs, microservices) StatefulSet: Stateful applications (databases, message queues) DaemonSet: Node-level services (log collectors, monitoring agents) Job: One-time tasks (batch processing, migrations) CronJob: Scheduled tasks (backups, periodic reports)

Resource Management

Requests: Guaranteed resources for scheduling Limits: Maximum resources enforced by kubelet HPA: Horizontal Pod Autoscaler (scale replicas based on metrics) VPA: Vertical Pod Autoscaler (adjust resource requests/limits)

Quick Reference

Task	Load reference
Deployment strategies (rolling, blue-green, canary)	skills/kubernetes-deployment-patterns/references/deployment-strategies.md
Workload types (Deployment, StatefulSet, DaemonSet, Job)	skills/kubernetes-deployment-patterns/references/workload-types.md
Configuration management (ConfigMaps, Secrets)	skills/kubernetes-deployment-patterns/references/configuration-management.md
Resource management and autoscaling (HPA, VPA)	skills/kubernetes-deployment-patterns/references/resource-management.md
Production best practices and security	skills/kubernetes-deployment-patterns/references/production-best-practices.md

Workflow

1. Choose Deployment Strategy

# Rolling update for standard deployments
strategy:
  type: RollingUpdate
  rollingUpdate:
    maxSurge: 1
    maxUnavailable: 0

# Recreate for incompatible versions
strategy:
  type: Recreate

2. Select Workload Type

• Stateless? → Use Deployment
• Stateful with persistent identity? → Use StatefulSet
• One pod per node? → Use DaemonSet
• Run to completion? → Use Job
• Run on schedule? → Use CronJob

3. Configure Resources

resources:
  requests:
    memory: "256Mi"
    cpu: "250m"
  limits:
    memory: "512Mi"
    cpu: "1000m"

4. Add Configuration

# ConfigMap for non-sensitive config
envFrom:
- configMapRef:
    name: app-config

# Secret for sensitive data
env:
- name: DB_PASSWORD
  valueFrom:
    secretKeyRef:
      name: db-credentials
      key: password

5. Implement Health Checks

livenessProbe:
  httpGet:
    path: /healthz
    port: 8080
  initialDelaySeconds: 30
  periodSeconds: 10

readinessProbe:
  httpGet:
    path: /ready
    port: 8080
  initialDelaySeconds: 5
  periodSeconds: 5

6. Enable Autoscaling

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
spec:
  scaleTargetRef:
    kind: Deployment
    name: app
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70

Common Mistakes

1. Using latest tag: Always use specific version tags for reproducibility
2. No resource limits: Can cause resource starvation and cluster instability
3. Missing health checks: Kubernetes can't manage pod health without probes
4. Single replica in production: No high availability or resilience
5. Secrets in ConfigMaps: Use Secrets for sensitive data, not ConfigMaps
6. No update strategy: Leads to unpredictable deployment behavior
7. Running as root: Security vulnerability, violates least privilege
8. No monitoring: Can't detect or debug issues in production

Resources

• Official Docs: https://kubernetes.io/docs/concepts/workloads/
• Deployment Strategies: https://kubernetes.io/docs/concepts/workloads/controllers/deployment/
• StatefulSets: https://kubernetes.io/docs/concepts/workloads/controllers/statefulset/
• Autoscaling: https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/
• Configuration: https://kubernetes.io/docs/concepts/configuration/
• Best Practices: https://kubernetes.io/docs/concepts/configuration/overview/