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Automated management of containerized applications

Core Idea: Container orchestration is the automated configuration, coordination, and management of containerized applications and the underlying infrastructure, handling deployment, scaling, networking, and availability.

Key Elements

Key Features

• Automated container deployment
• Service discovery and load balancing
• Horizontal scaling
• Self-healing capabilities
• Configuration management
• Storage orchestration
• Secret and configuration management
• Rolling updates and rollbacks

Major Orchestration Platforms

• Kubernetes: The dominant open-source container orchestration platform
• Docker Swarm: Native Docker orchestration, simpler than Kubernetes
• Amazon ECS: AWS's container management service
• Azure Kubernetes Service (AKS): Microsoft's managed Kubernetes
• Google Kubernetes Engine (GKE): Google's managed Kubernetes service
• Red Hat OpenShift: Enterprise Kubernetes platform with additional features
• Nomad: HashiCorp's workload orchestrator (supports containers and non-containers)

Core Concepts

• Containers: Packaged applications with dependencies
• Pods (in Kubernetes): Groups of containers deployed together
• Services: Abstraction to expose applications
• Volumes: Persistent storage for containers
• Networking: Inter-container and external communication
• Load Balancing: Distribution of traffic
• Health Checks: Monitoring container health
• Scheduling: Placement decisions for containers

Implementation Example

Kubernetes deployment example (deployment.yaml):

apiVersion: apps/v1
kind: Deployment
metadata:
  name: web-application
  labels:
    app: web
spec:
  replicas: 3
  selector:
    matchLabels:
      app: web
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  template:
    metadata:
      labels:
        app: web
    spec:
      containers:
      - name: web-container
        image: nginx:1.21
        ports:
        - containerPort: 80
        resources:
          limits:
            cpu: "500m"
            memory: "512Mi"
          requests:
            cpu: "200m"
            memory: "256Mi"
        livenessProbe:
          httpGet:
            path: /health
            port: 80
          initialDelaySeconds: 3
          periodSeconds: 10
        volumeMounts:
        - name: config-volume
          mountPath: /etc/nginx/conf.d/
      volumes:
      - name: config-volume
        configMap:
          name: nginx-config

Deployment Strategies

• Rolling Updates: Gradually replace old instances with new ones
• Blue/Green Deployment: Maintain two identical environments
• Canary Releases: Route a percentage of traffic to new version
• A/B Testing: Compare different versions simultaneously
• Shadow Deployment: Test new version with production traffic without affecting users

Networking Models

• Overlay Networks: Create virtual networks spanning multiple hosts
• Container Network Interface (CNI): Kubernetes networking standard
• Service Discovery: Automatic detection of available services
• Ingress Controllers: Managing external access to services
• Network Policies: Controlling traffic between pods

Additional Connections

• Broader Context: Cloud Native Architecture, DevOps Practices
• Applications: Microservices Deployment, Continuous Deployment
• See Also: Docker, Kubernetes, Service Mesh

References

1. "Kubernetes: Up and Running" by Brendan Burns, Joe Beda, and Kelsey Hightower
2. "Docker in Action" by Jeff Nickoloff and Stephen Kuenzli

#containers #orchestration #kubernetes #devops #cloud-native

Connections:

Sources:

• From: Worklog n8n