Azure AKS Workloads

Explore and manage the various workloads running on your Azure Kubernetes Service clusters. AKS provides a robust platform for deploying, scaling, and managing containerized applications.

Key Workload Concepts in AKS

Understanding the fundamental building blocks of your applications on AKS is crucial for efficient management and operations.

Pods

The smallest deployable units in Kubernetes, representing a single instance of a running process in your cluster.

Deployments

Declarative updates for Pods and ReplicaSets. Deployments manage the desired state of your applications.

StatefulSets

Manages stateful applications, providing unique network identifiers, persistent storage, and ordered deployment/scaling.

ReplicaSets

Ensures a specified number of pod replicas are running at any given time. Often managed by Deployments.

Services

Abstracts away the underlying Pods, providing a stable IP address and DNS name for accessing your application components.

DaemonSets

Ensures that all (or some) Nodes run a copy of a Pod. Useful for cluster services like log collection or node monitoring.

Managing Workloads

You can manage your AKS workloads using various tools, including the Azure portal, Azure CLI, kubectl, and Helm.

Deploying a Sample Application

Here's a simplified example of a Kubernetes Deployment manifest in YAML:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: nginx-deployment
  labels:
    app: nginx
spec:
  replicas: 3
  selector:
    matchLabels:
      app: nginx
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx:latest
        ports:
        - containerPort: 80
            

To apply this, save it as nginx-deployment.yaml and run: kubectl apply -f nginx-deployment.yaml

Key Considerations

Resource Requests and Limits: Define CPU and memory requirements for your containers to ensure optimal resource utilization and prevent node instability.
Health Probes: Implement liveness and readiness probes to allow Kubernetes to automatically manage pod health and traffic routing.
Autoscaling: Configure Horizontal Pod Autoscaler (HPA) to automatically scale your application based on metrics like CPU or custom metrics.
Rolling Updates and Rollbacks: Leverage Deployments for seamless application updates with zero downtime and the ability to roll back to previous versions if issues arise.
Namespaces: Organize your cluster resources into logical groups using namespaces to improve management and isolation.

Next Steps

Dive deeper into specific workload types or explore how to integrate with other Azure services.

Azure Kubernetes Service (AKS) Workloads