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Abraham Dahunsi Web Developer 🌐 | Technical Writer ✍️| DevOps Enthusiast👨‍💻 | Python🐍 |

Deploying Applications With High Availability on Kubernetes

3 min read

The concept of high availability is critical in today’s application deployment strategies. Even when part of your application’s part fails, your application remains functional and accessible. In Kubernetes, high availability is about designing systems that can tolerate component failures with minimal impact on the service.

To deploy applications with high availability, you need to understand the tools and practices that can help you achieve a resilient and reliable system. This article will guide you through the steps to deploy applications with high availability on Kubernetes.

What Is High Availability

High availability is a characteristic of a system that aims to ensure an agreed level of operational performance, usually uptime, for a longer than normal period.

High availability is achieved by eliminating single points of failure. This means making sure that every component of your application has a backup. These backups are automatically used in case of a failure.

Key Components of High Availability

High availability in Kubernetes relies on several key components, and here are the main components:

Replication Controller/ReplicaSet

Replication controllers, or ReplicaSets, are Kubernetes controllers responsible for maintaining a specified number of pod replicas running at all times.

Pods

Pods are the smallest deployable units in Kubernetes, consisting of one or more containers that share network and storage resources. Pods are scheduled onto nodes by the Kubernetes scheduler. By running multiple replicas of pods across different nodes, Kubernetes ensures redundancy and fault tolerance. If a pod fails, its workload is automatically redistributed to other healthy pods.

Kubernetes Scheduler

The Kubernetes scheduler is responsible for placing pods on nodes in the cluster.

etcd

etcd is a distributed key-value store used by Kubernetes to store cluster state and configuration data. It provides consistent and reliable storage for critical information such as pod metadata, configuration settings, and API objects.

Cluster Auto-Scaling

Kubernetes supports cluster auto-scaling, which automatically adjusts the number of nodes in the cluster based on resource utilization and demand. By dynamically scaling the cluster up or down, Kubernetes ensures that there are enough resources available to maintain high availability and meet workload requirements.

These components work together to provide a reliable platform for running containerized applications, ensuring high availability in Kubernetes clusters.

Benefits of High Availability in Applications:

Improved User Experience

A highly available application ensures a seamless user experience by minimizing downtime. Users can rely on the application to be accessible whenever they need it.

Business Continuity

High availability is crucial for maintaining business operations. Even a few minutes of downtime can lead to a significant revenue loss.

Data Protection

High availability strategies often include data replication processes, which ensure your data is safe and always available, even in the event of a failure.

Scalability

High availability architectures are often designed to be scalable. This means that as your user base grows, your application can scale to meet the demand.

High availability in Kubernetes involves deploying your application across multiple nodes in the cluster, ensuring that if one node fails, the application can continue to run on another node.

Deploying an Application

Deploying your application on Kubernetes involves several steps. Here’s a step-by-step guide to deploy your application on Kubernetes and ensuring high availability:

Step 1 – Set Up Your Kubernetes Cluster:

Before you can deploy your application, you need to have a Kubernetes cluster set up. This could be on a cloud provider like Google Cloud, AWS, or Azure, or it could be a local cluster.

Step 2 – Connect to Your Cluster:

Use the kubectl command-line tool to interact with your cluster. Make sure you’ve configured kubectl to connect to your cluster.

Step 3 – Deploy Your Application:

Use the kubectl apply command to deploy your application. You’ll need to point this command at the Kubernetes manifests you created during the preparation stage.

kubectl apply -f </path/to/your/manifest.yaml>

Step 4 – Verify the Deployment

After deploying your application, use kubectl commands to verify that your deployment was successful. The kubectl get and kubectl describe commands can be particularly useful.

kubectl get deployments
kubectl describe deployment <your-deployment-name>

Now, let’s talk about ensuring high availability during deployment:

Replicas

In your Deployment, you can specify the number of replicas you want for your application.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-application
spec:
  replicas: 3  # specify the number of Pod replicas
  selector:
    matchLabels:
      app: my-application
  template:
    metadata:
      labels:
        app: my-application
    spec:
      containers:
      - name: my-application
        image: my-application:latest

Kubernetes will ensure that this number of instances of your application is always running.

Strategy

Kubernetes Deployments have a strategy field where you can specify the strategy used to replace old Pods by new ones. The RollingUpdate strategy, which is the default, gradually replaces old Pods by new ones while ensuring that your application remains available during the update.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-application
spec:
  replicas: 3
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxUnavailable: 1
      maxSurge: 1
  selector:
    matchLabels:
      app: my-application
  template:
    metadata:
      labels:
        app: my-application
    spec:
      containers:
      - name: my-application
        image: my-application:latest

Readiness and Liveness Probes

Kubernetes uses readiness and liveness probes to know when to send traffic to a Pod and when to restart it.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-application
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-application
  template:
    metadata:
      labels:
        app: my-application
    spec:
      containers:
      - name: my-application
        image: my-application:latest
        ports:
        - containerPort: 8080
        readinessProbe:
          httpGet:
            path: /readiness
            port: 8080
          initialDelaySeconds: 5
          periodSeconds: 5
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 15
          periodSeconds: 15

By setting up these probes, you can ensure that your application is ready to receive traffic and healthy.

  • Services: Kubernetes Services provide network access to your application’s Pods. By using a Service, you can ensure that your application remains accessible even if some Pods fail.
apiVersion: v1
kind: Service
metadata:
  name: my-application-service
spec:
  selector:
    app: my-application
  ports:
    - protocol: TCP
      port: 80
      targetPort: 8080
  type: LoadBalancer

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Abraham Dahunsi Web Developer 🌐 | Technical Writer ✍️| DevOps Enthusiast👨‍💻 | Python🐍 |
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