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IoT Edge Computing with MicroK8s

You're reading from   IoT Edge Computing with MicroK8s A hands-on approach to building, deploying, and distributing production-ready Kubernetes on IoT and Edge platforms

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803230634
Length 416 pages
Edition 1st Edition
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Author (1):
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Karthikeyan Shanmugam Karthikeyan Shanmugam
Author Profile Icon Karthikeyan Shanmugam
Karthikeyan Shanmugam
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Toc

Table of Contents (24) Chapters Close

Preface 1. Part 1: Foundations of Kubernetes and MicroK8s
2. Chapter 1: Getting Started with Kubernetes FREE CHAPTER 3. Chapter 2: Introducing MicroK8s 4. Part 2: Kubernetes as the Preferred Platform for IoT and Edge Computing
5. Chapter 3: Essentials of IoT and Edge Computing 6. Chapter 4: Handling the Kubernetes Platform for IoT and Edge Computing 7. Part 3: Running Applications on MicroK8s
8. Chapter 5: Creating and Implementing Updates on a Multi-Node Raspberry Pi Kubernetes Clusters 9. Chapter 6: Configuring Connectivity for Containers 10. Chapter 7: Setting Up MetalLB and Ingress for Load Balancing 11. Chapter 8: Monitoring the Health of Infrastructure and Applications 12. Chapter 9: Using Kubeflow to Run AI/MLOps Workloads 13. Chapter 10: Going Serverless with Knative and OpenFaaS Frameworks 14. Part 4: Deploying and Managing Applications on MicroK8s
15. Chapter 11: Managing Storage Replication with OpenEBS 16. Chapter 12: Implementing Service Mesh for Cross-Cutting Concerns 17. Chapter 13: Resisting Component Failure Using HA Clusters 18. Chapter 14: Hardware Virtualization for Securing Containers 19. Chapter 15: Implementing Strict Confinement for Isolated Containers 20. Chapter 16: Diving into the Future 21. Frequently Asked Questions About MicroK8s
22. Index 23. Other Books You May Enjoy

Understanding deployments

Deployment allows you to make declarative changes to pods and ReplicaSets. You can provide a desired state for the deployment, and the deployment controller will incrementally change the actual state to the desired state.

Deployments can be used to create new ReplicaSets or to replace existing deployments with new deployments. When a new version is ready to go live in production, the deployment can easily handle the upgrade with no downtime by using predefined rules. The following diagram shows an example of a deployment:

Figure 1.8 – A deployment

Figure 1.8 – A deployment

The following is an example of a deployment. It creates a ReplicaSet to bring up three nginx pods:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: nginx-sample-deployment
  labels:
    app: nginx
spec:
  replicas: 3
  selector:
    matchLabels:
      app: nginx
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx:1:21
        ports:
        - containerPort: 80

In the preceding example, the following occurred:

  • A deployment called nginx-sample-deployment is created, as indicated by the metadata.name field.
  • The image for this deployment is set by the Spec.containers.image field (nginx:latest).
  • The deployment creates three replicated pods, as indicated by the replicas field.

The most commonly used kubectl commands concerning deployment are as follows:

  • The apply command creates the pod:
    kubectl apply -f FILENAME.

For example, the kubectl apply -f ./nginx-deployment.yaml command will create a new deployment from the nginx-deployment.yaml YAML file.

  • The get deployments command checks the status of the deployment:
    kubectl get deployments 

This will produce the following output:

NAME               READY   UP-TO-DATE   AVAILABLE   AGE
nginx-sample-deployment   3/3     0            0           1s

The following fields are displayed:

  • NAME indicates the names of the deployments in the namespace.
  • READY shows how many replicas of the application are available.
  • UP-TO-DATE shows the number of replicas that have been updated to achieve the desired state.
  • AVAILABLE shows the number of available replicas.
  • AGE indicates the length of time the application has been running.
  • The describe deployments command indicates the details of the deployment:
    kubectl describe deployments
  • The delete command removes the deployment that was made by the apply command:
    kubectl delete -f FILENAME.

With that, we have learned that deployments are used to define the life cycle of an application, including which container images to use, how many pods you should have, and how they should be updated. In the next section, we will look at StatefulSets and DaemonSets.

You have been reading a chapter from
IoT Edge Computing with MicroK8s
Published in: Sep 2022
Publisher: Packt
ISBN-13: 9781803230634
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