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Mastering Elastic Kubernetes Service on AWS

You're reading from   Mastering Elastic Kubernetes Service on AWS Deploy and manage EKS clusters to support cloud-native applications in AWS

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Product type Paperback
Published in Jul 2023
Publisher Packt
ISBN-13 9781803231211
Length 448 pages
Edition 1st Edition
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Authors (2):
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Yang-Xin Cao Yang-Xin Cao
Author Profile Icon Yang-Xin Cao
Yang-Xin Cao
Malcolm Orr Malcolm Orr
Author Profile Icon Malcolm Orr
Malcolm Orr
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Toc

Table of Contents (28) Chapters Close

Preface 1. Part 1: Getting Started with Amazon EKS
2. Chapter 1: The Fundamentals of Kubernetes and Containers FREE CHAPTER 3. Chapter 2: Introducing Amazon EKS 4. Chapter 3: Building Your First EKS Cluster 5. Chapter 4: Running Your First Application on EKS 6. Chapter 5: Using Helm to Manage a Kubernetes Application 7. Part 2: Deep Dive into EKS
8. Chapter 6: Securing and Accessing Clusters on EKS 9. Chapter 7: Networking in EKS 10. Chapter 8: Managing Worker Nodes on EKS 11. Chapter 9: Advanced Networking with EKS 12. Chapter 10: Upgrading EKS Clusters 13. Part 3: Deploying an Application on EKS
14. Chapter 11: Building Applications and Pushing Them to Amazon ECR 15. Chapter 12: Deploying Pods with Amazon Storage 16. Chapter 13: Using IAM for Granting Access to Applications 17. Chapter 14: Setting Load Balancing for Applications on EKS 18. Chapter 15: Working with AWS Fargate 19. Chapter 16: Working with a Service Mesh 20. Part 4: Advanced EKS Service Mesh and Scaling
21. Chapter 17: EKS Observability 22. Chapter 18: Scaling Your EKS Cluster 23. Chapter 19: Developing on EKS 24. Part 5: Overcoming Common EKS Challenges
25. Chapter 20: Troubleshooting Common Issues 26. Index 27. Other Books You May Enjoy

What is Kubernetes?

Kubernetes is an open source container orchestrator originally developed by Google but now seen as the de facto container platform for many organizations. Kubernetes is deployed as clusters containing a control plane that provides an API that exposes the Kubernetes operations, a scheduler that schedules containers (Pods are discussed next) across the worker nodes, a datastore to store all cluster data and state (etcd), and a controller that manages jobs, failures, and restarts.

Figure 1.5 – An overview of Kubernetes

Figure 1.5 – An overview of Kubernetes

The cluster is also composed of many worker nodes that make up the data plane. Each node runs the kubelet agent, which makes sure that containers are running on a specific node, and kube-proxy, which manages the networking for the node.

One of the major advantages of Kubernetes is that all the resources are defined as objects that can be created, read, updated, and deleted. The next section will review the major K8s objects, or “kinds” as they are called, that you will typically be working with.

Key Kubernetes API resources

Containerized applications will be deployed and launched on a worker node(s) using the API. The API provides an abstract object called a Pod, which is defined as one or more containers sharing the same Linux namespace, cgroups, network, and storage resources. Let’s look at a simple example of a Pod:

apiVersion: v1
kind: Pod
metadata:
  name: nginx
spec:
  containers:
  - name: nginx
    image: nginx:1.14.2
    ports:
    - containerPort: 80

In this example, kind defines the API object, a single Pod, and metadata contains the name of the Pod, in this case, nginx. The spec section contains one container, which will use the nginx 1.14.2 image and expose a port (80).

In most cases, you want to deploy multiple Pods across multiple nodes and maintain that number of Pods even if you have node failures. To do this, you use a Deployment, which will keep your Pods running. A Deployment is a Kubernetes kind that allows you to define the number of replicas or Pods you want, along with the Pod specification we saw previously. Let’s look at an example that builds on the nginx Pod we discussed previously:

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:1.14.2
        ports:
        - containerPort: 80

Finally, you want to expose your Pods outside the clusters! This is because, by default, Pods and Deployments are only accessible from inside the cluster’s other Pods. There are various services, but let’s discuss the NodePort service here, which exposes a dynamic port on all nodes in the cluster.

To do this, you will use the kind of Service, an example of which is shown here:

kind: Service
apiVersion: v1
metadata:
  name: nginx-service
spec:
  type: NodePort
  selector:
    app: nginx
  ports:
  port: 80
  nodePort: 30163

In the preceding example, Service exposes port 30163 on any host in the cluster and maps it back to any Pod that has label app=nginx (set in the Deployment), even if a host is not running on that Pod. It translates the port value to port 80, which is what the nginx Pod is listening on.

In this section, we’ve looked at the basic Kubernetes architecture and some basic API objects. In the final section, we will review some standard deployment architectures.

You have been reading a chapter from
Mastering Elastic Kubernetes Service on AWS
Published in: Jul 2023
Publisher: Packt
ISBN-13: 9781803231211
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