AWS EKS User Guide

Introduction

Amazon Elastic Kubernetes Service (AWS EKS) is a managed Kubernetes service on the AWS cloud platform. Instead of having to install, operate, and maintain a Kubernetes cluster from scratch yourself, AWS takes over the management of the system's "brain" (Control Plane), helping you focus entirely on deploying and running applications.

Advantages

  • Reduced administrative burden: AWS automatically performs difficult tasks such as version updates, security patching, and ensuring high availability for the Control Plane across multiple Availability Zones.
  • Optimal security: EKS integrates tightly with AWS security services such as IAM (for granular permissions for Pods), VPC (for network isolation), and AWS KMS (for data encryption).
  • Flexible scalability: You can easily increase or decrease the number of resources (nodes) based on the actual traffic of the application, helping to optimize costs.
  • Rich ecosystem: Easily connect with other AWS services such as CloudWatch (monitoring), ELB (load balancing), and Fargate (running containers without managing servers).
  • Full compatibility: Since EKS runs a standard Kubernetes version, you can easily migrate applications from On-premise environments or other clouds to AWS without changing the source code.


Prerequisites

In this article, I will use NestJS to create a simple API to get a list of files in an S3 Bucket. After that, I will build a docker image and push this image to AWS ECR and use this docker image in k8s; if you have any questions about any content, please review the previous articles I mentioned.

The content of the s3.service.ts file is as follows:

import {
  GetObjectCommand,
  ListObjectsV2Command,
  PutObjectCommand,
  S3Client,
} from '@aws-sdk/client-s3'
import {getSignedUrl} from '@aws-sdk/s3-request-presigner'
import {Injectable} from '@nestjs/common'
import {ConfigService} from '@nestjs/config'
import * as mime from 'mime-types'

@Injectable()
export class S3Service {
  private s3Client: S3Client
  private bucket = ''

  constructor(private configService: ConfigService) {
    this.bucket = this.configService.get<string>('BUCKET') || ''
    this.s3Client = new S3Client({})
  }

  async createPresignedUrl(fileName: string) {
    const ContentType = mime.lookup(fileName) || 'application/octet-stream'
    const command = new PutObjectCommand({
      Bucket: this.bucket,
      Key: fileName,
      ContentType,
    })
    const url = await getSignedUrl(this.s3Client, command, {expiresIn: 3600})
    return {url}
  }

  async listFiles() {
    const command = new ListObjectsV2Command({
      Bucket: this.bucket,
    })

    const {Contents} = await this.s3Client.send(command)

    if (!Contents) return []

    const fileList = await Promise.all(
      Contents.map(async file => {
        const getCommand = new GetObjectCommand({
          Bucket: this.bucket,
          Key: file.Key,
        })

        return {
          fileName: file.Key,
          size: file.Size,
          lastModified: file.LastModified,
          viewUrl: await getSignedUrl(this.s3Client, getCommand, {
            expiresIn: 3600,
          }),
        }
      })
    )
    return fileList
  }
}

  • The content is simply to allow uploading via presigned urls and listing the urls to access uploaded files
  • Pay attention to the BUCKET field; you will need to create this value in the .env file and in the .yaml file that will be created in the content below
  • As for the content regarding using CDK to create the S3 Bucket, controller, and how to use presigned urls, please review the previous article I shared

Detail

Use AWS CDK to create the file lib/eks-public-stack.ts as follows:

import { KubectlV34Layer } from "@aws-cdk/lambda-layer-kubectl-v34"
import * as cdk from "aws-cdk-lib"
import * as ec2 from "aws-cdk-lib/aws-ec2"
import * as eks from "aws-cdk-lib/aws-eks"
import * as iam from "aws-cdk-lib/aws-iam"
import { Construct } from "constructs"

export class EksPublicStack extends cdk.Stack {
  constructor(scope: Construct, id: string, props?: cdk.StackProps) {
    super(scope, id, props)

    const vpc = new ec2.Vpc(this, "EksVpc", {
      maxAzs: 2,
      natGateways: 0,
      subnetConfiguration: [
        {
          name: "PublicSubnet",
          subnetType: ec2.SubnetType.PUBLIC,
        },
      ],
    })

    const cluster = new eks.Cluster(this, "MyEksCluster", {
      vpc,
      vpcSubnets: [{ subnetType: ec2.SubnetType.PUBLIC }],
      defaultCapacity: 0,
      version: eks.KubernetesVersion.V1_34,
      endpointAccess: eks.EndpointAccess.PUBLIC_AND_PRIVATE,
      kubectlLayer: new KubectlV34Layer(this, "KubectlLayer"),
      authenticationMode: eks.AuthenticationMode.API_AND_CONFIG_MAP,
      bootstrapClusterCreatorAdminPermissions: true,
    })

    const currentUserName = "<username>"
    cluster.grantAccess(
      "AdminAccess",
      `arn:aws:iam::${this.account}:user/${currentUserName}`,
      [
        eks.AccessPolicy.fromAccessPolicyName("AmazonEKSClusterAdminPolicy", {
          accessScopeType: eks.AccessScopeType.CLUSTER,
        }),
      ],
    )

    cluster.clusterSecurityGroup.addIngressRule(
      ec2.Peer.anyIpv4(),
      ec2.Port.tcp(443),
      "Allow kubectl access from anywhere",
    )

    cluster.addNodegroupCapacity("PublicNodeGroup", {
      instanceTypes: [new ec2.InstanceType("t3.small")],
      minSize: 1,
      maxSize: 2,
      subnets: { subnetType: ec2.SubnetType.PUBLIC },
      amiType: eks.NodegroupAmiType.AL2023_X86_64_STANDARD,
    })

    const s3Policy = new iam.PolicyStatement({
      actions: ["s3:PutObject", "s3:GetObject", "s3:ListBucket"],
      resources: ["*"],
    })

    const serviceAccount = cluster.addServiceAccount("NestJsServiceAccount", {
      name: "nestjs-s3-sa",
      namespace: "default",
    })
    serviceAccount.addToPrincipalPolicy(s3Policy)

    new cdk.CfnOutput(this, "ConfigCommand", {
      value: `aws eks update-kubeconfig --name ${cluster.clusterName}`,
    })
  }
}

  • natGateways: 0, here I create a VPC without using a NAT gateway because this is a service with quite high costs
  • defaultCapacity: 0, the initial number of nodes (EC2); I will configure addAutoScalingGroupCapacity below, so it is not needed here
  • eks.KubernetesVersion.V1_34: this is the current latest version corresponding to the library @aws-cdk/lambda-layer-kubectl-v34; when you use it, please check again to use it with the appropriate kubectlLayer
  • currentUserName: this is the username of the account you use to deploy this CDK; you can get the information as follows (the purpose here is to grant permissions for your current account to operate with the Cluster after it is created)

aws sts get-caller-identity
{
    "UserId": "<UserId>",
    "Account": "<Account>",
    "Arn": "arn:aws:iam::<Account>:user/<username>"
}


  • ec2.Peer.anyIpv4(): I am allowing all IPs to connect to this cluster; if you want more security, you can use ec2.Peer.ipv4('<IP address>')
  • instanceTypes: [new ec2.InstanceType("t3.small")]: this is the minimum instance for nodes to run; if you use micro, there may be too few resources to use
  • PolicyStatement: because the NestJS docker image uses the S3 service, I will authorize this cluster to have permission to use the S3 service
  • the output part of ConfigCommand is used to connect to k8s


Next is the k8s.yml file

apiVersion: apps/v1
kind: Deployment
metadata:
  name: nestjs-app
  namespace: default
spec:
  replicas: 1
  selector:
    matchLabels:
      app: nestjs
  template:
    metadata:
      labels:
        app: nestjs
    spec:
      serviceAccountName: nestjs-s3-sa
      containers:
        - name: nestjs-container
          image: 758222924841.dkr.ecr.ap-southeast-1.amazonaws.com/nestjs-app:latest
          ports:
            - containerPort: 3000
          env:
            - name: REGION
              value: "ap-southeast-1"
            - name: BUCKET
              value: "bucket-public-cb2a91d6"
---
apiVersion: v1
kind: Service
metadata:
  name: nestjs-service
spec:
  type: LoadBalancer
  selector:
    app: nestjs
  ports:
    - protocol: TCP
      port: 80
      targetPort: 3000

  • serviceAccountName: note that this part must have the same name as the serviceAccount created in the CDK
  • image: please replace it with the image URI that you pushed to your ECR accordingly
  • LoadBalancer: to connect to the external internet


After deploying, the result is as follows

✅  EksPublicStack
✨  Deployment time: 961.89s

Outputs:
EksPublicStack.ConfigCommand = aws eks update-kubeconfig --name MyEksCluster83497DF9-b36f5821b0624f9cba4aa5d9414ea355    

✨  Total time: 1068.63s


Resources have been created on the AWS Console


Update the k8s config with the created cluster; you only need to execute the command outputted after deploying the CDK

aws eks update-kubeconfig --name {cluster name}

aws eks update-kubeconfig --name MyEksCluster83497DF9-b36f5821b0624f9cba4aa5d9414ea355
Updated context arn:aws:eks:ap-southeast-1:758222924841:cluster/MyEksCluster83497DF9-b36f5821b0624f9cba4aa5d9414ea355 in ~\.kube\config


Next is to apply the content of the k8s.yml file

$ kubectl apply -f k8s.yml
deployment.apps/nestjs-app created
service/nestjs-service created


Wait a moment for the resources to be created; when you check and see the status of the resources as ready like this, it is successful

$ kubectl get all
NAME                             READY   STATUS    RESTARTS   AGE
pod/nestjs-app-d5bd589dd-4h8c2   1/1     Running   0          3m45s

NAME                     TYPE           CLUSTER-IP       EXTERNAL-IP                                                                    PORT(S)        AGE
service/kubernetes       ClusterIP      172.20.0.1       <none>                                                                         443/TCP        15m
service/nestjs-service   LoadBalancer   172.20.222.102   a66b8971219564b5390f2a15cb8bf3f3-1141398222.ap-southeast-1.elb.amazonaws.com   80:30087/TCP   3m45s

NAME                         READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/nestjs-app   1/1     1            1           3m45s

NAME                                   DESIRED   CURRENT   READY   AGE
replicaset.apps/nestjs-app-d5bd589dd   1         1         1       3m45s


Pay attention to the LoadBalancer EXTERNAL-IP part, which is the endpoint you can use to access the API

Happy coding!

See more articles here.

Comments

Post a Comment

Popular posts from this blog

All practice series

Image
Introduction This is a comprehensive page about the technologies I have shared in series format. You can view brief introductions and links to directly access each series you are interested in. In the field of software development, to deploy a product from the initial idea to its release, the standard process typically involves several stages as follows: Database : Designing and implementing the database according to business requirements, storing data during the system's operation. Backend : Handling the main logic of the system, communicating with the database and services. Frontend : Building the interface for users to interact with the system, which could be a desktop, mobile, or web application. This usually includes implementing UI/UX and integrating APIs from the backend. DevOps : Deploying the system for use, which can be done on a server or in the cloud. Testing : Applying testing methods to ensure the product meets the standards for release. Of course, these are just stan...
Read more

Deploying a NodeJS Server on Google Kubernetes Engine

Image
Introduction to GKE Google Kubernetes Engine (GKE) is a managed Kubernetes service provided by Google Cloud Platform , facilitating simple and efficient deployment of Docker images. We only need to provide some configuration for the number of nodes, machine types, and replicas to use. Some Concepts Cluster A Cluster is a collection of Nodes where Kubernetes can deploy applications. A cluster includes at least one Master Node and multiple Worker Nodes . The Master Node is used to manage the Worker Nodes . Node A Node is a server in the Kubernetes Cluster. Nodes can be physical servers or virtual machines. Each Node runs  Kubernetes , which is responsible for communication between the Master Node and Worker Node , as well as managing Pods and containers running on it. Pod A Pod is the smallest deployable unit in Kubernetes . Each Pod contains one or more containers, typically Docker containers. Containers in the same Pod share a network namespace, meaning they have the ...
Read more

Setting up Kubernetes Dashboard with Kind

Image
Introduction In a previous article, I guided you through using Helm to deploy on Google Kubernetes Engine . However, if you want to cut down costs by using Kubernetes in your local environment instead of relying on a cloud provider during development, then Kind is your go-to. There are several tools to help set up Kubernetes locally, such as MiniKube , Kind , K3S , KubeAdm , and more. Each tool has its own pros and cons. In this article, I'll walk you through using Kind to quickly set up a Kubernetes cluster on Docker . Kind stands out for its compactness, making Kubernetes start up quickly, being user-friendly, and supporting the latest Kubernetes versions. Working with Kind Firstly, follow the instructions here to install Kind according to your operating system. If you're using Ubuntu , execute the command: [ $( uname -m ) = x86_64 ] && curl -Lo ./kind https://kind.sigs.k8s.io/dl/v0.23.0/kind-linux-amd64 chmod +x ./kind sudo mv ./kind /usr/local/bin/ki...
Read more

Using Kafka with Docker and NodeJS

Image
Introduction to Kafka Kafka is an open-source , distributed messaging system that functions on a publish/subscribe model. It is widely used by numerous large companies for high-performance , real-time data streaming. Developed by LinkedIn since 2011, Kafka has grown into the most popular distributed streaming platform. It can handle vast amounts of records with high efficiency. Advantages of Kafka Open-source : Freely available and continuously improved by a large community. High-throughput, high-frequency : Capable of processing large volumes of data across topics continuously. Automatic message storage : Allows for easy message retrieval and verification. Large user community : Offers extensive support and shared resources. Basic Concepts If you're new to Kafka and Message Queues, here are some key concepts to understand: Producer : Creates and sends data to the Kafka server, where data is sent as messages in byte array format. Consumer : One or more consumers subscribe to...
Read more

Monitoring with cAdvisor, Prometheus and Grafana on Docker

Image
Introduction Monitoring a system is crucial after deploying a product to a production environment. Keeping an eye on system metrics like logs , CPU , RAM , disks , etc, helps identify the system's status, performance issues, and provides timely solutions to ensure stable operations. While cloud providers like Google , Amazon , or Azure offer built-in monitoring systems, if your company needs to manage multiple applications/systems/containers and desires a centralized monitoring system for easier management, using cAdvisor , Prometheus , and Grafana is a sensible choice. These three popular open-source tools are widely used by DevOps teams, especially for monitoring container applications. cAdvisor Developed by Google , cAdvisor is an open-source project used to analyze resource usage, performance, and other metrics from container applications, providing an overview of all running containers. Find more details here Prometheus Prometheus is a toolkit for system monitoring and a...
Read more

Kubernetes Practice Series

Image
Introduction Kubernetes (often abbreviated as K8s ) is an open-source system designed to automate the deployment, scaling, and management of containerized applications. This page serves as a collection of articles related to Kubernetes (K8s) , including theoretical concepts and practical guides on using Kubernetes to set up essential tools for the software development process. I will continue to update this series with new articles as ideas come to mind, to ensure the series becomes more comprehensive. The articles are arranged in increasing order of difficulty to make it easier for you to follow. If you have time, it's recommended that you start from the beginning of the series to acquire the necessary knowledge and information that will prepare you for the subsequent articles. Key Topics Covered in This Series Basic Knowledge : Fundamental concepts, common commands, etc. Resources : Pod, Deployment, Service, StatefulSet, Ingress, etc. Pod Autoscaler : Horizontal and Vertical sc...
Read more

Kubernetes Deployment for Zero Downtime

Image
Introduction In Kubernetes (K8s) , a Pod is the smallest resource unit used to run one or more containers during deployment. There are several ways to create a Pod : you can create it directly, use a ReplicationController , or a ReplicaSet . However, the most commonly used resource for managing Pods is the Deployment . When you use a Deployment , it actually creates a ReplicaSet to manage the Pods but comes with many additional benefits that support the deployment process. Some Advantages of Deployment : Ensures Pod Availability : It guarantees that the specified number of Pods are always running according to the configuration, automatically deploying additional Pods if any failures occur. Supports Restart and Undo Deployment : Allows you to easily restart or roll back to previous versions of your Deployment . Zero Downtime Deployment : When updating configurations or scaling Deployments , zero downtime is crucial. This means that new Pods are created while the old Pods are stil...
Read more

Practicing with Google Cloud Platform - Google Kubernetes Engine to deploy nginx

Image
Introduction This article provides simple step-by-step instructions for those who are new to Google Cloud Platform (GCP) and Google Kubernetes Engine (GKE) . I'll guide you through using  GKE  to create clusters and deploy nginx . The instructions below will primarily use gcloud  and kubectl  to initialize the cluster, which is more convenient than manual management on the Google Cloud interface. Prerequisites First, you need to prepare the following: Have a GCP account with permission to use Cloud services. If you're new, you'll get a $300 free trial to use for 90 days . Create a new GCP project. Enable Compute Engine and Kubernetes Engine services. Install Google Cloud SDK and kubectl For this installation step, refer to the GCP documentation for instructions tailored to your operating system. Once installed, execute the following commands to check if gcloud  and kubectl  are installed: gcloud version kubectl version If you see the version resul...
Read more

NodeJS Practice Series

Image
Introduction NodeJS is an open-source and cross-platform JavaScript runtime environment . Here are some key points about NodeJS : V8 Engine : NodeJS runs on the V8 JavaScript engine , which is also the core of Google Chrome . This allows NodeJS to be highly performant. Asynchronous and Non-Blocking : NodeJS  uses an event-driven, non-blocking I/O model. It’s lightweight and efficient, making it ideal for data-intensive real-time applications. Single-Threaded : NodeJS  runs in a single process, handling multiple requests without creating new threads. It eliminates waiting and continues with the next request. Common Language : Frontend developers who write JavaScript for browsers can use the same language for server-side code in NodeJS . You can even use the latest ECMAScript standards without waiting for browser updates. This page is designed to compile articles related to NodeJS , including how to integrate it with various libraries and relevant tech stacks. I will cont...
Read more

Helm for beginer - Deploy nginx to Google Kubernetes Engine

Image
Introduction Helm is a package manager for Kubernetes , which simplifies the process of deploying and managing applications on Kubernetes clusters. Helm uses a packaging format called charts , which are collections of files that describe a related set of Kubernetes resources. Key Components of Helm Charts : Helm packages are called charts. A chart is a collection of files that describe a related set of Kubernetes resources. A single chart might be used to deploy something simple, like a memcached pod, or something complex, like a full web app stack with HTTP servers , databases, caches, and so on. Values : Charts can be customized with values, which are configuration settings that specify how the chart should be installed on the cluster. These values can be set in a ` values.yaml ` file or passed on the command line. Releases : When you install a chart, a new release is created. This means that one chart can be installed multiple times into the same cluster, and each can be indep...
Read more