This project provides a hassle-free solution for deploying Amazon Elastic Kubernetes Service (EKS) clusters, automating the process of git checkout, building code, creating Docker images, pushing them to a registry, and deploying to the EKS cluster. The tool simplifies the infrastructure setup and deployment pipeline, making it easier for developers and DevOps teams to focus on application development and scaling.
Automated EKS Cluster Setup: Deploys and configures an EKS cluster on AWS with minimal manual steps.
Continuous Integration/Deployment: Automatically checks out code from Git, builds Docker images, and pushes them to a container registry (e.g., ECR, Docker Hub).
Kubernetes Deployment: Seamlessly deploy your Docker images to the EKS cluster.
Customizable Deployment: Supports custom deployment configurations using Kubernetes YAML files.
Scalable: Designed for production-grade EKS clusters with high availability and scalability.
Before you begin, ensure you have the following:
Ensure your AWS credentials are properly configured either via ~/.aws/credentials or environment variables.
export AWS_ACCESS_KEY_ID="your-access-key"
export AWS_SECRET_ACCESS_KEY="your-secret-key"
AWS CLI: Set up the AWS CLI with the required permissions to manage EKS.
kubectl: Install and configure kubectl to interact with your Kubernetes clusters.
Docker: Docker installed to build and manage container images.
Terraform (optional): Use Terraform to automate EKS cluster provisioning.
Python or Node.js: For the backend services, which handle the automation tasks.
AWS IAM Permissions: Sufficient AWS IAM permissions to create and manage EKS, EC2, VPC, and other related services.
Clone the Repository:
git clone <repo-url>
cd eks-deployment-tool
Python:
pip install -r requirements.txt
Node.js:
npm install
aws configure
aws eks update-kubeconfig --name <cluster-name> --region <aws-region>
If you're using Terraform to provision the EKS cluster, run:
cd EKS-TERRAFORM
terragrunt init
terragrunt apply
Trigger Build and Deploy Pipeline:
From the Web UI:
Provide the Git repository URL, branch name, Docker image tag, and other necessary details.
Click "Start Deployment" to trigger the pipeline.
python deploy.py --repo <repo-url> --branch <branch> --image <image-name> --tag <tag>
Monitor Deployment:
View the logs and monitor the status of the deployment from the web UI.
The application requires the following environment variables to be set:
AWS_ACCESS_KEY_ID: Your AWS access key.
AWS_SECRET_ACCESS_KEY: Your AWS secret key.
AWS_DEFAULT_REGION: The AWS region for the EKS cluster.
DOCKER_REGISTRY_URL: The URL of your Docker registry (e.g., ECR, Docker Hub).
KUBE_CONFIG_PATH: The path to the kubeconfig file to interact with your Kubernetes cluster.
Git Checkout: The application checks out the latest code from the specified Git branch.
Build: Builds the source code and creates a Docker image using the provided Dockerfile.
Push to Registry: Tags and pushes the Docker image to the configured container registry.
Deploy to EKS: Deploys the Docker image to the EKS cluster using kubectl and a Kubernetes deployment YAML file.
Dockerfile: Ensure your project has a valid Dockerfile for building the application.
Kubernetes YAML: Customize the Kubernetes deployment YAML file located in k8s/deployment.yaml.
Troubleshooting
AWS Permissions Error: Ensure your IAM user/role has sufficient permissions to manage EKS and other AWS resources.
Docker Build Issues: Verify that the Dockerfile in your repository is valid and can successfully build the image locally.
Kubernetes Deployment Issues: Check the status of your deployment by running:
kubectl get pods
kubectl logs <pod-name>
Contributions are welcome! Please submit pull requests or open issues for any features or bugs.
This project is licensed under the MIT License.