High level guide to run data engineering project In EKS

Prasad
2 min readDec 13, 2023

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### 1. Containerize Your Applications:

  • For each of your data engineering projects, create a `Dockerfile` specifying the necessary dependencies, configurations, and the entry point for your application. Build Docker images for each project.

### 2. Create Kubernetes Manifests or Helm Charts:

  • For each project, create Kubernetes manifests (YAML files) or Helm charts that define the necessary Kubernetes resources, such as Deployments, Services, ConfigMaps, etc. These files should describe how your application should be deployed and exposed within the Kubernetes cluster.

### 3. Set Up EKS Cluster:

  • Use the AWS Management Console, AWS CLI, or Terraform to create an EKS cluster. Ensure that your AWS CLI and Kubernetes tools are configured correctly. This involves setting up your Amazon EKS cluster and associating it with your AWS account.

### 4. Configure kubectl for EKS:

  • Configure your `kubectl` command-line tool to interact with your EKS cluster. This involves running an AWS CLI command to update your kubeconfig file with the necessary cluster information:

. ```bash

. aws eks – region <region> update-kubeconfig – name <cluster-name>

. ```

### 5. Create Kubernetes Namespaces:

  • Create separate Kubernetes namespaces for each data engineering project. This helps isolate resources and avoids naming conflicts:

. ```bash

. kubectl create namespace project1

. kubectl create namespace project2

. kubectl create namespace project3

. ```

### 6. Deploy Applications to Respective Namespaces:

  • Deploy each project to its designated namespace using `kubectl apply` or Helm:

. ```bash

. # Example for deploying to project1 namespace

. kubectl apply -f project1-deployment.yaml -n project1

. ```

### 7. Verify Deployments:

  • Check the status of your deployments and services within each namespace to ensure that the applications are running correctly:

. ```bash

. kubectl get pods -n project1

. kubectl get services -n project1

. ```

### 8. Networking and Communication:

  • Configure networking and communication between different projects if needed. You can use Kubernetes Services, Ingress controllers, or Network Policies to control the communication between namespaces.

### 9. Monitoring and Logging:

  • Set up monitoring and logging solutions for each project. Kubernetes provides integrations with various tools like Prometheus, Grafana, and Fluentd. Configure these tools to monitor the performance and gather logs from your applications.

### 10. Scale and Manage:

  • Leverage Kubernetes features for scaling and managing your applications efficiently. Utilize features like autoscaling, rolling updates, and resource management based on the specific requirements of each project.

Always refer to the documentation of the tools, applications, and Kubernetes for more detailed and project-specific information. This guide provides a general overview, and the specifics may vary depending on your applications and requirements.

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Prasad

I am a OpenSource Enthusiast|Python Lover who attempts to find simple explanations for questions and share them with others