aws-ecs
aws-ecsterraformcloudformationmicroservicescontainerization
Description
This rule covers best practices for developing, deploying, and maintaining applications using AWS Elastic Container Service (ECS). It includes guidance on code organization, performance, security, testing, and common pitfalls.
Globs
**/*.{tf,yml,yaml,json,sh,dockerfile}---
description: This rule covers best practices for developing, deploying, and maintaining applications using AWS Elastic Container Service (ECS). It includes guidance on code organization, performance, security, testing, and common pitfalls.
globs: **/*.{tf,yml,yaml,json,sh,dockerfile}
---
- **General Principles:**
- **Infrastructure as Code (IaC):** Treat your ECS infrastructure as code. Use tools like Terraform, AWS CloudFormation, or AWS CDK to define and manage your ECS clusters, task definitions, and services.
- **Configuration Management:** Externalize configuration from your application code. Use environment variables, AWS Secrets Manager, or AWS Systems Manager Parameter Store to manage configuration data.
- **Idempotency:** Ensure that your deployment scripts and automation are idempotent. This means that running the same script multiple times should have the same result as running it once.
- **Automation:** Automate all aspects of your ECS deployment, from building container images to deploying services and scaling resources.
- **1. Code Organization and Structure:**
- **1.1 Directory Structure:**
- **Project Root:** The base directory containing all project-related files.
- `infrastructure/`: Contains IaC code (Terraform, CloudFormation) for ECS clusters, task definitions, services, VPC, etc.
- `application/`: Contains source code for your containerized application.
- `src/`: Application source code.
- `tests/`: Unit, integration, and end-to-end tests.
- `Dockerfile`: Dockerfile for building the application container image.
- `scripts/`: Contains deployment, build, and other utility scripts.
- `docs/`: Documentation for the project.
- `README.md`: Project README file.
- **1.2 File Naming Conventions:**
- **Terraform:** `main.tf`, `variables.tf`, `outputs.tf`, `<module_name>.tf`
- **CloudFormation:** `<stack_name>.yml` or `<stack_name>.yaml`
- **Docker:** `Dockerfile` (no extension), `.dockerignore`
- **Scripts:** `<script_name>.sh` (Bash), `<script_name>.py` (Python)
- **Configuration:** `config.yml`, `config.json`, `.env`
- **1.3 Module Organization:**
- **Terraform Modules:** Create reusable Terraform modules for common ECS infrastructure components (e.g., ECS cluster, task definition, load balancer).
- **Application Modules:** Organize your application code into logical modules based on functionality (e.g., authentication, API, database access).
- Use separate git repositories for independent services/applications, and ECS services accordingly. This avoids monolithic deployments and allows independent scaling and versioning.
- **1.4 Component Architecture:**
- **Microservices:** Design your application as a collection of microservices, each deployed as an independent ECS service.
- **API Gateway:** Use an API gateway (e.g., Amazon API Gateway) to route requests to different ECS services.
- **Message Queue:** Use a message queue (e.g., Amazon SQS, Amazon MQ) for asynchronous communication between services.
- **Database:** Use a managed database service (e.g., Amazon RDS, Amazon DynamoDB) for data persistence. Ensure proper security and access control configurations.
- **1.5 Code Splitting:**
- Break down large applications or services into smaller, more manageable components that can be deployed independently.
- Optimize container images to only include code required for each specific component.
- Utilize ECS services to deploy each component separately, enabling independent scaling and upgrades.
- **2. Common Patterns and Anti-patterns:**
- **2.1 Design Patterns:**
- **Sidecar:** Use sidecar containers (e.g., for logging, monitoring, or service mesh) to add functionality to your main application container without modifying the application code. Use a separate container in the same task definition.
- **Backend for Frontend (BFF):** Create a BFF layer that provides a specific API for each client application, improving performance and security.
- **Strangler Fig:** Gradually migrate a legacy application to ECS by introducing new microservices and slowly replacing the old functionality.
- **Aggregator Pattern:** Use an aggregator service to combine data from multiple backend services into a single response.
- **2.2 Recommended Approaches:**
- **Health Checks:** Implement robust health checks for your containers and configure ECS to use them. Use both `HEALTHCHECK` in the `Dockerfile` for initial container health and ECS health checks (ELB health checks) for service availability.
- **Service Discovery:** Use service discovery (e.g., AWS Cloud Map) to enable services to find each other dynamically.
- **Load Balancing:** Use a load balancer (e.g., Application Load Balancer, Network Load Balancer) to distribute traffic across multiple ECS tasks.
- **Auto Scaling:** Configure auto scaling to automatically adjust the number of ECS tasks based on demand. Use CloudWatch metrics (CPU, memory, request count) as scaling triggers.
- **Immutable Infrastructure:** Avoid making changes to running containers. Instead, redeploy a new container image with the changes.
- **Use ECS Exec for debugging** avoid SSH into running EC2 instances
- **2.3 Anti-patterns:**
- **Hardcoding Configuration:** Avoid hardcoding configuration values in your application code.
- **Large Container Images:** Keep your container images small by using multi-stage builds and removing unnecessary dependencies.
- **Ignoring Security Best Practices:** Neglecting security best practices can lead to vulnerabilities. Always follow security best practices for container images, task definitions, and IAM roles.
- **Manual Scaling:** Manually scaling ECS tasks is inefficient and error-prone. Use auto scaling instead.
- **Monolithic Containers:** Avoid creating single containers that run multiple applications. Break them down into smaller, single-purpose containers.
- **2.4 State Management:**
- **Stateless Applications:** Design your applications to be stateless whenever possible. Store state in a database or other external storage service.
- **Persistent Storage:** Use persistent storage volumes (e.g., Amazon EFS, Amazon EBS) for stateful applications.
- **Container Lifecycle:** Understand the container lifecycle and how ECS manages container restarts and replacements.
- **2.5 Error Handling:**
- **Logging:** Implement comprehensive logging and monitoring for your applications. Log to stdout/stderr, and use a logging driver (e.g., FireLens) to ship logs to a central logging service (e.g., CloudWatch Logs, Splunk).
- **Exception Handling:** Implement proper exception handling in your application code.
- **Retry Logic:** Implement retry logic for transient errors.
- **Dead Letter Queues:** Use dead letter queues (DLQs) to handle messages that cannot be processed after multiple retries.
- **3. Performance Considerations:**
- **3.1 Optimization Techniques:**
- **Resource Allocation:** Properly size your ECS tasks based on the application's resource requirements (CPU, memory). Monitor resource utilization and adjust task sizes as needed.
- **Container Image Optimization:** Optimize container images by minimizing size, using efficient base images, and leveraging layer caching. Use tools like `docker image prune` to remove unused images.
- **Load Balancing:** Configure load balancing algorithms and connection draining to optimize traffic distribution and minimize downtime.
- **Caching:** Implement caching at various levels (e.g., application, CDN) to reduce latency and improve performance.
- **Connection Pooling:** Reuse database connections to minimize overhead.
- **3.2 Memory Management:**
- **Memory Limits:** Set appropriate memory limits for your containers. Monitor memory usage and adjust limits to prevent out-of-memory errors.
- **Garbage Collection:** Optimize garbage collection settings for your application's runtime environment.
- **Memory Leaks:** Identify and fix memory leaks in your application code.
- **3.3 Bundle Size Optimization:**
- **Code Splitting:** Split your application code into smaller bundles to reduce the initial load time. Utilize dynamic imports to only load code when it's needed.
- **Tree Shaking:** Remove unused code from your application bundle.
- **Minification:** Minify your application code to reduce its size.
- **Compression:** Compress your application code to reduce its size.
- **3.4 Lazy Loading:**
- Load resources (e.g., images, data) only when they are needed.
- Use lazy-loading techniques to improve the initial load time of your application.
- **4. Security Best Practices:**
- **4.1 Common Vulnerabilities:**
- **Container Image Vulnerabilities:** Unpatched vulnerabilities in container images can be exploited by attackers. Regularly scan container images for vulnerabilities and apply patches.
- **IAM Role Misconfiguration:** Overly permissive IAM roles can allow attackers to access sensitive resources. Follow the principle of least privilege and grant only the necessary permissions.
- **Network Security Misconfiguration:** Misconfigured network security can expose your ECS services to unauthorized access. Use security groups and network ACLs to restrict network access.
- **Secrets Management Vulnerabilities:** Storing secrets in plain text can expose them to attackers. Use a secrets management service (e.g., AWS Secrets Manager) to securely store and manage secrets.
- **4.2 Input Validation:**
- Validate all input data to prevent injection attacks (e.g., SQL injection, command injection).
- Use a framework or library to perform input validation.
- **4.3 Authentication and Authorization:**
- Implement authentication and authorization to control access to your ECS services.
- Use a standard authentication protocol (e.g., OAuth 2.0, OpenID Connect).
- Use fine-grained authorization policies to restrict access to specific resources.
- **4.4 Data Protection:**
- Encrypt sensitive data at rest and in transit.
- Use HTTPS to encrypt data in transit.
- Use AWS KMS to encrypt data at rest.
- Implement data masking and tokenization to protect sensitive data.
- **4.5 Secure API Communication:**
- Use HTTPS for all API communication.
- Implement authentication and authorization for all API endpoints.
- Validate all input data to prevent injection attacks.
- Protect against Cross-Site Request Forgery (CSRF) attacks.
- **5. Testing Approaches:**
- **5.1 Unit Testing:**
- Write unit tests for individual components of your application.
- Use a unit testing framework (e.g., JUnit, pytest).
- Mock external dependencies to isolate the component being tested.
- **5.2 Integration Testing:**
- Write integration tests to verify the interaction between different components of your application.
- Use a test environment that is similar to the production environment.
- Test the integration with external services (e.g., databases, message queues).
- **5.3 End-to-End Testing:**
- Write end-to-end tests to verify the functionality of the entire application.
- Use an end-to-end testing framework (e.g., Selenium, Cypress).
- Test the application from the user's perspective.
- **5.4 Test Organization:**
- Organize your tests into a logical directory structure.
- Use meaningful names for your test files and test methods.
- Use a test runner to execute your tests.
- **5.5 Mocking and Stubbing:**
- Use mocking and stubbing to isolate components during testing.
- Use a mocking framework (e.g., Mockito, EasyMock).
- Create mock objects that simulate the behavior of external dependencies.
- **6. Common Pitfalls and Gotchas:**
- **6.1 Frequent Mistakes:**
- **Incorrect IAM Permissions:** Granting insufficient or excessive IAM permissions can lead to security vulnerabilities or application failures.
- **Misconfigured Network Settings:** Misconfigured network settings can prevent containers from communicating with each other or with external services.
- **Insufficient Resource Limits:** Setting insufficient resource limits (CPU, memory) can cause containers to crash or become unresponsive.
- **Ignoring Health Checks:** Ignoring health checks can lead to ECS tasks being considered healthy even when they are not.
- **Failing to handle SIGTERM signals:** Applications in containers must gracefully handle SIGTERM signals to allow ECS to shutdown tasks cleanly.
- **6.2 Edge Cases:**
- **Task Placement Constraints:** Be aware of task placement constraints (e.g., availability zone, instance type) and how they can affect task scheduling.
- **Service Discovery Limitations:** Understand the limitations of service discovery and how it can affect service resolution.
- **Load Balancer Connection Draining:** Be aware of load balancer connection draining and how it can affect application availability during deployments.
- **6.3 Version-Specific Issues:**
- Stay up-to-date with the latest ECS agent and Docker versions to avoid known issues and security vulnerabilities.
- Check the AWS documentation for any version-specific issues or known bugs.
- **6.4 Compatibility Concerns:**
- Be aware of compatibility issues between ECS and other AWS services (e.g., VPC, IAM, CloudWatch).
- Test your application with different versions of these services to ensure compatibility.
- **6.5 Debugging Strategies:**
- **Logging:** Use comprehensive logging to track application behavior and identify errors.
- **Monitoring:** Use monitoring tools (e.g., CloudWatch) to track resource utilization and application performance.
- **Debugging Tools:** Use debugging tools (e.g., Docker exec, AWS Systems Manager Session Manager) to troubleshoot running containers.
- **ECS Exec:** Utilize the ECS Exec feature to directly connect to containers for debugging purposes.
- **7. Tooling and Environment:**
- **7.1 Recommended Tools:**
- **Terraform:** For infrastructure as code.
- **AWS CLI:** For interacting with AWS services from the command line.
- **Docker:** For building and managing container images.
- **AWS SAM CLI:** For local development of serverless applications.
- **Visual Studio Code (VS Code):** With AWS and Docker extensions for development and debugging.
- **cdk8s:** Define Kubernetes applications and ECS using general purpose programming languages.
- **7.2 Build Configuration:**
- **Makefile:** Use a Makefile to automate build, test, and deployment tasks.
- **Build Scripts:** Use build scripts to customize the build process.
- **CI/CD Pipeline:** Integrate your build process with a CI/CD pipeline (e.g., AWS CodePipeline, Jenkins).
- **7.3 Linting and Formatting:**
- **Linters:** Use linters (e.g., ESLint, Pylint) to enforce code style and identify potential errors.
- **Formatters:** Use formatters (e.g., Prettier, Black) to automatically format your code.
- **Editor Integration:** Integrate linters and formatters with your code editor.
- **7.4 Deployment:**
- **Blue/Green Deployments:** Use blue/green deployments to minimize downtime during deployments.
- **Canary Deployments:** Use canary deployments to gradually roll out new versions of your application.
- **Rolling Updates:** Use rolling updates to gradually update ECS tasks with the new version.
- **7.5 CI/CD Integration:**
- **Automated Builds:** Automate the build process using a CI/CD pipeline.
- **Automated Tests:** Run automated tests as part of the CI/CD pipeline.
- **Automated Deployments:** Automate the deployment process using a CI/CD pipeline.