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ADR011 - Use Containerization with Docker for Cloud Run Deployment

Status

Accepted

Context and Problem Statement

Containerizing applications using Docker ensures consistent deployments by encapsulating application dependencies and environments. Google Cloud Run, a fully managed serverless platform, simplifies the orchestration and deployment of containerized applications, removing the need for managing Kubernetes clusters.

Requirements

  • Consistent application deployment across development, staging, and production environments.
  • Scalable and serverless orchestration for containerized services.
  • Minimize operational overhead for managing infrastructure.
  • Ensure compatibility with existing development workflows.

Business or Technical Assumptions

  • Docker will be used to containerize applications, packaging all dependencies into a single artifact.
  • Cloud Run will handle the orchestration, scaling, and deployment of containerized services.

Decision Drivers

  • Deployment consistency and reliability.
  • Scalability and automatic handling of traffic spikes.
  • Reduced operational complexity with managed orchestration.
  • Cost efficiency, with pay-per-use pricing.

Considered Options

1. Docker with Cloud Run (Selected Option)

  • Advantages: Simplifies deployment with a serverless model, ensuring scalability and reliability without managing clusters.
  • Disadvantages: Limited control over infrastructure configuration compared to self-managed solutions like Kubernetes.

2. Docker with Kubernetes (GKE)

  • Advantages: Provides full control over orchestration, supports more complex workloads.
  • Disadvantages: Overkill for the project's needs, increases operational complexity.

3. Traditional Deployment Without Containers

  • Advantages: Simpler for small-scale applications without dynamic scaling needs.
  • Disadvantages: Lacks consistency, scalability, and flexibility provided by containerization.

Decision

Docker will be used for containerizing applications, creating artifacts for deployment on Google Cloud Run. This approach ensures consistency in deployments while leveraging the scalability and simplicity of a serverless orchestration platform.

Reasons

  • Docker encapsulates dependencies, ensuring consistent application behavior across environments.
  • Cloud Run eliminates the need to manage servers or orchestration infrastructure, reducing operational burden.
  • Automatic scaling supports traffic spikes without manual intervention, aligning with project scalability needs.

Consequences

Positive Impacts

  • Simplified deployment process with minimal operational overhead.
  • Scalable architecture that automatically adjusts to demand.
  • Consistent application behavior across development, staging, and production environments.
  • Improved developer productivity by focusing on application logic rather than infrastructure management.

Trade-offs and Limitations

  • Limited control over infrastructure and orchestration compared to Kubernetes.
  • Cloud Run's serverless nature may impose restrictions on non-HTTP workloads or applications requiring long-running processes.
  • Potential vendor lock-in with reliance on Google Cloud's managed services.

Implementation Notes

  • Build Docker images for each service, including all dependencies.
  • Deploy Docker containers to Google Cloud Run, configuring necessary environment variables and runtime settings.
  • Monitor resource usage and scaling behavior using Cloud Run's built-in monitoring tools.
  • Regularly update Docker images to ensure security patches and application updates are deployed efficiently.