Is it efficient to orchestrate a modular monolith with Docker microcontainers and automatic scaling for scalable apps?

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I’m designing an architecture in Node.js that will start as a modular monolith, where the parent monolith is a single Docker container running multiple microcontainers inside it. Each module, such as authentication or chat, will be encapsulated in its own microcontainer within this parent container. These microcontainers will follow a hexagonal architecture internally and communicate with each other through events, making the setup cloud-agnostic and implementation-independent.

The goal is to balance cost and performance while preparing for future scalability. I plan to avoid vertical scaling of the entire monolith by scaling only the modules under heavy load horizontally. To achieve this, I’m considering using a monitoring system like Grafana to detect when a module is overburdened, triggering the orchestrator to create new instances of that module's microcontainer. Over time, as demand increases, these modules would evolve into independent microservices.

Initially, I plan to deploy this setup on Hetzner due to their low instance costs. As the application scales, I intend to convert heavily-used modules into standalone microservices.

I haven’t implemented this yet, but I’m curious if this approach would be efficient in terms of cost and performance, especially as I plan to launch multiple apps or developments. Is this model of orchestration and automatic scaling within a Docker container viable for achieving future scalability?

asked 2 months ago63 views
1 Answer
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Your idea of using a modular monolith approach with Docker microcontainers sounds innovative and could offer some benefits, but there are a few considerations to keep in mind regarding efficiency, cost, and scalability:

Pros of Your Approach:

  • Modularization: Encapsulating different parts of your application (e.g., authentication, chat) into separate microcontainers within a parent container helps maintain a clear separation of concerns. This can make the application easier to manage and evolve over time.

  • Scalability: The idea of horizontally scaling individual modules that experience heavy load is sound. By monitoring module usage with tools like Grafana, you can dynamically adjust the number of instances running, which can help balance load and improve performance.

  • Future-Proofing: Starting with a modular monolith allows you to refine your application's architecture without the complexity of full microservices. As the demand for certain features grows, these modules can be split off into independent microservices, making the transition smoother.

  • Cloud-Agnostic: Using Docker containers makes your setup portable across different cloud providers, aligning well with the goal of being cloud-agnostic.

Challenges and Considerations:

  • Overhead of Microcontainers: Running multiple Docker containers inside a parent container may introduce unnecessary complexity and overhead. Each container has its own runtime, which could lead to increased memory and CPU usage. Managing these microcontainers could also become challenging as the number of modules grows.

  • Networking and Communication: Ensuring efficient communication between microcontainers, especially if they are inside a parent container, can be tricky. You'll need a robust event-driven communication mechanism. Using internal networks in Docker can help, but it adds another layer to manage.

  • Monitoring and Orchestration Complexity: While using Grafana for monitoring is great, the logic to automatically scale specific microcontainers based on load will need careful planning. Orchestrating these actions efficiently without causing downtime or resource contention is key.

  • Resource Utilization: Running multiple microcontainers within a parent container could lead to resource contention. You may need to fine-tune resource allocation and limits for each microcontainer to avoid one module hogging resources and impacting others.

  • Scaling Strategy: As you mentioned, as demand grows, some modules will turn into standalone microservices. This transition will require careful planning, especially in terms of data consistency, API contracts, and maintaining backward compatibility.

Is This Approach Viable?

Your approach could be viable, especially for small to medium-sized applications where the cost of managing full microservices from the start isn't justified. Starting with a modular monolith allows you to benefit from the simplicity of monoliths while preparing for scalability.

However, consider these points:

  • Avoid Nested Containers: Instead of running microcontainers inside a parent container, consider deploying each module as a separate container. This can simplify your architecture and make scaling more straightforward. Use an orchestration tool like Kubernetes, which can handle the lifecycle of containers and scaling more efficiently.

  • Focus on Monitoring and Automation: Build a robust monitoring and alerting system. Automate as much as possible, from scaling to deployment, to avoid manual interventions.

  • Plan for the Transition to Microservices: Have a clear plan and timeline for when and how modules will transition into microservices. This includes database separation, API management, and inter-service communication.

Your approach is creative and aligns with modern software architecture trends. By focusing on modularization and planning for future scalability, you are setting a solid foundation. Just be mindful of the potential complexities and overheads. As your application grows, transitioning to a more traditional microservices architecture using orchestration tools like Kubernetes may offer better efficiency and scalability.

For further reading and to refine your strategy, you might look into 12-Factor App Methodology and Microservices best practices https://12factor.net/ These resources provide insights into designing scalable and maintainable applications.

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answered 2 months ago
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