Monorepo vs Polyrepo: Real-World Trade-offs for Small Teams

Monorepos and polyrepos: the age-old debate. At MisuJob, we’ve wrestled with this decision firsthand, and we’re here to share our real-world experiences, including the unexpected benefits and painful gotchas, to help you choose the right strategy for your team.

Monorepo vs Polyrepo: Real-World Trade-offs for Small Teams

Choosing between a monorepo and a polyrepo architecture is a fundamental decision that impacts every aspect of your software development lifecycle. While larger organizations often tout the benefits of monorepos, the reality for smaller teams operating in a fast-paced environment, like ours at MisuJob, is far more nuanced. We’ll delve into the pros and cons of each approach, focusing on the specific trade-offs we’ve encountered while building a platform that processes 1M+ job listings and aggregates from multiple sources to provide AI-powered job matching across Europe.

Understanding the Definitions

Before diving into the specifics, let’s define our terms:

• Monorepo: A single repository containing multiple projects, libraries, and applications. Think of it as a single source of truth for all your codebase.

• Polyrepo: Multiple repositories, each containing a single project, library, or application. Each component lives in its own isolated world.

Our Journey: Initial Polyrepo Setup

Initially, we adopted a polyrepo architecture. It seemed logical. Each microservice that powered MisuJob’s features, like the AI-powered job matching algorithm or the API gateway, had its own repository. This approach offered a clear separation of concerns and seemingly simplified deployments.

However, as we scaled and our codebase grew, the cracks began to show. Dependency management became a nightmare, coordinating releases was a logistical challenge, and refactoring across services felt like navigating a minefield.

The Siren Song of the Monorepo

The allure of the monorepo, with its promise of simplified dependency management, atomic changes, and code reuse, became increasingly tempting. We started exploring tools like Bazel and Nx to manage the complexity of a monorepo.

The Monorepo Experiment: A Qualified Success

We decided to migrate a subset of our services into a monorepo. This included our core data processing pipeline and several shared libraries. Here’s what we learned:

Pros:

• Simplified Dependency Management: No more version conflicts or compatibility issues between services. Upgrading a shared library meant a single change that propagated across all dependent projects. This drastically reduced our dependency management overhead. Example:

  // Before (polyrepo - multiple package.json files)
  {
    "dependencies": {
      "shared-lib": "1.2.3"
    }
  }
  
  // After (monorepo - single package.json at the root)
  {
    "dependencies": {
      "shared-lib": "*" // or a more specific version range
    }
  }
  

• Atomic Changes: We could now make changes that spanned multiple services in a single commit, ensuring consistency and reducing the risk of integration issues. Imagine refactoring a data model used by both the data processing pipeline and the API. In a polyrepo, this would involve multiple pull requests and careful coordination. In a monorepo, it’s a single atomic change.

• Code Reuse: Sharing code between services became trivial. We extracted common functionalities into shared libraries, reducing code duplication and improving maintainability.

• Improved Visibility: Having all the code in one place made it easier to search, understand, and debug the entire system.

Cons:

• Increased Build Times: Building the entire monorepo took significantly longer than building individual repositories. This was a major pain point, especially during development. We had to invest heavily in build optimization and caching strategies.

• Steeper Learning Curve: Tools like Bazel and Nx have a steep learning curve. It took time for the team to become proficient in using them effectively.

• Code Ownership Concerns: It’s easy to step on each other’s toes when everyone has access to everything. We had to establish clear code ownership guidelines and enforce them through code reviews.

• Repository Size: The repository grew rapidly, making cloning and fetching updates slower.

Addressing the Challenges

To mitigate the challenges, we implemented several strategies:

• Incremental Builds: We configured our build system to only rebuild the parts of the monorepo that were affected by a change. This significantly reduced build times.

• Remote Caching: We used remote caching to share build artifacts between developers and CI/CD pipelines.

• Code Ownership Enforcement: We used code review tools to ensure that changes were reviewed by the appropriate owners.

• Directory Structure: We adopted a clear directory structure to organize the codebase and make it easier to navigate. For example:

  /
  ├── apps/            # Applications (e.g., API, web app)
  │   ├── api/
  │   └── web/
  ├── libs/            # Shared libraries
  │   ├── ui/
  │   ├── data/
  │   └── utils/
  └── tools/           # Build and development tools
  

The Hybrid Approach: Our Current Strategy

Ultimately, we adopted a hybrid approach. We keep our core data processing pipeline, shared libraries, and some internal tools within a monorepo. Services with a high degree of autonomy and independent release cycles remain in their own repositories. This allows us to leverage the benefits of both architectures while mitigating their drawbacks.

Data-Driven Decision Making: Performance Metrics

We constantly monitor the performance of both our monorepo and polyrepo services. Here are some key metrics we track:

These numbers clearly show the trade-offs. Monorepo services have longer build times but benefit from faster bug resolution, higher deployment frequency, and increased code reuse.

Salary Implications: Specialization vs. Generalization

Interestingly, the choice between monorepo and polyrepo can also impact salary expectations for engineers. Engineers working in a monorepo environment often need a broader understanding of the entire system, while those in a polyrepo environment may specialize in a specific service or technology.

Here’s a rough comparison of salary ranges for engineers with 5+ years of experience, based on our observations across Europe (all figures in EUR per year):

While these are just indicative ranges, they suggest that generalist engineers with experience in monorepo environments may command a slight premium due to the broader skillset required. MisuJob uses this data to help professionals understand their market value and negotiate competitive salaries.

Practical Advice: Making the Right Choice

Here’s our advice, based on our experiences, for making the right choice for your team:

1. Assess Your Team Size and Complexity: If you have a small team and a relatively simple codebase, a polyrepo might be sufficient. As your team and codebase grow, consider migrating to a monorepo, or a hybrid approach.
2. Consider Your Deployment Requirements: If you need to deploy services independently and frequently, a polyrepo might be a better choice. If you can tolerate longer deployment cycles, a monorepo can simplify dependency management and ensure consistency.
3. Invest in Tooling: Whether you choose a monorepo or a polyrepo, invest in tooling to automate builds, deployments, and dependency management.
4. Establish Clear Code Ownership: Define clear code ownership guidelines to prevent conflicts and ensure accountability.
5. Monitor Performance: Continuously monitor the performance of your build and deployment pipelines to identify bottlenecks and optimize your architecture.
6. Start Small: If you’re considering a monorepo, start by migrating a small subset of your services to it. This will allow you to learn the ropes and avoid overwhelming your team.

Example: Implementing Feature Flags

Regardless of your repo strategy, feature flags are a crucial tool for modern development. Here’s how we use them to manage releases, regardless of whether the code lives in a monorepo or polyrepo:

# Python example (using a feature flag library)
import feature_flags

def calculate_discount(user_id, product_price):
  """Calculates the discount based on user and product."""

  if feature_flags.is_enabled("new_discount_algorithm", user_id):
    discount = product_price * 0.15  # 15% discount
    print("Using new discount algorithm")
  else:
    discount = product_price * 0.10  # 10% discount
    print("Using old discount algorithm")
  return discount

# Example usage
user_id = "user123"
product_price = 100
discount = calculate_discount(user_id, product_price)
print(f"Discount: {discount}")

This allows us to test new features in production without impacting all users. If issues arise, we can simply disable the flag.

Database Migrations: A Common Pitfall

Database migrations are another area where monorepos and polyrepos diverge. In a polyrepo, each service typically has its own database schema and migration scripts. This can lead to inconsistencies if services need to share data. In a monorepo, it’s easier to manage database migrations centrally and ensure consistency across all services. Here’s an example using flyway in a monorepo context:

# Bash script to apply Flyway migrations
#!/bin/bash

FLYWAY_USER="your_db_user"
FLYWAY_PASSWORD="your_db_password"
FLYWAY_URL="jdbc:postgresql://your_db_host:5432/your_db_name"

flyway -url="$FLYWAY_URL" -user="$FLYWAY_USER" -password="$FLYWAY_PASSWORD" migrate

This script can be part of a CI/CD pipeline, ensuring that database migrations are applied automatically during deployments.

Conclusion

The choice between a monorepo and a polyrepo is not a binary one. The best approach depends on your specific needs and constraints. We’ve found that a hybrid approach, combining the benefits of both architectures, works best for us at MisuJob. Remember to continuously monitor your performance, adapt your strategy as needed, and prioritize the needs of your team.

Key Takeaways:

• Monorepos simplify dependency management and enable atomic changes but can increase build times and introduce code ownership concerns.
• Polyrepos offer greater isolation and faster build times but can lead to dependency conflicts and code duplication.
• A hybrid approach can be the best of both worlds, allowing you to leverage the benefits of both architectures.
• Invest in tooling to automate builds, deployments, and dependency management.
• Continuously monitor your performance and adapt your strategy as needed.
• Engineers in monorepo environments often require a broader skillset and may command slightly higher salaries.