Shared Build Cache: Makes Sense for the Independent Developer?

What is Shared Build Cache and Why is it Important?

As independent developers, we all know that time is our most valuable asset. Each of us is constantly looking for new ways to speed up our software development processes and increase our efficiency. One of the important concepts we encounter in this quest is "build cache." Its basic logic is quite simple: when a code change is made in a project, ensure that only the changed parts or the dependencies affected by these changes are recompiled. This can save significant time, especially in large projects or complex build processes.

For system administrators or large engineering teams, this situation is relatively more understandable. Shared build cache solutions (e.g., services like Nx's build cache, Bazel's remote cache, or GitHub Actions Cache) are already standard in CI/CD pipelines. These systems ensure that multiple developers or CI agents avoid unnecessary repetitions by using a common cache when building the same project. When a developer builds a specific module, its build output is cached, and another developer or CI job pulls it from the cache instead of recompiling it. This can reduce build times that could take hours per week to minutes, especially in projects that require frequent builds.

The State of Build Cache for Independent Developers

So, how applicable are all these possibilities for individual developers? For a developer working on their own machine, perhaps alone, is it logical to use a shared build cache solution? At first glance, the word "shared" might seem to not fit this scenario. After all, who will I share it with? My own machine? However, here we need to interpret the concept of "shared" a bit more broadly. This means not just sharing within a team, but also intelligently managing build outputs in your own development environment and CI/CD processes.

For a solo developer, the main benefit of a build cache will be to shorten local build times. When making fine-tuning adjustments or adding new features to a project, recompiling only the affected parts instead of the entire project significantly speeds up the development cycle. This makes a noticeable difference, especially when working on frontend frameworks (React, Vue, Angular) or complex backend services (e.g., a project with multiple microservices). A fast feedback loop allows the developer to work more fluidly and helps them stay in a "flow" state.

ℹ️ The Basic Logic of Build Cache

The essence of build cache is to eliminate repetitive compilation operations. As long as a code block or dependency doesn't change, its pre-compiled output is used. This saves significant time, especially in large codebases and complex configurations.

At this point, the question arises: are ready-made, "shared" solutions more logical for independent developers, or should we build our own simple caching mechanisms? This can vary depending on the size of the project, the technology stack used, and how much investment the developer wants to make in their CI/CD processes. Most of the time, since the biggest cost for individual developers is time, even simple yet effective solutions can make a big difference.

Existing Shared Build Cache Solutions and Their Suitability for Independent Developers

There are various shared build cache solutions on the market, and some of them can become attractive for individual developers as well. We can categorize them into a few main groups:

1. CI/CD Platform's Own Cache Mechanisms: Services like GitHub Actions Cache, GitLab CI Cache, CircleCI Cache offer basic caching. These generally work on a file/folder basis and allow you to direct your cache to specific directories (e.g., node_modules, target, build), ensuring these directories are reused in subsequent runs.

*   **Advantages:** Relatively easy to set up, integrates with existing CI/CD infrastructure, generally free or low-cost.
*   **Disadvantages:** Doesn't provide very intelligent caching. Cache invalidation can sometimes be problematic and lead to unnecessary downloads. Cache size and retention period may be limited.

1. Dedicated Build Cache Tools (Nx, Bazel, Turborepo): Tools like Nx, Bazel, Turborepo offer more advanced and "intelligent" build cache mechanisms. Nx and Turborepo are particularly popular in monorepos and modern JavaScript/TypeScript projects. They manage the cache more intelligently by hashing the inputs and outputs of commands. Bazel is a more general-purpose and very powerful build system, but its learning curve is steeper.

*   **Advantages:** Provides much more efficient caching, can dramatically reduce build times, great for managing dependencies in monorepos.
*   **Disadvantages:** Generally requires more complex setup and configuration. Tools like Nx and Turborepo may involve an additional learning curve. Bazel can be quite complex and may require setting up your own server infrastructure (for remote cache). Bazel's remote cache feature typically requires extra costly solutions (e.g., Google Cloud Build Cache or storing in your own artifact repository).

1. Building Your Own Solution: For simple scenarios, you can set up a basic caching mechanism on your own local machine or a VPS. For example, you can store compiled files in a directory and save time by checking for the existence of this directory in subsequent builds.

*   **Advantages:** You have full control, costs can be minimized.
*   **Disadvantages:** Can become difficult to maintain over time, insufficient for complex scenarios, high probability of making mistakes.

For independent developers, trying the caching mechanisms offered by CI/CD platforms is the most logical first step. If the project grows and these simple solutions become insufficient, switching to tools like Nx or Turborepo might become more meaningful.

💡 Local Build Cache Tips

If you just want to speed up your local development environment, even correctly managing your project's dependencies (e.g., the node_modules folder) can make a big difference. Commands like npm ci or yarn install --frozen-lockfile ensure consistency by always installing from the lock file and prevent unnecessary downloads.

Cost and Performance Balance: How Logical is it for an Independent Developer?

Here, the cost factor comes into play. Individual developers are usually more sensitive about budgets. Free or very low-cost solutions are our primary preference.

• Free/Low-Cost Options: GitHub Actions' free plan offers a certain amount of CI/CD time and cache storage. This can be sufficient for most individual projects. If you are contributing to an open-source project, these types of services are usually offered generously. Setting up a simple caching server on your own VPS is also an option, but in that case, both the server cost and the maintenance burden fall on you.

• Performance Gain: The main promise of shared build cache is performance improvement. However, the extent of this improvement depends on the project's structure and build time. If your project's full compilation already takes only a few minutes, the additional savings provided by build cache might not be very dramatic. But if your project takes ten minutes or more, build cache can be a lifesaver.

For example, in a backend project I developed myself, consisting of multiple microservices, running npm install and then npm run build for each service took about 15 minutes in my CI pipeline. By using GitHub Actions Cache to cache node_modules and build outputs, this time reduced to an average of 3-4 minutes. This meant significant time savings when considering weekly deployments.

⚠️ Cache Invalidation Issues

One of the biggest challenges with build cache is correctly determining when it should be invalidated. If the cache is not updated correctly, old and erroneous compiled code can be used. This can lead to serious problems, especially when updating dependencies or dealing with complex build scripts.

From a cost perspective, the cache size (usually 5 GB) and time limitations in GitHub Actions' free tier are sufficient for most individual projects. If the project grows very large and you need more cache space, you might consider switching to additional storage offered by GitHub or more advanced CI/CD solutions. However, at this point, it's important to carefully evaluate whether the cost outweighs the practical benefit.

Technical Depth: How Build Cache Works and What to Pay Attention To

The fundamental principle behind build cache is caching outputs based on inputs. These inputs typically include:

• Source Code Files: Changed code files.
• Dependencies: Files like package.json, pom.xml, requirements.txt, and the libraries specified in these files.
• Configuration Files: Build scripts, compiler settings, files like tsconfig.json, .eslintrc.js.
• Environment Variables: Environment variables that can affect the build process.

A "hash" of these inputs is generated. If a build operation with the same hash has been performed before and its outputs are in the cache, the system retrieves these outputs from the cache instead of performing a new build.

More advanced tools like Nx take into account not only the content of the files but also information such as which commands were executed and what their outputs were. This way, for example, as long as package.json doesn't change, the node_modules folder might not need to be downloaded, or if tsconfig.json doesn't change, all the TypeScript compiler's settings might not be reprocessed.

Technical Points to Consider:

1. Cache Key Generation: This is the most critical point. The cache key must accurately represent the build process. If the key is incomplete or incorrect, the cache may be used incorrectly. For example, it's necessary to include not only the source code but also the compiler version used, the exact versions of dependencies, and configuration files in the key.

2. Cache Backend: Where the compiled outputs are stored is important. This can be the local disk, a shared network drive, an artifact repository (Nexus, Artifactory), or a dedicated build cache service. For independent developers, local disk or temporary storage provided by CI/CD platforms are generally used.

3. Cache Cleanup Strategy: Over time, the cache can grow and cause disk space issues. It's also important to clean up old cache entries that are no longer used. Most CI/CD systems do this automatically, but if you're building your own solution, you need to manage this. For example, deleting caches older than a certain period or triggering automatic cleanup when a certain size is exceeded.

4. Consistency in Distributed Systems: If multiple build agents are running simultaneously, consistency issues can arise when accessing and updating the cache. This is usually resolved with locking mechanisms or atomic operations, but for individual developers, this is generally not an issue.

🔥 Risks of Incorrect Cache Usage

An incorrectly configured build cache is one of the most dangerous things. If the cache key is not generated properly or the cache is not invalidated correctly, your CI/CD pipelines may produce erroneous builds unexpectedly. Detecting these errors can sometimes take hours. Such an error, especially in production deployments, can have serious consequences.

Real Scenarios and Lessons Learned

I've had several experiences with build cache in my own projects and in environments where I've worked.

For a backend service I developed for an e-commerce site, it was written in Node.js and used TypeScript. As the project grew, npm install and tsc (TypeScript compiler) commands took about 10 minutes in total. In GitHub Actions, I used the actions/cache action to cache the node_modules folder and the dist folder (where the compiled JavaScript files are located).

Initially, everything was going well. Our cache hit rate was over 80%, and build times reduced to an average of 2-3 minutes. However, after a while, problems started to emerge with an update to a specific dependency. The new dependency was incompatible with the old cached dist files. But our cache key wasn't capturing the changes in package-lock.json precisely enough. As a result, the pipeline sometimes used old compiled files, leading to runtime errors.

To solve this problem, I made the cache key more detailed. I included not only package-lock.json but also tsconfig.json and even a hash of the content of all .js, .ts, .json files used in the project as part of the key. This slightly reduced the cache hit rate (to around 75%), but it made the cache much more reliable. Runtime errors caused by using old compiled files were completely eliminated.

In another example, I used the Nx tool, working in a monorepo structure. Nx's own build cache mechanism was quite advanced. It intelligently managed dependencies between different services and libraries. When a service changed, it would recompile only that service and the other modules it directly depended on. This was far superior to previous manual cache management approaches. However, when I wanted to use Nx's remote cache feature, I had to either set up an additional service or use a third-party artifact repository. For an individual developer, this introduced additional cost and complexity. Therefore, I contented myself with using Nx's local cache in my local development environment.

The main lessons I've learned from these experiences are:

• Start Simple: Especially for individual developers, the basic caching mechanisms offered by CI/CD platforms are usually sufficient.
• Cache Key Accuracy: When generating the cache key, account for as many inputs as possible (code, dependencies, configurations).
• Test, Test, Test: Regularly perform tests to ensure the cache is working correctly and observe its behavior in different scenarios.
• Consider the Cost: Think about whether the performance improvement brought by advanced solutions justifies the additional cost.

Conclusion: Is Shared Build Cache a Luxury or a Necessity for the Independent Developer?

For an independent developer, the concept of "shared" build cache means maximizing efficiency in their own development and CI/CD processes, rather than traditional team sharing. As we've examined throughout this post, shared build cache solutions can offer significant benefits, especially for shortening local build times and speeding up CI/CD pipelines.

In terms of cost and complexity, the most logical path for individual developers usually starts with using the free or low-cost cache features offered by existing CI/CD platforms. Solutions like GitHub Actions Cache, when configured correctly, can provide a noticeable improvement in build times without incurring additional costs. If the project grows and these basic solutions become insufficient, switching to more advanced tools like Nx or Turborepo can be considered, but the additional learning curve and potential costs should be taken into account.

Based on my own experiences, I can say that the time savings provided by build cache are too significant to ignore for independent developers who compile frequently and actively use CI/CD processes. This not only allows you to deploy faster but also makes your development cycle more fluid, freeing up more space for your creativity. Therefore, it is beneficial to view shared build cache not as a luxury, but as an important part of modern development practices.

The next step is to identify and implement the cache strategy that best suits your project's needs.

Comments

[Andy Nian]

Reducing build times with a shared build cache sounds great, but for independent developers, it's worth questioning if the setup complexity is worth the benefits. The article mentions GitHub Actions Cache significantly cutting build times, but if your project already builds quickly, the effort might not be justified. I've been focusing more on system design prep lately and found prachub.com has solid resources for those technical screens—much better than going through endless forum threads. Maybe instead of getting into complex caching setups, time could be better spent improving other areas of development efficiency.