remote-apis VS Bazel

In the case of the Remote Execution/Cache API used by Bazel among others[1] at least, it's a bit more detailed. There's an "ActionCache" and an actual content-addressed cache that just stores blobs ("ContentAddressableStorage"). When you run a `gcc -O2 foo.c -o foo.o` command (locally or remotely; doesn't matter), you upload an "Action" into the action cache, which basically said "This command was run. As a result it had this stderr, stdout, error code, and these input files read and output files written." The input and output files are then referenced by the hash of their contents, in this case.

Most importantly you can look up an action in the ActionCache without actually running it. So now when another person comes by and runs the same build command, they say "Has this Action, with these inputs, been run before?" and the server can say "Yes, and the output is a file identified by hash XYZ" where XYZ is the hash of foo.o

So realistically you always some mix of "input content hashing" and "output content hashing" (the second being the definition of 'content addressable'.)

[1] https://github.com/bazelbuild/remote-apis/blob/main/build/ba...

Not only it's distributed like distcc, Bazel also provide sandboxing to ensure that environment factors does not affect the build/test results. This might not mean much for smaller use cases, but at scale with different compiler toolchains targeting different OS and CPU Architecture, the sandbox helps a ton in keeping your cache accurate.

On top of it, the APIs Bazel uses to communicate with the remote execution environment is standardized and adopted by other build tools with multiple server implementation to match it. Looking into https://github.com/bazelbuild/remote-apis/#clients, you could see big players are involved: Meta, Twitter, Chromium project, Bloomberg while there are commercial supports for some server implementations.

Finally, on top of C/C++, Bazel also supports these remote compilation / remote test execution for Go, Java, Rust, JS/TS etc... Which matters a lot for many enterprise users.

Disclaimer: I work for https://www.buildbuddy.io/ which provides one of the remote execution server implementation and I am a contributor to Bazel.

Regardless of whether you should use Bazel or not, my hope is that any future build systems attempt to adopt Bazel's remote execution protocol (or at least a protocol that is similar in spirit):

https://github.com/bazelbuild/remote-apis

In my opinion the protocol is fairly well designed.

> The thing I really would like to see is a smarter CI system. Caching of build outputs, so you don't have to rebuild the world from scratch every time. Distributed execution of tests and compilation, so you are not bottle-necked by one machine.

This is already achievable nowadays using Bazel (https://bazel.build) as a build system. It uses a gRPC based protocol for offloading/caching the actual build on a build cluster (https://github.com/bazelbuild/remote-apis). I am the author of one of the Open Source build cluster implementations (Buildbarn).

Very nice! I really like the ease-of-use of this, as well as the scale-to-zero costs. That's a tricky thing to achieve. Seems like it could become a standard path to ease the migration from local to remote builds.

If the author is interested in standardizing the same, I'd suggest implementing the REAPI protocol (https://github.com/bazelbuild/remote-apis). It should be amenable to implementing on a Lambda-esque back-end, and is already standard amongst most tools doing Remote Execution (including Bazel! Bazel+llama could be fun). And equally, it's totally usable by a distcc-esque distribution tool (recc[1] is one example) - that's also what Android is doing before they finish migrating to Bazel ([2], sadly not yet oss'd).

The main interesting challenge I expect this project to hit is going to be worker-local caching: for compilation actions it's not too bad to skip assuming the compiler is built into the container environment, but if branching out into either hermetic toolchains or data-heavy action types (like linking), fetching all bytes to the ephemeral worker anew each time may prove to be prohibitive. On the other hand, that might be a nice transition point to switch to persistent workers: use a lambda backed solution for the scale-to-0 case, and switch execution stacks under the hood to something based on reused VMs when hitting sufficient scale that persistent executors start to win out.

(Disclaimer: I TL'd the creation of this API, and Google implementation of the same).

[1] https://gitlab.com/BuildGrid/recc

[2] https://opensource.googleblog.com/2020/11/welcome-android-op...

Wow, if you curl it, there's a lot of boilerplate code there.

Maybe built using Bazel?

https://bazel.build

Bazel by Google

Luckily a feature to limit the disk cache size is in development: https://github.com/bazelbuild/bazel/issues/5139

This is a problem that Bazel (https://bazel.build) solves in a very convenient way. You can just keep using the paths relative to the repository root, and as long as you properly declare your test needs that file it will access it without problems. Or you can use the runfile libraries to access them too.

When doing research for this lab exercise I looked at both vcpkg and conan. Both are package managers that would automate the installation and configuration of my program with its dependencies. However, when it came to releasing and sharing my program my options were limited. For example, the central public registry for conan packages is conan-center, but these packages are curated and the process is very involved. There was no way conan-center would accept a class project like mine. Alternatively, I could host a conan package on a public Artifactory repository, but accessing the package requires users to add the repository to their conan remote. This already sounded like too many steps to expect regular users to follow - I already haven't setup any conan remotes, there's no way I could expect regular users to know about conan remotes, let alone have conan installed on their system. After discussing with people online and consulting my instructor, I ultimately decided to do a GitHub release. However, in the future I was encouraged to look into using CMake or bazel.

NOTE: I won’t mention SBT and Leiningen here because, with all due respect, they are niche build tools. I also won’t discuss Kobalt for the same reason (besides, it’s no longer actively maintained). Additionally, I won’t touch upon Bazel and Buck in this context, mainly because I’m not very familiar with them. If you have insights or comments about these tools, please feel free to share them in the comments 👇

> None of this solves C's only REAL problem (in my opinion) which is the lack of dependency management.

Bazel solves this really nicely, I know some people have strong opinions on it but I cannot recommend it enough

https://bazel.build/