mirror of
https://git.deuxfleurs.fr/Deuxfleurs/garage.git
synced 2024-11-29 19:41:00 +00:00
75 lines
3.7 KiB
Markdown
75 lines
3.7 KiB
Markdown
+++
|
|
title = "Testing strategy"
|
|
weight = 30
|
|
+++
|
|
|
|
|
|
## Testing Garage
|
|
|
|
Currently, we have the following tests:
|
|
|
|
- some unit tests spread around the codebase
|
|
- integration tests written in Rust (`src/garage/test`) to check that Garage operations perform correctly
|
|
- integration test for compatibility with external tools (`script/test-smoke.sh`)
|
|
|
|
We have also tried `minio/mint` but it fails a lot and for now we haven't gotten a lot from it.
|
|
|
|
In the future:
|
|
|
|
1. We'd like to have a systematic way of testing with `minio/mint`,
|
|
it would add value to Garage by providing a compatibility score and reference that can be trusted.
|
|
2. We'd also like to do testing with Jepsen in some way.
|
|
|
|
## How to instrument Garagae
|
|
|
|
We should try to test in least invasive ways, i.e. minimize the impact of the testing framework on Garage's source code. This means for example:
|
|
|
|
- Not abstracting IO/nondeterminism in the source code
|
|
- Not making `garage` a shared library (launch using `execve`, it's perfectly fine)
|
|
|
|
Instead, we should focus on building a clean outer interface for the `garage` binary,
|
|
for example loading configuration using environnement variables instead of the configuration file if that's helpfull for writing the tests.
|
|
|
|
There are two reasons for this:
|
|
|
|
- Keep the soure code clean and focused
|
|
- Test something that is as close as possible as the true garage that will actually be running
|
|
|
|
Reminder: rules of simplicity, concerning changes to Garage's source code.
|
|
Always question what we are doing.
|
|
Never do anything just because it looks nice or because we "think" it might be usefull at some later point but without knowing precisely why/when.
|
|
Only do things that make perfect sense in the context of what we currently know.
|
|
|
|
## References
|
|
|
|
Testing is a research field on its own.
|
|
About testing distributed systems:
|
|
|
|
- [Jepsen](https://jepsen.io/) is a testing framework designed to test distributed systems. It can mock some part of the system like the time and the network.
|
|
- [FoundationDB Testing Approach](https://www.micahlerner.com/2021/06/12/foundationdb-a-distributed-unbundled-transactional-key-value-store.html#what-is-unique-about-foundationdbs-testing-framework). They chose to abstract "all sources of nondeterminism and communication are abstracted, including network, disk, time, and pseudo random number generator" to be able to run tests by simulating faults.
|
|
- [Testing Distributed Systems](https://asatarin.github.io/testing-distributed-systems/) - Curated list of resources on testing distributed systems
|
|
|
|
About S3 compatibility:
|
|
- [ceph/s3-tests](https://github.com/ceph/s3-tests)
|
|
- (deprecated) [minio/s3verify](https://blog.min.io/s3verify-a-simple-tool-to-verify-aws-s3-api-compatibility/)
|
|
- [minio/mint](https://github.com/minio/mint)
|
|
|
|
About benchmarking S3 (I think it is not necessarily very relevant for this iteration):
|
|
- [minio/warp](https://github.com/minio/warp)
|
|
- [wasabi-tech/s3-benchmark](https://github.com/wasabi-tech/s3-benchmark)
|
|
- [dvassallo/s3-benchmark](https://github.com/dvassallo/s3-benchmark)
|
|
- [intel-cloud/cosbench](https://github.com/intel-cloud/cosbench) - used by Ceph
|
|
|
|
Engineering blog posts:
|
|
- [Quincy @ Scale: A Tale of Three Large-Scale Clusters](https://ceph.io/en/news/blog/2022/three-large-scale-clusters/)
|
|
|
|
Interesting blog posts on the blog of the Sled database:
|
|
|
|
- <https://sled.rs/simulation.html>
|
|
- <https://sled.rs/perf.html>
|
|
|
|
Misc:
|
|
- [mutagen](https://github.com/llogiq/mutagen) - mutation testing is a way to assert our test quality by mutating the code and see if the mutation makes the tests fail
|
|
- [fuzzing](https://rust-fuzz.github.io/book/) - cargo supports fuzzing, it could be a way to test our software reliability in presence of garbage data.
|
|
|
|
|