How rqlite is tested
philipotoole.com
philipotoole.com
The first test of a class of tests is the hardest, but it's almost always worth adding. Second and subsequent tests are much easier, especially when using:
Parametrised tests let you test more things without copying boilerplate, but don't throw more variants just to get the count up. Having said that:
Exhaustive validation of constraints, when it's plausible. We have ~100k tests of our translations for one project, validating that every string/locale pair can be resolved. Three lines of code, two seconds of wall-clock time, and we know that everything works. If there are too many variants to run them all, then:
Prop tests, if you can get into them. Again, validate consistency and invariants.
And make sure that you're actually testing what you think you're testing by using mutation testing. It's great for having some confidence that tests actually catch failures.
Kotest and Spock are such frameworks.
Or Pytest, or a short shell script, or Busted, or Jest, or Node's built in test runner, or a "--selftest" flag to a variant of the native executable.
Agreed, this has been my experience too.
We're also possibly working with multiple teams on products that interact and it ends up being "nobody's job" to fill in the e2e layer for example.
Then when someone bites the bullet to get on with it....the whole thing isn't designed to be tested. e.g. how does anyone do testing with Auth0 as their auth mechanism? How do you even get a token to run an E2E type test? I have to screen scrape it which is awful.
Without those E2E tests - even just the test that you can login - the system can break and even when it's a test environment that makes the environment useless for other developers and gets in everyone's way. It becomes the victim's job to debug what change broke login and push the perpetrator to fix it. With automated e2e tests the deployment that broke something is easy to see and rollback before it does any damage.
I suppose I'm challenging the focus in a sense - I care about e2e more because some of those issues block teams from working. If you can't work because of some stupid e2e failure, you can't get fixes out for issues you found in the unit/integration tests.
If you're building a logic lite application which has a lot of integration touch points (I find most commercial code actually fits this pattern) then it makes zero sense - an integration test heavy test suite is what you want - an upside down pyramid if you will.
If you have a ball of mud on your hands then it doesnt matter what kind of app it is, E2E tests are the only thing that makes sense and you need to build very sophisticated fakes (requiring a lot of engineering skill) to avoid things like flakiness bugs and the token scraping problem you referred to.
If you're writing a parser, you probably want 100% unit tests and property tests for all those millions of parser edge cases. No pyramid of any shape is required, just a slab.
The testing pyramid reminds me of microservices: the people who came up with Their Grand Idea had no clue what it was about their specific circumstances that made their approach work for them but still managed to market it as The Way.
Realistically, the ultimate shape of your test suite should be an emergent property based upon a series of smart, local decisions - ideally TDD'ed tests which match the kind of code you are writing right now. Making a particular shape a goal is asinine.
The way things to do things is very dependent on the project. They way one maintain, debug, test e.g. a math library vs embedded sw vs a video game vs a database vs a enterprise app vs a service in a distributed system are all just different.
Almost all advice should be qualified by "in this domain, one this type of project ...".
I happen to know raft and the kind of problem it solves, but the average reader might not. A practical demonstration of the problems it solves might be in order.
So that also means describing for whicj applications rqlite is more wellsuited (and for which it might be worse) than other databases.
The section of the talk at the timestamp above is titled "Should I use Raft"?
https://github.com/wildarch/jepsen.rqlite/blob/main/doc/blog...
Always have been envious of that performance testing setup that is shown here
My motivation in adapting the bot to work with rqlite was looking for a low resistance path to higher availability. I store the small amount of state that the bot requires in rqlite and also use it to implement a simple leader election.
It's still in active use by them. https://www.textgroove.com/ is another company that uses it, though I know less about their use case.
We're still building it but we're dogfooding it and run it in production ourselves.
Can't recommend it enough
Just went through the website and read through some documents. It is quite easy to read and understand.
One part I couldn't follow was security - other than items listed (file system, HTTPS, IP based filter), is it correct to say that if you know & have access to the URL API endpoints, any query can be run directly off the db with curl or such tools? How is this aspect managed in production? Sorry if this question is inappropriate or too dumb.
You can enable BasicAuth on the HTTP endpoints. You can also require that any client presenting BasicAuth credentials has the right permission for the operation the client is trying to perform. Finally you can also enable Mutual TLS, requiring that any client that connects must first present a cert that is signed by an acceptable CA.
For full details on security check out https://rqlite.io/docs/guides/security/
(I for one didn't notice at first)
I really admire the testing that the SQLite team does[1], and the way it allows them to stand behind the statements they make about quality. It's inspiring.
IMO there have only been two really big improvements to software development relative to when I started programming professionally 25 years ago: 1) code reviews becoming mainstream, and 2) unit testing. (Perhaps Gen AI will be the third). I believe extensive testing is the only reason that rqlite continues to be developed to this day. It's not just that it helps keep the quality high, it's a key design guide. If a new module cannot be unit tested during development, in a straightforward manner, it's a strong sign one's decomposition of the problem is wrong.
Applying it to software is a logical step if you want similar levels of quality assurance.
Do you need that level of assurance for a database? Probably not in most cases. But I think it's a reasonable thing to mention on a post that is touting database reliability, especially because there are real databases that do use it.
Or if you really wanna keep the SQLite theme: https://github.com/losfair/mvsqlite
Why promote the vaporware project when comparing with something that's been in development for 10 years?
Probably because it's been in the news very recently and most people learned of DST in software from it.
The cargo culting bit is using vaporware that was just in the news cycle to shout down good work that has been done for decades.
https://github.com/rqlite/rqlite/blob/master/CHANGELOG.md#10...
2. Why Go? Go is garbage collected, how is this even a good idea for a database engine in the first place?
First, the database itself is Sqlite, which is C and arguably the most widely deployed database engine in the galaxy.
Secondly, Go is popular for network services as it's easy to write (relative to languages like C++, Rust etc), is memory-safe and is "fast enough" for the network/disk to be your bottleneck and its concurrency features make it easy to use hardware efficiently without having to worry about scheduling in your application, among other reasons.
The planet perhaps. We don't really know at the galaxy level. At best we're atleast 200k years away from knowing for sure :)
/nitpick