abatilo
Born on January 09, 2017•253 Karma
More broadly, a lot of other command line utils for transforming input have such an emphasis on terseness that I sort of bounce off of them. awk and sed and jq are all super powerful tools, but I wanted a tool that had a more balanced trade-off of characters vs. clarity.
I'll sometimes chat with the people who have had to maintain whatever ground work I had laid, and each time around, I get a little bit better at laying down a framework of infrastructure and operations that's better and better at staying sustainable
> including running your tests, "thankfully", we use maven which means that our tests are part of the build lifecycle. It's a bit annoying because our CI provider has some neat parallelism stuff that we could lean on if we could separate out the test phase from the build phase. We use docker-compose inside our builders for dev dependencies (we run our tests against a real database running in docker) but I think they should be our only major issues here.
But, Thanks for the heads up.
It's been years that writing Dockerfiles has been fairly common. Years. And yet it's still so common that people write such poorly optimized Dockerfiles.
I think we should definitely start thinking about admitting that it's too much over head for people to learn how to write a Dockerfile.
That being said, I've known Kyle for a while now. The team at Depot have consistently shown the deepest possible understanding of the container ecosystem. I'm very excited to see what else they do.
I'm not officially affiliated with them at all. But I'm a big fan of their product.
It appears that one difference though is that Depot is more focused on just docker builds and y'all are more generalized runners Is that right?
So you'll get that goodness when running CI with zero changes to your actions needed.
In other words, they're used when you want to share some kind of state across all of the computers, without the potential overhead of communicating to some other system like a database.
Physics simulations and like, molecular modeling come to mind as common examples.
In the case of ML training, model parameters and broadcasting the deltas that get calculated during training are that shared state.