GitHub API is actually quite tricky here because there is a different between “comment” and “review” and “review comment” (paraphrasing, I don’t remember the details). So it’s not as simple as one API call that grabs the markdown. Of course you can write a creative one-liner to extract what you need, though.
If the DNS resolution call blocks the thread, then you need N worker threads to perform N DNS calls. Threads aren’t free, so this is suboptimal. OTOH some thread pools e.g. libdispatch on Apple operating systems will spawn new threads on demand to prevent starvation, so this _can_ be viable. Though of course this can lead to thread explosion which may be even more problematic depending on the use case. In libcurl’s situation, spawning a million threads is probably even worse than a memory leak, which is worse than long timeouts.
In general, what you really want is for the API call to be nonblocking so you’re not forced to burn a thread.
This is an interesting point. Hangs usually cost $ from user experience, with serverless they cost $ from compute. All the more reason to set strict deadlines on all API calls!
Not that difficult, but it’s still a separate dependency (with python requirements). If the goal here is a Caddy competitor, then IMO it’s missing the mark in terms of “one stop shop”. What’s the killer feature?
- containers are each isolated in a VM (aka virtualized)
- workloads are not homogenous and change often (your neighbor today may not be your neighbor tomorrow)
I believe these are fair assumptions if you’re running on generic infrastructure with kubernetes.
In this setup, my concerns are pretty much noisy neighbors + throttling. You may get latency spikes out of nowhere and the cause could be any of:
- your neighbor is hogging IO (disk or network)
- your database spawned too many threads and got throttled by CFS
- CFS scheduled your DBs threads on a different CPU and you lost your cache lines
In short, the DB does not have stable, predictable performance, which are exactly the characteristics you want it to have. If you ran the DB on a dedicated host you avoid this whole suite of issues.
You can alleviate most of this if you make sure the DB’s container gets the entire host’s resources and doesn’t have neighbors.
Agreed, but if you’re asking for a solution that will generate a spec from your code, the more proven path is to generate code from a spec. Gives you more and costs less.
In my opinion the problem is that there’s some APIs that are impossible to represent with OpenAPI — that’s the real challenge they should be solving with this version, not reducing spec line count.
I suspect OpenAPI advocates would argue you should start with the spec and use it to generate both the client and server. This is already a common pattern in other RPC definition languages such as gRPC. You _could_ write a server to match the gRPC spec, but why would you?