The third argument to `open()` in `-|` mode is passed to a shell if it's
a string. In my case the store URI contains
`?secret-key=${signingKey.directory}/secret&compression=zstd`
For the `nix store cat` case this means that
* until `&` the process will be started in the background. This fails
immediately because no path to cat is specified.
* `compression=zstd` is a variable assignment
* the `$path` argument to `store cat` is attempted to be executed as
another command
Passing just the list solves the problem.
`dev-notes` are severely outdated. I dropped everything except one note
that I moved to hacking.md. The parts about creating users are also
covered elsewhere.
The `update-dbix` part got a just command to make it discoverable again.
* justfile, inspired from Lix.
* let foreman use the stuff from outputs, similar to what Lix does>
* mess around with PERL5LIB[1] and PATH to get tests running locally.
[1] I don't really know how `Setup` was found before tbh.
When an artifact is requested from hydra the output is first copied
from the nix store into memory and then sent as a response, delaying
the download and taking up significant amounts of memory.
As reported in https://github.com/NixOS/hydra/issues/1357
Instead of calling a command and blocking while reading in the entire
output, this adds read_into_socket(). the function takes a
command, starting a subprocess with that command, returning a file
descriptor attached to stdout.
This file descriptor is then by responsebuilder of Catalyst to steam
the output directly
The primary host for this repo isn't github, and this is causing a whole
bunch of false indications in the Lix Forgejo UI as it tries to run the
.github/workflow with non-existing runners.
Only log issues/failures when something's actually up.
It has irked me for a long time that so much output came
out of running the tests, this seems to silence it.
It does hide some warnings, but I think it makes the output
so much more readable that it's worth the tradeoff.
Helps for highly parallel running of jobs, sometimes they'd not give output for a while.
Setting this timeout higher appears to help.
Not completely sure if this is the right place to do it, but it works fine for me.
We've seen many fails on ofborg, at lot of them ultimately appear to come down to
a timeout being hit, resulting in something like this:
Failure executing slapadd -F /<path>/slap.d -b dc=example -l /<path>/load.ldif.
Hopefully this resolves it for most cases.
I've done some endurance testing and this helps a lot.
some other commands also regularly time-out with high load:
- hydra-init
- hydra-create-user
- nix-store --delete
This should address most issues with tests randomly failing.
Used the following script for endurance testing:
```
import os
import subprocess
run_counter = 0
fail_counter = 0
while True:
try:
run_counter += 1
print(f"Starting run {run_counter}")
env = os.environ
env["YATH_JOB_COUNT"] = "20"
result = subprocess.run(["perl", "t/test.pl"], env=env)
if (result.returncode != 0):
fail_counter += 1
print(f"Finish run {run_counter}, total fail count: {fail_counter}")
except KeyboardInterrupt:
print(f"Finished {run_counter} runs with {fail_counter} fails")
break
```
In case someone else wants to do it on their system :).
Note that YATH_JOB_COUNT may need to be changed loosely based on your
cores.
I only have 4 cores (8 threads), so for others higher numbers might
yield better results in hashing out unstable tests.
Lost in the h-e-j -> n-e-j migration, causing evaluation to always be
single threaded and limited to 4GiB RAM. Follow the config settings like
h-e-j used to do (via C++ code).
There are some known regressions regarding local testing setups - since
everything was kinda half written with the expectation that build dir =
source dir (which should not be true anymore). But everything builds and
the test suite runs fine, after several hours spent debugging random
crashes in libpqxx with MALLOC_PERTURB_...
The current way this whole build works is incompatible with having a
separate build dir, or at least with having a separate build dir. To be
improved in the future - maybe minimize the dependencies a bit. But this
isn't so much data that we really have to care.
New jobs have their "new" status take precedence over them being
"failed" or "queued", which means actions that can act on "failed" or
"queued" jobs weren't shown to the user when they could only act on
"new" jobs.
- Use extra-trusted-users to avoid overriding the default set of trusted
users and causing permission issues.
- Add hydra and hydra-www users which also need permissions.
nix-eval-jobs streams output, unlike hydra-eval-jobs. Now that we've
migrated, we can use this to:
1. Use less RAM by avoiding buffering a whole eval's worth of metadata
into a Perl string and an array of JSON objects.
2. Make evals latency a bit lower by allowing the queue runner to start
ingesting builds faster.
The feature cannot easily be ported to nix-eval-jobs since it requires
deep integration into the evaluator, and h.n.o doesn't use it. Later
more of this will be ripped out.
Nixpkgs only contains a `hydra_unstable`, not `hydra`, package, so
adjust the default accordingly, and then override it to our package in
the separate module which does that.
(cherry picked from commit e149da7b9bbc04bd0b1ca03fa0768e958cbcd40e)
Due to newer nixpkgs, there were a number of things that could be
cleaned up in the process.
(cherry picked from commit 743795b2b090a5cdfe8bd90120add8db7770086a)
This was the source of a flaky test because sometimes hydra-notify was
quick enough to send out `buildStarted` and sometimes it apparently
wasn't which was quickly spottable with `nix build --rebuild`.
Removing that status update doesn't make a difference functionally,
gitea doesn't differentiate between "queued" and "running", so we send
the same status ("pending") out on both events, so we'd even safe one
avoidable request.
(cherry picked from commit 806c375c338b4e6a1d276b96994018908784bf11)
This is an integration test that confirms that jobset definitions from
git repositories are correctly built and status updates pushed to the
gitea instance. The following things needed to be fixed:
* We're still on 23.05 where gitea is marked as insecure. Not going to
update nixpkgs right now, but going for the quick fix.
* Since gitea 1.19 tokens have scopes that describe what's possible.
Not specifying the scope in the DB appears to imply that no
permissions are granted.
* Apparently we have three status updates now (for three status hooks,
queued/started/finished). No idea why that was broken before, but the
behavior still looks correct.
(cherry picked from commit ceff5c5cfeaf211691f4d1156f358a940b5ef7b4)
Instead of just going for "whatever is the oldest build we know of",
use the following first:
- Is the step more constrained? If so, schedule it first to avoid
filling up "more desirable" build slots with less constrained builds.
- Does the step have more dependents? If so, schedule it first to try
and maximize open parallelism and breadth of scheduling options.
This allows for better builder usage when the queue runner is busy. To
avoid running into uncontrollable imbalances between builder/queue
runner, we only release the machine reservation after the local
throttler has found a slot to start copying the outputs for that build.
We don't rely on sequential / monotonic build IDs processing anymore, so
randomizing actually has the advantage of mixing builds for different
systems together, to avoid only one chunk of builds for a single system
getting processed while builders for other systems are starved.
Each output for a given step being ingested is looked up in parallel,
which should basically multiply the speed of builds ingestion by the
average number of outputs per derivation.
Running the query with/without it shows that it makes no difference to
postgres, since there's an index on finished=0 already. This allows a
few simplifications, but also paves the way towards running multiple
parallel monitor threads in the future.
By looking at the ratio of running vs. waiting for the dispatcher and
the queue monitor, we should get better visibility into what hydra is
currently bottlenecked on.
There are other side effects we can try to measure to get to the same
result, but having a simple way doesn't cost us much.