closes#1801closes#1815closes#1144
closes #983
closes #557closes#1827
regression of #1791
# TODO
- [x] adjust log model
- [x] add migration for logs
- [x] send log line via grpc using step-id
- [x] save log-line to db
- [x] stream log-lines to UI
- [x] use less structs for log-data
- [x] make web UI work
- [x] display logs loaded from db
- [x] display streaming logs
- [ ] ~~make migration work~~ -> dedicated pull (#1828)
# TESTED
- [x] new logs are stored in database
- [x] log retrieval via cli (of new logs) works
- [x] log streaming works (tested via curl & webui)
- [x] log retrieval via web (of new logs) works
---------
Co-authored-by: 6543 <6543@obermui.de>
This add a simple implementation of requests/limits for individual
steps. There is no validation of what the resource actually is beyond
checking that it can successfully be converted to a Quantity, so it can
be used for things other than just memory/CPU.
close#1809
closes#1181closes#834
Adds `ignore_failure` to pipeline steps. When it's set to true,
if the step fails the following steps continue to execute as if no failure had occurred.
---
failure enums idea:
* fail (default) = if other steps run in parallel, wait for them and
then let workflow fail
* cancel = if other steps run in parallel, kill them
* ignore = we mark the step as failed but it wont have any impact
at the moment we compile a script that we can pipe in as single command
this is because of the constrains the docker backend gives us.
so we move it into the docker backend and eventually get rid of it altogether
When executing a backend step, in case of failure of the specific step, the run is marked as errored but the step error is missing.
Added:
1. Log for the backend error (without trace)
2. Mark the step as errored with exit code 126 (Could not execute).
Co-authored-by: Zav Shotan <zshotan@bloomberg.net>
Co-authored-by: Anton Bracke <anton@ju60.de>
