This commit fixes various issues with run executions, including a pretty gnarly memory bloat issue when resuming a run that had a decent number of completed tasks (e.g. anything over a few). Other issues fixed:
- Run executions no longer are bound to a queue, which will allow more parallel runs in a single job (instead of 1).
- Serverless function timeouts (504) errors are now handled better, and no longer are retried using the graphile worker failure/retry mechanism (causing massive delays).
- Fixed the job_key design of the performRunExecutionV2 task, which will ensure resumed runs are executed
- Added a mechanism to measure the amount of execution time a given run has accrued, and added a maximum execution duration on the org to be able to limit total execution time for a single run
* WIP job run performance improvements
- Added a `perf` tool to better measure job run performance under heavy load
- Removed `runFinished` job (not really needed)
- startQueuedRuns now uses a jobKey with replace
- Fixed an issue with ZodWorker when using jobKey
* Publish improvement docker images
* fixed the improvement docker publishing
* Downgrade back to prisma 4.16.0 because 5.1.x broke docker builds
* Changes to how queued runs work
- Split the worker into two different workers, one dedicated to performRunExecution
- Schedule performRunExecution in a single place, with a queue and using a round robin manually controlled concurrency
- Remove startQueuedRuns
- All runs are queued before they are started
- Setting the worker maxPoolSize to the same as the worker concurrency
- Starting to be able to split the docker image
* Remove queue name from startRun graphile job
* Make the prisma connection pool stuff configurable through env vars
* Hardcode (for now) the max concurrent runs limit
* Rewrite performRunExecution to be more performant
PerformRunExecutionV2:
- Does not create and manage jobRunExecution records
- Does not reimplement retrying, uses graphile worker retrying instead
I’ve kept around PerformRunExecutionV1 so this works when deploying. Definitely needs LOTS of testing
* Fix issues with cached tasks
- Limit the size of the cached tasks sent when executing a run, using the knapsack problem dynamic programming approach
- Actually USE the cached tasks in IO by using the idempotencyKey instead of the task ID
- Remove output from all logs
- Added a stress test job catalog
* Forgot to commit the logger updates
* Never log connectionString
* Login to docker hub to get around rate limits
* Add additional logging to the graphile workers
* Fix the *_ENABLED env vars
* Allow adding and removing jobs to be done from the webapp
* Don’t set the job to failed if it’s being retried
* Deprecated queue options in the job and removed startPosition. Now using the job/env combo as the job queue name
* Dequeung jobs doesn’t check if the runner is initialized
* Fixed issues with retrying a run getting stuck on a cancelled task, and errors from parsing the results of dequeing a job
* Remove queued round robin thing that isn’t used anymore
* Added slack to job catalog
* Better forwards compat
* Added long delay
* Fixed lock file
Matt Aitken