## Problem
Fix build-tools image tag calculation for PRs.
Broken in https://github.com/neondatabase/neon/pull/6195
## Summary of changes
- Use `pinned` tag instead of `$GITHUB_RUN_ID` if there's no changes in
the dockerfile (and we don't build such image)
## Fixing GitHub workflow issue related to build and push images
## Summary of changes
Followup of PR#608[move docker file from build repo to neon to solve
issue some issues
The build started failing because it missed a validation in logic that
determines changes in the docker file
Also, all the dependent jobs were skipped because of the build and push
of the image job.
To address the above issue following changes were made
- we are adding validation to generate image tag even if it's a merge to
repo.
- All the dependent jobs won't skip even if the build and push image job
is skipped.
- We have moved the logic to generate a tag in the sub-workflow. As the
tag name was necessary to be passed to the sub-workflow it made sense to
abstract that away where it was needed and then store it as an output
variable so that downward dependent jobs could access the value.
- This made the dependency logic easy and we don't need complex
expressions to check the condition on which it will run
- An earlier PR was closed that tried solving a similar problem that has
some feedback and context before creating this PR
https://github.com/neondatabase/neon/pull/6175
## Checklist before requesting a review
- [x] Move the tag generation logic from the main workflow to the
sub-workflow of build and push the image
- [x] Add a condition to generate an image tag for a non-PR-related run
- [x] remove complex if the condition from the job if conditions
---------
Co-authored-by: Alexander Bayandin <alexander@neon.tech>
Co-authored-by: Abhijeet Patil <abhijeet@neon.tech>
## Problem
This is a comment only change.
To ensure that our benchmarking results are fair we need to have correct
stats in catalog. Otherwise optimizer chooses seq scan instead of index
only scan for some queries. Added comment to run vacuum after data prep.
This PR adds a component-level benchmarking utility for pageserver.
Its name is `pagebench`.
The problem solved by `pagebench` is that we want to put Pageserver
under high load.
This isn't easily achieved with `pgbench` because it needs to go through
a compute, which has signficant performance overhead compared to
accessing Pageserver directly.
Further, compute has its own performance optimizations (most
importantly: caches). Instead of designing a compute-facing workload
that defeats those internal optimizations, `pagebench` simply bypasses
them by accessing pageserver directly.
Supported benchmarks:
* getpage@latest_lsn
* basebackup
* triggering logical size calculation
This code has no automated users yet.
A performance regression test for getpage@latest_lsn will be added in a
later PR.
part of https://github.com/neondatabase/neon/issues/5771
## Problem
HTTP connection pool will grow without being pruned
## Summary of changes
Remove connection clients from pools once idle, or once they exit.
Periodically clear pool shards.
GC Logic:
Each shard contains a hashmap of `Arc<EndpointPool>`s.
Each connection stores a `Weak<EndpointPool>`.
During a GC sweep, we take a random shard write lock, and check that if
any of the `Arc<EndpointPool>`s are unique (using `Arc::get_mut`).
- If they are unique, then we check that the endpoint-pool is empty, and
sweep if it is.
- If they are not unique, then the endpoint-pool is in active use and we
don't sweep.
- Idle connections will self-clear from the endpoint-pool after 5
minutes.
Technically, the uniqueness of the endpoint-pool should be enough to
consider it empty, but the connection count check is done for
completeness sake.
Allows usage via `aws sso login --profile=<p>; AWS_PROFILE=<p>`. Now
there is no need to manually configure things any more via
`SSO_ACCOUNT_ID` and others. Now one can run the tests locally (given
Neon employee access to aws):
```
aws sso login --profile dev
export ENABLE_REAL_S3_REMOTE_STORAGE=nonempty REMOTE_STORAGE_S3_REGION=eu-central-1 REMOTE_STORAGE_S3_BUCKET=neon-github-public-dev AWS_PROFILE=dev
cargo test -p remote_storage -j 1 s3 -- --nocapture
```
Also makes the scrubber use the same region for auth that it does its
operations in (not touching the hard coded role name and start_url
values here, they are not ideal though).
Adds a new disk usage based eviction option, EvictionOrder, which
selects whether to use the current `AbsoluteAccessed` or this new
proposed but not yet tested `RelativeAccessed`. Additionally a fudge
factor was noticed while implementing this, which might help sparing
smaller tenants at the expense of targeting larger tenants.
Cc: #5304
Co-authored-by: Arpad Müller <arpad@neon.tech>
## Problem
Currently a chart of S3 error rate is misleading: it can show errors any
time we are attaching a tenant (probing for index_part generation,
checking for remote delete marker).
Considering 404 successful isn't perfectly elegant, but it enables the
error rate to be used a a more meaningful alert signal: it would
indicate if we were having auth issues, sending bad requests, getting
throttled ,etc.
## Summary of changes
Track 404 requests in the AttemptOutcome::Ok bucket instead of the
AttemptOutcome::Err bucket.
This is a precursor to:
- https://github.com/neondatabase/neon/pull/6185
While that PR contains big changes to neon_local and attachment_service,
this PR contains a few unrelated standalone changes generated while
working on that branch:
- Fix restarting a pageserver when it contains multiple shards for the
same tenant
- When using location_config api to attach a tenant, create its
timelines dir
- Update test paths where generations were previously optional to make
them always-on: this avoids tests having to spuriously assert that
attachment_service is not None in order to make the linter happy.
- Add a TenantShardId python implementation for subsequent use in test
helpers that will be made shard-aware
- Teach scrubber to read across shards when checking for layer
existence: this is a refactor to track the list of existent layers at
tenant-level rather than locally to each timeline. This is a precursor
to testing shard splitting.