## Problem
https://github.com/neondatabase/neon/pull/11210 migrated pushing images
to ghcr. Unfortunately, it was incomplete in using images from ghcr,
which resulted in a few places referencing the ghcr build-tools image,
while trying to use docker hub credentials.
## Summary of changes
Use build-tools image from ghcr consistently.
## Problem
we measure ingest performance for a few variants (stripe-sizes,
pre-sharded, shard-splitted).
However some phenomena (e.g. related to L0 compaction) in PS can be
better observed and optimized with un-sharded tenants.
## Summary of changes
- Allow to create projects with a policy that disables sharding
(`{"scheduling": "Essential"}`)
- add a variant to ingest_benchmark that uses that policy for the new
project
## Test run
https://github.com/neondatabase/neon/actions/runs/13396325970
We want to verify if pageserver stripe size has an impact on ingest
performance.
We want to verify if ingest performance has improved or regressed with
postgres version 17.
## Summary of changes
- Allow to create new project with different postgres versions
- allow to pre-shard new project with different stripe sizes instead of
relying on storage manager to shard_split the project once a threshold
is exceeded
Replaces https://github.com/neondatabase/neon/pull/10509
Test run https://github.com/neondatabase/neon/actions/runs/12986410381
## Problem
`benchmarking` job fails because `aws-oicd-role-arn` input is not set
## Summary of changes:
- Set `aws-oicd-role-arn` for `benchmarking job
- Always require `aws-oicd-role-arn` to be set
- Rename `aws_oicd_role_arn` to `aws-oicd-role-arn` for consistency
## Problem
CI currently uses static credentials in some places. These are less
secure and hard to maintain, so we are going to deprecate them and use
OIDC auth.
## Summary of changes
- ci(fix): Use OIDC auth to upload artifact on s3
- ci(fix): Use OIDC auth to login on ECR
## Problem
we tried different parallelism settings for ingest bench
## Summary of changes
the following settings seem optimal after merging
- SK side Wal filtering
- batched getpages
Settings:
- effective_io_concurrency 100
- concurrency limit 200 (different from Prod!)
- jobs 4, maintenance workers 7
- 10 GB chunk size
## Problem
The first version of the ingest benchmark had some parsing and reporting
logic in shell script inside GitHub workflow.
it is better to move that logic into a python testcase so that we can
also run it locally.
## Summary of changes
- Create new python testcase
- invoke pgcopydb inside python test case
- move the following logic into python testcase
- determine backpressure
- invoke pgcopydb and report its progress
- parse pgcopydb log and extract metrics
- insert metrics into perf test database
- add additional column to perf test database that can receive endpoint
ID used for pgcopydb run to have it available in grafana dashboard when
retrieving other metrics for an endpoint
## Example run
https://github.com/neondatabase/neon/actions/runs/11860622170/job/33056264386
## Problem
We have no specific benchmark testing project migration of postgresql
project with existing data into Neon.
Typical steps of such a project migration are
- schema creation in the neon project
- initial COPY of relations
- creation of indexes and constraints
- vacuum analyze
## Summary of changes
Add a periodic benchmark running 9 AM UTC every day.
In each run:
- copy a 200 GiB project that has realistic schema, data, tables,
indexes and constraints from another project into
- a new Neon project (7 CU fixed)
- an existing tenant, (but new branch and new database) that already has
4 TiB of data
- use pgcopydb tool to automate all steps and parallelize COPY and index
creation
- parse pgcopydb output and report performance metrics in Neon
performance test database
## Logs
This benchmark has been tested first manually and then as part of
benchmarking.yml workflow, example run see
https://github.com/neondatabase/neon/actions/runs/11757679870
