## Problem
We don't have a well-documented, periodic benchmark for TPC-C like OLTP
workload.
## Summary of changes
# Benchbase TPC-C-like Performance Results
Runs TPC-C-like benchmarks on Neon databases using
[Benchbase](https://github.com/cmu-db/benchbase).
Docker images are built
[here](https://github.com/neondatabase-labs/benchbase-docker-images)
We run the benchmarks at different scale factors aligned with different
compute sizes we offer to customers.
For each scale factor, we determine a max rate (see Throughput in warmup
phase) and then run the benchmark at a target rate of approx. 70 % of
the max rate.
We use different warehouse sizes which determine the working set size -
it is optimized for LFC size of the respected pricing tier.
Usually we should get LFC hit rates above 70 % for this setup and quite
good, consistent (non-flaky) latencies.
## Expected performance as of first testing this
| Tier | CU | Warehouses | Terminals | Max TPS | LFC size | Working set
size | LFC hit rate | Median latency | p95 latency |
|------------|------------|---------------|-----------|---------|----------|------------------|--------------|----------------|-------------|
| free | 0.25-2 | 50 - 5 GB | 150 | 800 | 5 GB | 6.3 GB | 95 % | 170 ms
| 600 ms |
| serverless | 2-8 | 500 - 50 GB | 230 | 2000 | 26 GB | ?? GB | 91 % |
50 ms | 200 ms |
| business | 2-16 | 1000 - 100 GB | 330 | 2900 | 51 GB | 50 GB | 72 % |
40 ms | 180 ms |
Each run
- first loads the database (not shown in the dashboard).
- Then we run a warmup phase for 20 minutes to warm up the database and
the LFC at unlimited target rate (max rate) (highest throughput but
flaky latencies).
The warmup phase can be used to determine the max rate and adjust it in
the github workflow in case Neon is faster in the future.
- Then we run the benchmark at a target rate of approx. 70 % of the max
rate for 1 hour (expecting consistent latencies and throughput).
## Important notes on implementation:
- we want to eventually publish the process how to reproduce these
benchmarks
- thus we want to reduce all dependencies necessary to run the
benchmark, the only thing needed are
- docker
- the docker images referenced above for benchbase
- python >= 3.9 to run some config generation steps and create diagrams
- to reduce dependencies we deliberatly do NOT use some of our python
fixture test infrastructure to make the dependency chain really small -
so pls don't add a review comment "should reuse fixture xy"
- we also upload all generator python scripts, generated bash shell
scripts and configs as well as raw results to S3 bucket that we later
want to publish once this benchmark is reviewed and approved.
## Problem
There has been some inconsistencies of providing tenant config via
`tenant_create` and via other tenant config APIs due to how the
properties are processed: in `tenant_create`, the test framework calls
neon-cli and therefore puts those properties in the cmdline. In other
cases, it's done via the HTTP API by directly serializing to a JSON.
When using the cmdline, the program only accepts serde bool that is
true/false.
## Summary of changes
Convert Python bool into `true`/`false` when using neon-cli.
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
LKB-197, #9516
To make sure the migration path is smooth.
The previous plan is to store new relations in new keyspace and old ones
in old keyspace until it gets dropped. This makes the migration path
hard as we can't validate v2 writes and can't rollback. This patch gives
us a more smooth migration path:
- The first time we enable reldirv2 for a tenant, we copy over
everything in the old keyspace to the new one. This might create a short
spike of latency for the create relation operation, but it's oneoff.
- After that, we have identical v1/v2 keyspace and read/write both of
them. We validate reads every time we list the reldirs.
- If we are in `migrating` mode, use v1 as source of truth and log a
warning for failed v2 operations. If we are in `migrated` mode, use v2
as source of truth and error when writes fail.
- One compatibility test uses dataset from the time where we enabled
reldirv2 (of the original rollout plan), which only has relations
written to the v2 keyspace instead of the v1 keyspace. We had to adjust
it accordingly.
- Add `migrated_at` in index_part to indicate the LSN where we did the
initialize.
TODOs:
- Test if relv1 can be read below the migrated_at LSN.
- Move the initialization process to L0 compaction instead of doing it
on the write path.
- Disable relcache in the relv2 test case so that all code path gets
fully tested.
## Summary of changes
- New behavior of reldirv2 migration flags as described above.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
In the gap between picking an optimization and applying it, something
might insert a change to the intent state that makes it incompatible.
If the change is done via the `schedule()` method, we are covered by the
increased sequence number, but otherwise we can panic if we violate the
intent state invariants.
## Summary of Changes
Validate the optimization right before applying it. Since we hold the
service lock at that point, nothing else can sneak in.
Closes LKB-65
https://github.com/neondatabase/cloud/issues/19011
Measure relative performance for prewarmed and non-prewarmed endpoints.
Add test that runs on every commit, and one performance test with a
remote cluster.
## Problem
We lost capability to explicitly disable the global eviction task (for
testing).
## Summary of changes
Add an `enabled` flag to `DiskUsageEvictionTaskConfig` to indicate
whether we should run the eviction job or not.
The `--gzip-probability` parameter was removed in #12250. However,
`test_basebackup_with_high_slru_count` still uses it, and keeps failing.
This patch removes the use of the parameter (gzip is enabled by
default).
## Problem
- We run the large tenant oltp workload with a fixed size (larger than
existing customers' workloads).
Our customer's workloads are continuously growing and our testing should
stay ahead of the customers' production workloads.
- we want to touch all tables in the tenant's database (updates) so that
we simulate a continuous change in layer files like in a real production
workload
- our current oltp benchmark uses a mixture of read and write
transactions, however we also want a separate test run with read-only
transactions only
## Summary of changes
- modify the existing workload to have a separate run with pgbench
custom scripts that are read-only
- create a new workload that
- grows all large tables in each run (for the reuse branch in the large
oltp tenant's project)
- updates a percentage of rows in all large tables in each run (to
enforce table bloat and auto-vacuum runs and layer rebuild in
pageservers
Each run of the new workflow increases the logical database size about
16 GB.
We start with 6 runs per day which will give us about 96-100 GB growth
per day.
---------
Co-authored-by: Alexander Lakhin <alexander.lakhin@neon.tech>
## Problem
We support two ingest protocols on the pageserver: vanilla and
interpreted.
Interpreted has been the only protocol in use for a long time.
## Summary of changes
* Remove the ingest handling of the vanilla protocol
* Remove tenant and pageserver configuration for it
* Update all tests that tweaked the ingest protocol
## Compatibility
Backward compatibility:
* The new pageserver version can read the existing pageserver
configuration and it will ignore the unknown field.
* When the tenant config is read from the storcon db or from the
pageserver disk, the extra field will be ignored.
Forward compatiblity:
* Both the pageserver config and the tenant config map missing fields to
their default value.
I'm not aware of any tenant level override that was made for this knob.
## Problem
- Benchmark periodic pagebench had inconsistent benchmarking results
even when run with the same commit hash.
Hypothesis is this was due to running on dedicated but virtualized EC
instance with varying CPU frequency.
- the dedicated instance type used for the benchmark is quite "old" and
we increasingly get `An error occurred (InsufficientInstanceCapacity)
when calling the StartInstances operation (reached max retries: 2):
Insufficient capacity.`
- periodic pagebench uses a snapshot of pageserver timelines to have the
same layer structure in each run and get consistent performance.
Re-creating the snapshot was a painful manual process (see
https://github.com/neondatabase/cloud/issues/27051 and
https://github.com/neondatabase/cloud/issues/27653)
## Summary of changes
- Run the periodic pagebench on a custom hetzner GitHub runner with
large nvme disk and governor set to defined perf profile
- provide a manual dispatch option for the workflow that allows to
create a new snapshot
- keep the manual dispatch option to specify a commit hash useful for
bi-secting regressions
- always use the newest created snapshot (S3 bucket uses date suffix in
S3 key, example
`s3://neon-github-public-dev/performance/pagebench/shared-snapshots-2025-05-17/`
- `--ignore`
`test_runner/performance/pageserver/pagebench/test_pageserver_max_throughput_getpage_at_latest_lsn.py`
in regular benchmarks run for each commit
- improve perf copying snapshot by using `cp` subprocess instead of
traversing tree in python
## Example runs with code in this PR:
- run which creates new snapshot
https://github.com/neondatabase/neon/actions/runs/15083408849/job/42402986376#step:19:55
- run which uses latest snapshot
-
https://github.com/neondatabase/neon/actions/runs/15084907676/job/42406240745#step:11:65
This PR commits the benchmarks I ran to qualify concurrent IO before we
released it.
Changes:
- Add `l0stack` fixture; a reusable abstraction for creating a stack of
L0 deltas
each of which has 1 Value::Delta per page.
- Such a stack of L0 deltas is a good and understandable demo for
concurrent IO
because to reconstruct any page, $layer_stack_height` Values need to be
read.
Before concurrent IO, the reads were sequential.
With concurrent IO, they are executed concurrently.
- So, switch `test_latency` to use the l0stack.
- Teach `pagebench`, which is used by `test_latency`, to limit itself to
the blocks of the relation created by the l0stack abstraction.
- Additional parametrization of `test_latency` over dimensions
`ps_io_concurrency,l0_stack_height,queue_depth`
- Use better names for the tests to reflect what they do, leave
interpretation of the (now quite high-dimensional) results to the reader
- `test_{throughput => postgres_seqscan}`
- `test_{latency => random_reads}`
- Cut down on permutations to those we use in production. Runtime is
about 2min.
Refs
- concurrent IO epic https://github.com/neondatabase/neon/issues/9378
- batching task: fixes https://github.com/neondatabase/neon/issues/9837
---------
Co-authored-by: Peter Bendel <peterbendel@neon.tech>
# Fix KeyError in physical replication benchmark test
This PR fixes the failing physical replication benchmark test that was
encountering a KeyError: 'endpoints'.
The issue was in accessing `project["project"]["endpoints"][0]["id"]`
when it should be `project["endpoints"][0]["id"]`, consistent with how
endpoints are accessed elsewhere in the codebase.
Fixed the issue in both test functions:
- test_ro_replica_lag
- test_replication_start_stop
Link to Devin run:
https://app.devin.ai/sessions/be3fe9a9ee5942e4b12e74a7055f541b
Requested by: Peter Bendel
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: peterbendel@neon.tech <peterbendel@neon.tech>
## Problem
`test_compute_startup_simple` and `test_compute_ondemand_slru_startup`
are failing.
This test implicitly asserts that the metrics.json endpoint succeeds and
returns all expected metrics, but doesn't make it easy to see what went
wrong if it doesn't (e.g. in this failure
https://neon-github-public-dev.s3.amazonaws.com/reports/main/14513210240/index.html#suites/13d8e764c394daadbad415a08454c04e/b0f92a86b2ed309f/)
In this case, it was failing because of a missing auth token, because it
was using `requests` directly instead of using the endpoint http client
type.
## Summary of changes
- Use endpoint http wrapper to get raise_for_status & auth token
This is mostly a documentation update, but a few updates with regard to
neon_local, pageserver, and tests.
17 is our default for users in production, so dropping references to 16
makes sense.
Signed-off-by: Tristan Partin <tristan@neon.tech>
Signed-off-by: Tristan Partin <tristan@neon.tech>
## Problem
Benchmarks results are inconsistent on existing small-metal runners
## Summary of changes
Introduce new `unit-perf` runners, and lets run benchmark on them.
The new hardware has slower, but consistent, CPU frequency - if run with
default governor schedutil.
Thus we needed to adjust some testcases' timeouts and add some retry
steps where hard-coded timeouts couldn't be increased without changing
the system under test.
-
[wait_for_last_record_lsn](6592d69a67/test_runner/fixtures/pageserver/utils.py (L193))
1000s -> 2000s
-
[test_branch_creation_many](https://github.com/neondatabase/neon/pull/11409/files#diff-2ebfe76f89004d563c7e53e3ca82462e1d85e92e6d5588e8e8f598bbe119e927)
1000s
-
[test_ingest_insert_bulk](https://github.com/neondatabase/neon/pull/11409/files#diff-e90e685be4a87053bc264a68740969e6a8872c8897b8b748d0e8c5f683a68d9f)
- with back throttling disabled compute becomes unresponsive for more
than 60 seconds (PG hard-coded client authentication connection timeout)
-
[test_sharded_ingest](https://github.com/neondatabase/neon/pull/11409/files#diff-e8d870165bd44acb9a6d8350f8640b301c1385a4108430b8d6d659b697e4a3f1)
600s -> 1200s
Right now there are only 2 runners of that class, and if we decide to go
with them, we have to check how much that type of runners we need, so
jobs not stuck with waiting for that type of runners available.
However we now decided to run those runners with governor performance
instead of schedutil.
This achieves almost same performance as previous runners but still
achieves consistent results for same commit
Related issue to activate performance governor on these runners
https://github.com/neondatabase/runner/pull/138
## Verification that it helps
### analyze runtimes on new runner for same commit
Table of runtimes for the same commit on different runners in
[run](https://github.com/neondatabase/neon/actions/runs/14417589789)
| Run | Benchmarks (1) | Benchmarks (2) |Benchmarks (3) |Benchmarks (4)
| Benchmarks (5) |
|--------|--------|---------|---------|---------|---------|
| 1 | 1950.37s | 6374.55s | 3646.15s | 4149.48s | 2330.22s |
| 2 | - | 6369.27s | 3666.65s | 4162.42s | 2329.23s |
| Delta % | - | 0,07 % | 0,5 % | 0,3 % | 0,04 % |
| with governor performance | 1519.57s | 4131.62s | - | - | - |
| second run gov. perf. | 1513.62s | 4134.67s | - | - | - |
| Delta % | 0,3 % | 0,07 % | - | - | - |
| speedup gov. performance | 22 % | 35 % | - | - | - |
| current desktop class hetzner runners (main) | 1487.10s | 3699.67s | -
| - | - |
| slower than desktop class | 2 % | 12 % | - | - | - |
In summary, the runtimes for the same commit on this hardware varies
less than 1 %.
---------
Co-authored-by: BodoBolero <peterbendel@neon.tech>
## Problem
https://github.com/neondatabase/neon/pull/11494 changes the batching
logic, but we don't have a way to evaluate it.
## Summary of changes
This PR introduces a global and per timeline metric which tracks the
reason for
which a batch was broken.
## Problem
Get page batching stops when we encounter requests at different LSNs.
We are leaving batching factor on the table.
## Summary of changes
The goal is to support keys with different LSNs in a single batch and
still serve them with a single vectored get.
Important restriction: the same key at different LSNs is not supported
in one batch. Returning different key
versions is a much more intrusive change.
Firstly, the read path is changed to support "scattered" queries. This
is a conceptually simple step from
https://github.com/neondatabase/neon/pull/11463. Instead of initializing
the fringe for one keyspace,
we do it for multiple at different LSNs and let the logic already
present into the fringe handle selection.
Secondly, page service code is updated to support batching at different
LSNs. Eeach request parsed from the wire determines its effective
request LSN and keeps it in mem for the batcher toinspect. The batcher
allows keys at
different LSNs in one batch as long one key is not requested at
different LSNs.
I'd suggest doing the first pass commit by commit to get a feel for the
changes.
## Results
I used the batching test from [Christian's
PR](https://github.com/neondatabase/neon/pull/11391) which increases the
change of batch breaks. Looking at the logs I think the new code is at
the max batching factor for the workload (we
only break batches due to them being oversized or because the executor
is idle).
```
Main:
Reasons for stopping batching: {'LSN changed': 22843, 'of batch size': 33417}
test_throughput[release-pg16-50-pipelining_config0-30-100-128-batchable {'max_batch_size': 32, 'execution': 'concurrent-futures', 'mode': 'pipelined'}].perfmetric.batching_factor: 14.6662
My branch:
Reasons for stopping batching: {'of batch size': 37024}
test_throughput[release-pg16-50-pipelining_config0-30-100-128-batchable {'max_batch_size': 32, 'execution': 'concurrent-futures', 'mode': 'pipelined'}].perfmetric.batching_factor: 19.8333
```
Related: https://github.com/neondatabase/neon/issues/10765
## Problem
The `pagebench` benchmarks set up an initial dataset by creating a
template tenant, copying the remote storage to a bunch of new tenants,
and attaching them to Pageservers.
In #11420, we found that
`test_pageserver_characterize_throughput_with_n_tenants` had degraded
performance because it set a custom tenant config in Pageservers that
was then replaced with the default tenant config by the storage
controller.
The initial fix was to register the tenants directly in the storage
controller, but this created the tenants with generation 1. This broke
`test_basebackup_with_high_slru_count`, where the template tenant was at
generation 2, leading to all layer files at generation 2 being ignored.
Resolves#11485.
Touches #11381.
## Summary of changes
This patch addresses both test issues by modifying `attach_hook` to also
take a custom tenant config. This allows attaching tenants to
Pageservers from pre-existing remote storage, specifying both the
generation and tenant config when registering them in the storage
controller.
The batching perf test workload is currently read-only sequential scans.
However, realistic workloads have concurrent writes (to other pages)
going on.
This PR simulates concurrent writes to other pages by emitting logical
replication messages.
These degrade the achieved batching factor, for the reason see
- https://github.com/neondatabase/neon/issues/10765
PR
- https://github.com/neondatabase/neon/pull/11494
will fix this problem and get batching factor back up.
---------
Co-authored-by: Vlad Lazar <vlad@neon.tech>
## Problem
our large oltp benchmark runs very long - we want to remove the duration
of the reindex step.
we don't run concurrent workload anyhow but added "concurrently" only to
have a "prod-like" approach. But if it just doubles the time we report
because it requires two instead of one full table scan we can remove it
## Summary of changes
remove keyword concurrently from the reindex step
We'd like to run benchmarks starting from a steady state. To this end,
do a reconciliation round before proceeding with the benchmark.
This is useful for benchmarks that use tenant dir snapshots since a
non-standard tenant configuration is used to generate the snapshot. The
storage controller is not aware of the non default tenant configuration
and will reconcile while the bench is running.
Log the created project and endpoint IDs and improve typing in the
source code to improve readability.
Signed-off-by: Tristan Partin <tristan@neon.tech>
Based on https://github.com/neondatabase/neon/pull/11139
## Problem
We want to export performance traces from the pageserver in OTEL format.
End goal is to see them in Grafana.
## Summary of changes
https://github.com/neondatabase/neon/pull/11139 introduces the
infrastructure required to run the otel collector alongside the
pageserver.
### Design
Requirements:
1. We'd like to avoid implementing our own performance tracing stack if
possible and use the `tracing` crate if possible.
2. Ideally, we'd like zero overhead of a sampling rate of zero and be a
be able to change the tracing config for a tenant on the fly.
3. We should leave the current span hierarchy intact. This includes
adding perf traces without modifying existing tracing.
To satisfy (3) (and (2) in part) a separate span hierarchy is used.
`RequestContext` gains an optional `perf_span` member
that's only set when the request was chosen by sampling. All perf span
related methods added to `RequestContext` are no-ops for requests that
are not sampled.
This on its own is not enough for (3), so performance spans use a
separate tracing subscriber. The `tracing` crate doesn't have great
support for this, so there's a fair amount of boilerplate to override
the subscriber at all points of the perf span lifecycle.
### Perf Impact
[Periodic
pagebench](https://neonprod.grafana.net/d/ddqtbfykfqfi8d/e904990?orgId=1&from=2025-02-08T14:15:59.362Z&to=2025-03-10T14:15:59.362Z&timezone=utc)
shows no statistically significant regression with a sample ratio of 0.
There's an annotation on the dashboard on 2025-03-06.
### Overview of changes:
1. Clean up the `RequestContext` API a bit. Namely, get rid of the
`RequestContext::extend` API and use the builder instead.
2. Add pageserver level configs for tracing: sampling ratio, otel
endpoint, etc.
3. Introduce some perf span tracking utilities and expose them via
`RequestContext`. We add a `tracing::Span` wrapper to be used for perf
spans and a `tracing::Instrumented` equivalent for it. See doc comments
for reason.
4. Set up OTEL tracing infra according to configuration. A separate
runtime is used for the collector.
5. Add perf traces to the read path.
## Refs
- epic https://github.com/neondatabase/neon/issues/9873
---------
Co-authored-by: Christian Schwarz <christian@neon.tech>
## Problem
Pagebench creates a bunch of tenants by first creating a template tenant
and copying its remote storage, then attaching the copies to the
Pageserver.
These tenants had custom configurations to disable GC and compaction.
However, these configs were only picked up by the Pageserver on attach,
and not registered with the storage controller. This caused the storage
controller to replace the tenant configs with the default tenant config,
re-enabling GC and compaction which interferes with benchmark
performance.
Resolves#11381.
## Summary of changes
Register the copied tenants with the storage controller, instead of
directly attaching them to the Pageserver.
## Problem
In Neon DBaaS we adjust the shared_buffers to the size of the compute,
or better described we adjust the max number of connections to the
compute size and we adjust the shared_buffers size to the number of max
connections according to about the following sizes
`2 CU: 225mb; 4 CU: 450mb; 8 CU: 900mb`
[see](877e33b428/goapp/controlplane/internal/pkg/compute/computespec/pg_settings.go (L405))
## Summary of changes
We should run perf unit tests with settings that is realistic for a
paying customer and select 8 CU as the reference for those tests.
## Problem
`TYPE_CHECKING` is used inconsistently across Python tests.
## Summary of changes
- Update `ruff`: 0.7.0 -> 0.11.2
- Enable TC (flake8-type-checking):
https://docs.astral.sh/ruff/rules/#flake8-type-checking-tc
- (auto)fix all new issues
## Problem
While working on bulk import, I want to use the `control-plane-url` flag
for a different request.
Currently, the local compute hook is used whenever no control plane is
specified in the config.
My test requires local compute notifications and a configured
`control-plane-url` which isn't supported.
## Summary of changes
Add a `use-local-compute-notifications` flag. When this is set, we use
the local flow regardless of other config values.
It's enabled by default in neon_local and disabled by default in all
other envs. I had to turn the flag off in tests
that wish to bypass the local flow, but that's expected.
---------
Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
## Problem
Currently, we only split tenants into 8 shards once, at the 64 GB split
threshold. For very large tenants, we need to keep splitting to avoid
huge shards. And we also want to eagerly split at a lower threshold to
improve throughput during initial ingestion.
See
https://github.com/neondatabase/cloud/issues/22532#issuecomment-2706215907
for details.
Touches https://github.com/neondatabase/cloud/issues/22532.
Requires #11157.
## Summary of changes
This adds parameters and logic to enable repeated splits when a tenant's
largest timeline divided by shard count exceeds `split_threshold`, as
well as eager initial splits at a lower threshold to speed up initial
ingestion. The default parameters are all set such that they retain the
current behavior in production (only split into 8 shards once, at 64
GB).
* `split_threshold` now specifies a maximum shard size. When a shard
exceeds it, all tenant shards are split by powers of 2 such that all
tenant shards fall below `split_threshold`. Disabled by default, like
today.
* Add `max_split_shards` to specify a max shard count for autosplits.
Defaults to 8 to retain current behavior.
* Add `initial_split_threshold` and `initial_split_shards` to specify a
threshold and target count for eager splits of unsharded tenants.
Defaults to 64 GB and 8 shards to retain current production behavior.
Because this PR sets `initial_split_threshold` to 64 GB by default, it
has the effect of enabling autosplits by default. This was not the case
previously, since `split_threshold` defaults to None, but it is already
enabled across production and staging. This is temporary until we
complete the production rollout.
For more details, see code comments.
This must wait until #11157 has been deployed to Pageservers.
Once this has been deployed to production, we plan to change the
parameters to:
* `split-threshold`: 256 GB
* `initial-split-threshold`: 16 GB
* `initial-split-shards`: 4
* `max-split-shards`: 16
The final split points will thus be:
* Start: 1 shard
* 16 GB: 4 shards
* 1 TB: 8 shards
* 2 TB: 16 shards
We will then change the default settings to be disabled by default.
---------
Co-authored-by: John Spray <john@neon.tech>
## Problem
We had a recent Postgres startup latency (`start_postgres_ms`)
degradation, but it was only caught with SLO alerts. There was actually
an existing test for the same purpose -- `start_postgres_ms`, but it's
doing only two starts, so it's a bit noisy.
## Summary of changes
Add new compute startup latency test that does 100 iterations and
reports p50, p90 and p99 latencies.
Part of https://github.com/neondatabase/cloud/issues/24882
... to better match the workload characteristics of real Neon customers
## Problem
We analyzed workloads of large Neon users and want to extend the oltp
workload to include characteristics seen in those workloads.
## Summary of changes
- for re-use branch delete inserted rows from last run
- adjust expected run-time (time-outs) in GitHub workflow
- add queries that exposes the prefetch getpages path
- add I/U/D transactions for another table (so far the workload was
insert/append-only)
- add an explicit vacuum analyze step and measure its time
- add reindex concurrently step and measure its time (and take care that
this step succeeds even if prior reindex runs have failed or were
canceled)
- create a second connection string for the pooled connection that
removes the `-pooler` suffix from the hostname because we want to run
long-running statements (database maintenance) and bypass the pooler
which doesn't support unlimited statement timeout
## Test run
https://github.com/neondatabase/neon/actions/runs/13851772887/job/38760172415
We want to switch away from and deprecate the `--compute-hook-url` param
for the storcon in favour of `--control-plane-url` because it allows us
to construct urls with `notify-safekeepers`.
This PR switches the pytests and neon_local from a
`control_plane_compute_hook_api` to a new param named
`control_plane_hooks_api` which is supposed to point to the parent of
the `notify-attach` URL.
We still support reading the old url from disk to not be too disruptive
with existing deployments, but we just ignore it.
Also add docs for the `notify-safekeepers` upcall API.
Follow-up of #11173
Part of https://github.com/neondatabase/neon/issues/11163
# Fix metric_unit length in test_compute_ctl_api.py
## Description
This PR changes the metric_unit from "microseconds" to "μs" in
test_compute_ctl_api.py to fix the issue where perf test results were
not being stored in the database due to the string exceeding the 10
character limit of the metric_unit column in the perf_test_results
table.
## Problem
As reported in Slack, the perf test results were not being uploaded to
the database because the "microseconds" string (12 characters) exceeds
the 10 character limit of the metric_unit column in the
perf_test_results table.
## Solution
Replace "microseconds" with "μs" in all metric_unit parameters in the
test_compute_ctl_api.py file.
## Testing
The changes have been committed and pushed. The PR is ready for review.
Link to Devin run:
https://app.devin.ai/sessions/e29edd672bd34114b059915820e8a853
Requested by: Peter Bendel
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: peterbendel@neon.tech <peterbendel@neon.tech>
## Problem
The current migration API does a live migration, but if the destination
doesn't already have a secondary, that live migration is unlikely to be
able to warm up a tenant properly within its timeout (full warmup of a
big tenant can take tens of minutes).
Background optimisation code knows how to do this gracefully by creating
a secondary first, but we don't currently give a human a way to trigger
that.
Closes: https://github.com/neondatabase/neon/issues/10540
## Summary of changes
- Add `prefererred_node` parameter to TenantShard, which is respected by
optimize_attachment
- Modify migration API to have optional prewarm=true mode, in which we
set preferred_node and call optimize_attachment, rather than directly
modifying intentstate
- Require override_scheduler=true flag if migrating somewhere that is a
less-than-optimal scheduling location (e.g. wrong AZ)
- Add `origin_node_id` to migration API so that callers can ensure
they're moving from where they think they're moving from
- Add tests for the above
The storcon_cli wrapper for this has a 'watch' mode that waits for
eventual cutover. This doesn't show the warmth of the secondary evolve
because we don't currently have an API for that in the controller, as
the passthrough API only targets attached locations, not secondaries. It
would be straightforward to add later as a dedicated endpoint for
getting secondary status, then extend the storcon_cli to consume that
and print a nice progress indicator.
## Problem
We just had a regression reported at
https://neondb.slack.com/archives/C08EXUJF554/p1741102467515599, which
clearly came with one of the releases. It's not a huge problem yet, but
it's annoying that we cannot quickly attribute it to a specific commit.
## Summary of changes
Add a very simple `compute_ctl` HTTP API benchmark that does 10k
requests to `/status` and `metrics.json` and reports p50 and p99.
---------
Co-authored-by: Peter Bendel <peterbendel@neon.tech>
## Problem
part of https://github.com/neondatabase/neon/issues/9516
## Summary of changes
Similar to the aux v2 migration, we persist the relv2 migration status
into index_part, so that even the config item is set to false, we will
still read from the v2 storage to avoid loss of data.
Note that only the two variants `None` and
`Some(RelSizeMigration::Migrating)` are used for now. We don't have full
migration implemented so it will never be set to
`RelSizeMigration::Migrated`.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
## Problem
We want to support larger tenants (regarding logical database size,
number of transactions per second etc.) and should increase our test
coverage of OLTP transactions at larger scale.
## Summary of changes
Start a new benchmark that over time will add more OLTP tests at larger
scale.
This PR covers the first version and will be extended in further PRs.
Also fix some infrastructure:
- default for new connections and large tenants is to use connection
pooler pgbouncer, however our fixture always added
`statement_timeout=120` which is not compatible with pooler
[see](https://neon.tech/docs/connect/connection-errors#unsupported-startup-parameter)
- action to create branch timed out after 10 seconds and 10 retries but
for large tenants it can take longer so use increasing back-off for
retries
## Test run
https://github.com/neondatabase/neon/actions/runs/13593446706
## Problem
So far cumulative statistics have not been persisted when Neon scales to
zero (suspends endpoint).
With PR https://github.com/neondatabase/neon/pull/6560 the cumulative
statistics should now survive endpoint restarts and correctly trigger
the auto- vacuum and auto analyze maintenance
So far we did not have a testcase that validates that improvement in our
dev cloud environment with a real project.
## Summary of changes
Introduce testcase `test_cumulative_statistics_persistence`in the
benchmarking workflow running daily to verify:
- Verifies that the cumulative statistics are correctly persisted across
restarts.
- Cumulative statistics are important to persist across restarts because
they are used
- when auto-vacuum an auto-analyze trigger conditions are met.
- The test performs the following steps:
- Seed a new project using pgbench
- insert tuples that by itself are not enough to trigger auto-vacuum
- suspend the endpoint
- resume the endpoint
- insert additional tuples that by itself are not enough to trigger
auto-vacuum but in combination with the previous tuples are
- verify that autovacuum is triggered by the combination of tuples
inserted before and after endpoint suspension
## Test run
https://github.com/neondatabase/neon/actions/runs/13546879714/job/37860609089#step:6:282
## Problem
We have `test_perf_many_relations` but it only runs on remote clusters,
and we cannot directly modify tenant config. Therefore, I patched one of
the current tests to benchmark relv2 performance.
close https://github.com/neondatabase/neon/issues/9986
## Summary of changes
* Add `v1/v2` selector to `test_tx_abort_with_many_relations`.
---------
Signed-off-by: Alex Chi Z <chi@neon.tech>
The compute_ctl HTTP server has the following purposes:
- Allow management via the control plane
- Provide an endpoint for scaping metrics
- Provide APIs for compute internal clients
- Neon Postgres extension for installing remote extensions
- local_proxy for installing extensions and adding grants
The first two purposes require the HTTP server to be available outside
the compute.
The Neon threat model is a bad actor within our internal network. We
need to reduce the surface area of attack. By exposing unnecessary
unauthenticated HTTP endpoints to the internal network, we increase the
surface area of attack. For endpoints described in the third bullet
point, we can just run an extra HTTP server, which is only bound to the
loopback interface since all consumers of those endpoints are within the
compute.
## Problem
Endpoint kept running while timeline was deleted, causing forbidden
warnings on the pageserver when the tenant is not found.
## Summary of changes
- Explicitly stop the endpoint before the end of the test, so that it
isn't trying to talk to the pageserver in the background while things
are torn down
## Problem
During ingest_benchmark which uses `pgcopydb`
([see](https://github.com/dimitri/pgcopydb))we sometimes had outages.
- when PostgreSQL COPY step failed we got a segfault (reported
[here](https://github.com/dimitri/pgcopydb/issues/899))
- the root cause was Neon idle_in_transaction_session_timeout is set to
5 minutes which is suboptimal for long-running tasks like project import
(reported [here](https://github.com/dimitri/pgcopydb/issues/900))
## Summary of changes
Patch pgcopydb to avoid segfault.
override idle_in_transaction_session_timeout and set it to "unlimited"
