this is to speed up suspends, see
https://github.com/neondatabase/cloud/issues/10284
## Problem
## Summary of changes
## Checklist before requesting a review
- [ ] I have performed a self-review of my code.
- [ ] If it is a core feature, I have added thorough tests.
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checklist
It was using `PRECONDITION_FAILED` for errors during `ComputeSpec` to
`ParsedSpec` conversion, but this disobeys the OpenAPI spec [1] and
correct code should be `BAD_REQUEST` for any spec processing errors.
While on it, I also noticed that `compute_ctl` OpenAPI spec has an
invalid format and fixed it.
[1] fd81945a60/compute_tools/src/http/openapi_spec.yaml (L119-L120)
instead of direct S3 request.
Pros:
- simplify code a lot (no need to provide AWS credentials and paths);
- reduce latency of downloading extension data as proxy resides near
computes; -reduce AWS costs as proxy has cache and 1000 computes asking
the same extension will not generate 1000 downloads from S3.
- we can use only one S3 bucket to store extensions (and rid of regional
buckets which were introduced to reduce latency);
Changes:
- deprecate remote-ext-config compute_ctl parameter, use
http://pg-ext-s3-gateway if any old format remote-ext-cofig is provided;
- refactor tests to use mock http server;
A set of changes to enable neon to work in IPv6 environments. The
changes are backward-compatible but allow to deploy neon even to
IPv6-only environments:
- bind to both IPv4 and IPv6 interfaces
- allow connections to Postgres from IPv6 interface
- parse the address from control plane that could also be IPv6
Don't download ext_index.json from s3, but instead receive it as a part of spec from control plane.
This eliminates s3 access for most compute starts,
and also allows us to update extensions spec on the fly
Don't panic if library or extension is not found in remote extension storage
or download has failed. Instead, log the error and proceed - if file is not
present locally as well, postgres will fail with postgres error. If it is a
shared_preload_library, it won't start, because of bad config. Otherwise, it
will just fail to run the SQL function/ command that needs the library.
Also, don't try to download extensions if remote storage is not configured.
Add infrastructure to dynamically load postgres extensions and shared libraries from remote extension storage.
Before postgres start downloads list of available remote extensions and libraries, and also downloads 'shared_preload_libraries'. After postgres is running, 'compute_ctl' listens for HTTP requests to load files.
Postgres has new GUC 'extension_server_port' to specify port on which 'compute_ctl' listens for requests.
When PostgreSQL requests a file, 'compute_ctl' downloads it.
See more details about feature design and remote extension storage layout in docs/rfcs/024-extension-loading.md
---------
Co-authored-by: Anastasia Lubennikova <anastasia@neon.tech>
Co-authored-by: Alek Westover <alek.westover@gmail.com>
This adds test coverage for 'compute_ctl', as it is now used by all
the python tests.
There are a few differences in how 'compute_ctl' is called in the
tests, compared to the real web console:
- In the tests, the postgresql.conf file is included as one large
string in the spec file, and it is written out as it is to the data
directory. I added a new field for that to the spec file. The real
web console, however, sets all the necessary settings in the
'settings' field, and 'compute_ctl' creates the postgresql.conf from
those settings.
- In the tests, the information needed to connect to the storage, i.e.
tenant_id, timeline_id, connection strings to pageserver and
safekeepers, are now passed as new fields in the spec file. The real
web console includes them as the GUCs in the 'settings' field. (Both
of these are different from what the test control plane used to do:
It used to write the GUCs directly in the postgresql.conf file). The
plan is to change the control plane to use the new method, and
remove the old method, but for now, support both.
Some tests that were sensitive to the amount of WAL generated needed
small changes, to accommodate that compute_ctl runs the background
health monitor which makes a few small updates. Also some tests shut
down the pageserver, and now that the background health check can run
some queries while the pageserver is down, that can produce a few
extra errors in the logs, which needed to be allowlisted.
Other changes:
- remove obsolete comments about PostgresNode;
- create standby.signal file for Static compute node;
- log output of `compute_ctl` and `postgres` is merged into
`endpoints/compute.log`.
---------
Co-authored-by: Anastasia Lubennikova <anastasia@neon.tech>
Our scale-to-zero logic was optimized for short auto-suspend intervals,
e.g. minutes or hours. In this case, if compute was restarted by k8s due
to some reason (OOM, k8s node went down, pod relocation, etc.),
`last_active` got bumped, we start counting auto-suspend timeout again.
It's not a big deal, i.e. we suspend completely idle compute not after 5
minutes, but after 10 minutes or so.
Yet, some clients may want days or even weeks. And chance that compute
could be restarted during this interval is pretty high, but in this case
we could be not able to suspend some computes for weeks.
After this commit, we won't initialize `last_active` on start, so
`/status` could return an unset attribute. This means that there was no
user activity since start. Control-plane should deal with it by taking
`max()` out of all available activity timestamps: `started_at`,
`last_active`, etc.
compute_ctl part of neondatabase/cloud#4853
Do several attempts to get spec from the control-plane and retry network
errors and all reasonable HTTP response codes. Do not hang waiting for
spec without confirmation from the control-plane that compute is known
and is in the `Empty` state.
Adjust the way we track `total_startup_ms` metric, it should be
calculated since the moment we received spec, not from the moment
`compute_ctl` started. Also introduce a new `wait_for_spec_ms` metric
to track the time spent sleeping and waiting for spec to be delivered
from control-plane.
Part of neondatabase/cloud#3533
Initially, idea was to ensure that when we come and check data
availability, special service table already contains one row. So if we
loose it for some reason, we will error out.
Yet, to do availability check we anyway start compute first! So it
doesn't really add some value, but we affect each compute start as we
update at least one row in the database. Also this writes some WAL, so
if timeline is close to `neon.max_cluster_size` it could prevent compute
from starting up.
That said, do CREATE TABLE IF NOT EXISTS + UPSERT right in the
`/check_writability` handler.
With this commit one can request compute reconfiguration
from the running `compute_ctl` with compute in `Running` state
by sending a new spec:
```shell
curl -d "{\"spec\": $(cat ./compute-spec-new.json)}" http://localhost:3080/configure
```
Internally, we start a separate configurator thread that is waiting on
`Condvar` for `ConfigurationPending` compute state in a loop. Then it does
reconfiguration, sets compute back to `Running` state and notifies other
waiters.
It will need some follow-ups, e.g. for retry logic for control-plane
requests, but should be useful for testing in the current state. This
shouldn't affect any existing environment, since computes are configured
in a different way there.
Resolvesneondatabase/cloud#4433
Sometimes, it contained real values, sometimes just defaults if the
spec was not received yet. Make the state more clear by making it an
Option instead.
One consequence is that if some of the required settings like
neon.tenant_id are missing from the spec file sent to the /configure
endpoint, it is spotted earlier and you get an immediate HTTP error
response. Not that it matters very much, but it's nicer nevertheless.
This is in preparation of using compute_ctl to launch postgres nodes
in the neon_local control plane. And seems like a good idea to
separate the public interfaces anyway.
One non-mechanical change here is that the 'metrics' field is moved
under the Mutex, instead of using atomics. We were not using atomics
for performance but for convenience here, and it seems more clear to
not use atomics in the model for the HTTP response type.
This commit adds an option to start compute without spec and then pass
it a valid spec via `POST /configure` API endpoint. This is a main
prerequisite for maintaining the pool of compute nodes in the
control-plane.
For example:
1. Start compute with
```shell
cargo run --bin compute_ctl -- -i no-compute \
-p http://localhost:9095 \
-D compute_pgdata \
-C "postgresql://cloud_admin@127.0.0.1:5434/postgres" \
-b ./pg_install/v15/bin/postgres
```
2. Configure it with
```shell
curl -d "{\"spec\": $(cat ./compute-spec.json)}" http://localhost:3080/configure
```
Internally, it's implemented using a `Condvar` + `Mutex`. Compute spec
is moved under Mutex, as it's now could be updated in the http handler.
Also `RwLock` was replaced with `Mutex` because the latter works well
with `Condvar`.
First part of the neondatabase/cloud#4433
After enabling autoscaling, we faced the issue that customers are not
able to get the number of CPUs they use at this moment. Therefore I've
added these two options:
1. Postgresql function to allow customers to call it whenever they want
2. `compute_ctl` endpoint to show these number in console
This commit adds a basic HTTP API endpoint that allows scraping the
`pg_stat_statements` data and getting a list of slow queries. New
insights like cache hit rate and so on could be added later.
Extension `pg_stat_statements` is checked / created only if compute
tries to load the corresponding shared library. The latter is configured
by control-plane and currently covered with feature flag.
Co-authored by Eduard Dyckman (bird.duskpoet@gmail.com)
Refactors Compute::prepare_and_run. It's split into subroutines
differently, to make it easier to attach tracing spans to the
different stages. The high-level logic for waiting for Postgres to
exit is moved to the caller.
Replace 'env_logger' with 'tracing', and add `#instrument` directives
to different stages fo the startup process. This is a fairly
mechanical change, except for the changes in 'spec.rs'. 'spec.rs'
contained some complicated formatting, where parts of log messages
were printed directly to stdout with `print`s. That was a bit messed
up because the log normally goes to stderr, but those lines were
printed to stdout. In our docker images, stderr and stdout both go to
the same place so you wouldn't notice, but I don't think it was
intentional.
This changes the log format to the default
'tracing_subscriber::format' format. It's different from the Postgres
log format, however, and because both compute_tools and Postgres print
to the same log, it's now a mix of two different formats. I'm not
sure how the Grafana log parsing pipeline can handle that. If it's a
problem, we can build custom formatter to change the compute_tools log
format to be the same as Postgres's, like it was before this commit,
or we can change the Postgres log format to match tracing_formatter's,
or we can start printing compute_tool's log output to a different
destination than Postgres
+ neondatabase/cloud#1103
This adds a couple of control endpoints to simplify compute state
discovery for control-plane. For example, now we may figure out
that Postgres wasn't able to start or basebackup failed within
seconds instead of just blindly polling the compute readiness
for a minute or two.
Also we now expose startup metrics (time of the each step: basebackup,
sync safekeepers, config, total). Console grabs them after each
successful start and report as histogram to prometheus and grafana.
OpenAPI spec is added and up-tp date, but is not currently used in the
console yet.
