We have rare walredo failures with pg16.
Let's introduce recording of failing walredo input in `#[cfg(feature =
"testing")]`. There is additional logging (the value reconstruction path
logging usually shown with not found keys), keeping it for
`#[cfg(features = "testing")]`.
Cc: #5404.
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
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
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.
Currently it's included with minimal changes and lives aside of the main
workspace. Later we may re-use and combine common parts with zenith
control_plane.
This change is mostly needed to unify cloud deployment pipeline:
1.1. build compute-tools image
1.2. build compute-node image based on the freshly built compute-tools
2. build zenith image
So we can roll new compute image and new storage required by it to
operate properly. Also it becomes easier to test console against some
specific version of compute-node/-tools.
