Files
neon/compute_tools
Heikki Linnakangas 8bb45fd5da Introduce built-in Prometheus exporter to the Postgres extension (#12591)
Currently, the exporter exposes the same LFC metrics that are exposed by
the "autoscaling" sql_exporter in the docker image. With this, we can
remove the dedicated sql_exporter instance. (Actually doing the removal
is left as a TODO until this is rolled out to production and we have
changed autoscaling-agent to fetch the metrics from this new endpoint.)

The exporter runs as a Postgres background worker process. This is
extracted from the Rust communicator rewrite project, which will use the
same worker process for much more, to handle the communications with the
pageservers. For now, though, it merely handles the metrics requests.

In the future, we will add more metrics, and perhaps even APIs to
control the running Postgres instance.

The exporter listens on a Unix Domain socket within the Postgres data
directory. A Unix Domain socket is a bit unconventional, but it has some
advantages:

- Permissions are taken care of. Only processes that can access the data
directory, and therefore already have full access to the running
Postgres instance, can connect to it.

- No need to allocate and manage a new port number for the listener

It has some downsides too: it's not immediately accessible from the
outside world, and the functions to work with Unix Domain sockets are
more low-level than TCP sockets (see the symlink hack in
`postgres_metrics_client.rs`, for example).

To expose the metrics from the local Unix Domain Socket to the
autoscaling agent, introduce a new '/autoscaling_metrics' endpoint in
the compute_ctl's HTTP server. Currently it merely forwards the request
to the Postgres instance, but we could add rate limiting and access
control there in the future.

---------

Co-authored-by: Conrad Ludgate <conrad@neon.tech>
2025-07-22 12:00:20 +00:00
..

Compute node tools

Postgres wrapper (compute_ctl) is intended to be run as a Docker entrypoint or as a systemd ExecStart option. It will handle all the Neon specifics during compute node initialization:

  • compute_ctl accepts cluster (compute node) specification as a JSON file.
  • Every start is a fresh start, so the data directory is removed and initialized again on each run.
  • Next it will put configuration files into the PGDATA directory.
  • Sync safekeepers and get commit LSN.
  • Get basebackup from pageserver using the returned on the previous step LSN.
  • Try to start postgres and wait until it is ready to accept connections.
  • Check and alter/drop/create roles and databases.
  • Hang waiting on the postmaster process to exit.

Also compute_ctl spawns two separate service threads:

  • compute-monitor checks the last Postgres activity timestamp and saves it into the shared ComputeNode;
  • http-endpoint runs a Hyper HTTP API server, which serves readiness and the last activity requests.

If AUTOSCALING environment variable is set, compute_ctl will start the vm-monitor located in [neon/libs/vm_monitor]. For VM compute nodes, vm-monitor communicates with the VM autoscaling system. It coordinates downscaling and requests immediate upscaling under resource pressure.

Usage example:

compute_ctl -D /var/db/postgres/compute \
            -C 'postgresql://cloud_admin@localhost/postgres' \
            -S /var/db/postgres/specs/current.json \
            -b /usr/local/bin/postgres

State Diagram

Computes can be in various states. Below is a diagram that details how a compute moves between states.

%% https://mermaid.js.org/syntax/stateDiagram.html
stateDiagram-v2
  [*] --> Empty : Compute spawned
  Empty --> ConfigurationPending : Waiting for compute spec
  ConfigurationPending --> Configuration : Received compute spec
  Configuration --> Failed : Failed to configure the compute
  Configuration --> Running : Compute has been configured
  Empty --> Init : Compute spec is immediately available
  Empty --> TerminationPendingFast : Requested termination
  Empty --> TerminationPendingImmediate : Requested termination
  Init --> Failed : Failed to start Postgres
  Init --> Running : Started Postgres
  Running --> TerminationPendingFast : Requested termination
  Running --> TerminationPendingImmediate : Requested termination
  TerminationPendingFast --> Terminated compute with 30s delay for cplane to inspect status
  TerminationPendingImmediate --> Terminated : Terminated compute immediately
  Failed --> [*] : Compute exited
  Terminated --> [*] : Compute exited

Tests

Cargo formatter:

cargo fmt

Run tests:

cargo test

Clippy linter:

cargo clippy --all --all-targets -- -Dwarnings -Drust-2018-idioms

Cross-platform compilation

Imaging that you are on macOS (x86) and you want a Linux GNU (x86_64-unknown-linux-gnu platform in rust terminology) executable.

Using docker

You can use a throw-away Docker container (rustlang/rust image) for doing that:

docker run --rm \
    -v $(pwd):/compute_tools \
    -w /compute_tools \
    -t rustlang/rust:nightly cargo build --release --target=x86_64-unknown-linux-gnu

or one-line:

docker run --rm -v $(pwd):/compute_tools -w /compute_tools -t rust:latest cargo build --release --target=x86_64-unknown-linux-gnu

Using rust native cross-compilation

Another way is to add x86_64-unknown-linux-gnu target on your host system:

rustup target add x86_64-unknown-linux-gnu

Install macOS cross-compiler toolchain:

brew tap SergioBenitez/osxct
brew install x86_64-unknown-linux-gnu

And finally run cargo build:

CARGO_TARGET_X86_64_UNKNOWN_LINUX_GNU_LINKER=x86_64-unknown-linux-gnu-gcc cargo build --target=x86_64-unknown-linux-gnu --release