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>
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_ctlaccepts 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
PGDATAdirectory. - Sync safekeepers and get commit LSN.
- Get
basebackupfrom pageserver using the returned on the previous step LSN. - Try to start
postgresand wait until it is ready to accept connections. - Check and alter/drop/create roles and databases.
- Hang waiting on the
postmasterprocess to exit.
Also compute_ctl spawns two separate service threads:
compute-monitorchecks the last Postgres activity timestamp and saves it into the sharedComputeNode;http-endpointruns 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