## Problem
hyper auto-cancels the request futures on connection close.
`sql_over_http::handle` is not 'drop cancel safe', so we need to do some
other work to make sure connections are queries in the right way.
## Summary of changes
1. tokio::spawn the request handler to resolve the initial cancel-safety
issue
2. share a cancellation token, and cancel it when the request `Service`
is dropped.
3. Add a new log span to be able to track the HTTP connection lifecycle.
## Problem
Now that we have tls-listener vendored, we can refactor and remove a lot
of bloated code and make the whole flow a bit simpler
## Summary of changes
1. Remove dead code
2. Move the error handling to inside the `TlsListener` accept() function
3. Extract the peer_addr from the PROXY protocol header and log it with
errors
## Problem
Hard to find error reasons by endpoint for HTTP flow.
## Summary of changes
I want all root spans to have session id and endpoint id. I want all
root spans to be consistent.
## Problem
Proxy already supported HTTP2, but I expect no one is using it because
we don't advertise it in the TLS handshake.
## Summary of changes
#6335 without the websocket changes.
## Problem
Taking my ideas from https://github.com/neondatabase/neon/pull/6283 and
doing a bit less radical changes. smaller commits.
We currently don't report error classifications in proxy as the current
error handling made it hard to do so.
## Summary of changes
1. Add a `ReportableError` trait that all errors will implement. This
provides the error classification functionality.
2. Handle Client requests a strongly typed error
* this error is a `ReportableError` and is logged appropriately
3. The handle client error only has a few possible error types, to
account for the fact that at this point errors should be returned to the
user.
## Problem
The password check logic for the sql-over-http is a bit non-intuitive.
## Summary of changes
1. Perform scram auth using the same logic as for websocket cleartext
password.
2. Split establish connection logic and connection pool.
3. Parallelize param parsing logic with authentication + wake compute.
4. Limit the total number of clients
## Problem
not really any problem, just some drive-by changes
## Summary of changes
1. move wake compute
2. move json processing
3. move handle_try_wake
4. move test backend to api provider
5. reduce wake-compute concerns
6. remove duplicate wake-compute loop
## Problem
Taking my ideas from https://github.com/neondatabase/neon/pull/6283 and
doing a bit less radical changes. smaller commits.
Proxy flow was quite deeply nested, which makes adding more interesting
error handling quite tricky.
## Summary of changes
I recommend reviewing commit by commit.
1. move handshake logic into a separate file
2. move passthrough logic into a separate file
3. no longer accept a closure in CancelMap session logic
4. Remove connect_to_db, copy logic into handle_client
5. flatten auth_and_wake_compute in authenticate
6. record info for link auth
## Problem
http-over-sql allowes host to be in format api.aws.... however it's not
the case for the websocket flow.
## Summary of changes
Relax endpoint check for the ws serverless connections.
## Problem
HTTP connection pool was not respecting the PitR options.
## Summary of changes
1. refactor neon_options a bit to allow easier access to cache_key
2. make HTTP not go through `StartupMessageParams`
3. expose SNI processing to replace what was removed in step 2.
## Summary of changes
### RequestMonitoring
We want to add an event stream with information on each request for
easier analysis than what we can do with diagnostic logs alone
(https://github.com/neondatabase/cloud/issues/8807). This
RequestMonitoring will keep a record of the final state of a request. On
drop it will be pushed into a queue to be uploaded.
Because this context is a bag of data, I don't want this information to
impact logic of request handling. I personally think that weakly typed
data (such as all these options) makes for spaghetti code. I will
however allow for this data to impact rate-limiting and blocking of
requests, as this does not _really_ change how a request is handled.
### Parquet
Each `RequestMonitoring` is flushed into a channel where it is converted
into `RequestData`, which is accumulated into parquet files. Each file
will have a certain number of rows per row group, and several row groups
will eventually fill up the file, which we then upload to S3.
We will also upload smaller files if they take too long to construct.
## Problem
HTTP connection pool will grow without being pruned
## Summary of changes
Remove connection clients from pools once idle, or once they exit.
Periodically clear pool shards.
GC Logic:
Each shard contains a hashmap of `Arc<EndpointPool>`s.
Each connection stores a `Weak<EndpointPool>`.
During a GC sweep, we take a random shard write lock, and check that if
any of the `Arc<EndpointPool>`s are unique (using `Arc::get_mut`).
- If they are unique, then we check that the endpoint-pool is empty, and
sweep if it is.
- If they are not unique, then the endpoint-pool is in active use and we
don't sweep.
- Idle connections will self-clear from the endpoint-pool after 5
minutes.
Technically, the uniqueness of the endpoint-pool should be enough to
consider it empty, but the connection count check is done for
completeness sake.
## Problem
The `src/proxy.rs` file is far too large
## Summary of changes
Creates 3 new files:
```
src/metrics.rs
src/proxy/retry.rs
src/proxy/connect_compute.rs
```
## Problem
The websockets gauge for active db connections seems to be growing more
than the gauge for client connections over websockets, which does not
make sense.
## Summary of changes
refactor how our counter-pair gauges are represented. not sure if this
will improve the problem, but it should be harder to mess-up the
counters. The API is much nicer though now and doesn't require
scopeguard::defer hacks
## Problem
Single rate bucket is limited in usefulness
## Summary of changes
Introduce a secondary bucket allowing an average of 200 requests per
second over 1 minute, and a tertiary bucket allowing an average of 100
requests per second over 10 minutes.
Configured by using a format like
```sh
proxy --endpoint-rps-limit 300@1s --endpoint-rps-limit 100@10s --endpoint-rps-limit 50@1m
```
If the bucket limits are inconsistent, an error is returned on startup
```
$ proxy --endpoint-rps-limit 300@1s --endpoint-rps-limit 10@10s
Error: invalid endpoint RPS limits. 10@10s allows fewer requests per bucket than 300@1s (100 vs 300)
```
This is needed to allow use of batch queries from browsers.
## Problem
SQL-over-HTTP batch queries fail from web browsers because the relevant
headers, `Neon-Batch-isolation-Level` and `Neon-Batch-Read-Only`, are
not included in the server's OPTIONS response. I think we simply forgot
to add them when implementing the batch query feature.
## Summary of changes
Added `Neon-Batch-Isolation-Level` and `Neon-Batch-Read-Only` to the
OPTIONS response.
## Problem
1. Using chrono for durations only is wasteful
2. The arc/mutex was not being utilised
3. Locking every shard in the dashmap every GC could cause latency
spikes
4. More buckets
## Summary of changes
1. Use `Instant` instead of `NaiveTime`.
2. Remove the `Arc<Mutex<_>>` wrapper, utilising that dashmap entry
returns mut access
3. Clear only a random shard, update gc interval accordingly
4. Multiple buckets can be checked before allowing access
When I benchmarked the check function, it took on average 811ns when
multithreaded over the course of 10 million checks.
## Problem
The cancellation code was confusing and error prone (as seen before in
our memory leaks).
## Summary of changes
* Use the new `TaskTracker` primitve instead of JoinSet to gracefully
wait for tasks to shutdown.
* Updated libs/utils/completion to use `TaskTracker`
* Remove `tokio::select` in favour of `futures::future::select` in a
specialised `run_until_cancelled()` helper function
## Problem
Per-project IP allowlist:
https://github.com/neondatabase/cloud/issues/8116
## Summary of changes
Implemented IP filtering on the proxy side.
To retrieve ip allowlist for all scenarios, added `get_auth_info` call
to the control plane for:
* sql-over-http
* password_hack
* cleartext_hack
Added cache with ttl for sql-over-http path
This might slow down a bit, consider using redis in the future.
---------
Co-authored-by: Conrad Ludgate <conrad@neon.tech>
## Problem
Our serverless backend was a bit jumbled. As a comment indicated, we
were handling SQL-over-HTTP in our `websocket.rs` file.
I've extracted out the `sql_over_http` and `websocket` files from the
`http` module and put them into a new module called `serverless`.
## Summary of changes
```sh
mkdir proxy/src/serverless
mv proxy/src/http/{conn_pool,sql_over_http,websocket}.rs proxy/src/serverless/
mv proxy/src/http/server.rs proxy/src/http/health_server.rs
mv proxy/src/metrics proxy/src/usage_metrics.rs
```
I have also extracted the hyper server and handler from websocket.rs
into `serverless.rs`
