## Problem
Actually read redis events.
## Summary of changes
This is revert of https://github.com/neondatabase/neon/pull/7350 +
fixes.
* Fixed events parsing
* Added timeout after connection failure
* Separated regional and global redis clients.
## Problem
My benchmarks show that prometheus is not very good.
https://github.com/conradludgate/measured
We're already using it in storage_controller and it seems to be working
well.
## Summary of changes
Replace prometheus with my new measured crate in proxy only.
Apologies for the large diff. I tried to keep it as minimal as I could.
The label types add a bit of boiler plate (but reduce the chance we
mistype the labels), and some of our custom metrics like CounterPair and
HLL needed to be rewritten.
## Problem
Proxy doesn't know about existing endpoints.
## Summary of changes
* Added caching of all available endpoints.
* On the high load, use it before going to cplane.
* Report metrics for the outcome.
* For rate limiter and credentials caching don't distinguish between
`-pooled` and not
TODOs:
* Make metrics more meaningful
* Consider integrating it with the endpoint rate limiter
* Test it together with cplane in preview
## Problem
https://github.com/neondatabase/cloud/issues/9642
## Summary of changes
1. Make `EndpointRateLimiter` generic, renamed as `BucketRateLimiter`
2. Add support for claiming multiple tokens at once
3. Add `AuthRateLimiter` alias.
4. Check `(Endpoint, IP)` pair during authentication, weighted by how
many hashes proxy would be doing.
TODO: handle ipv6 subnets. will do this in a separate PR.
## Problem
Support of IAM Roles for Service Accounts for authentication.
## Summary of changes
* Obtain aws 15m-long credentials
* Retrieve redis password from credentials
* Update every 1h to keep connection for more than 12h
* For now allow to have different endpoints for pubsub/stream redis.
TODOs:
* PubSub doesn't support credentials refresh, consider using stream
instead.
* We need an AWS role for proxy to be able to connect to both: S3 and
elasticache.
Credentials obtaining and connection refresh was tested on xenon
preview.
https://github.com/neondatabase/cloud/issues/10365
## Problem
Currently cplane communication is a part of the latency monitoring. It
doesn't allow to setup the proper alerting based on proxy latency.
## Summary of changes
Added dimension to exclude cplane latency.
## Problem
For the ephemeral endpoint feature, it's not really too helpful to keep
them around in the connection pool. This isn't really pressing but I
think it's still a bit better this way.
## Summary of changes
Add `is_ephemeral` function to `NeonOptions`. Allow
`serverless::ConnInfo::endpoint_cache_key()` to return an `Option`.
Handle that option appropriately
## 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
In a recent refactor, we accidentally dropped the cancel session early
## Summary of changes
Hold the cancel session during proxy passthrough
## Problem
Not really a problem, just refactoring.
## Summary of changes
Separate authenticate from wake compute.
Do not call wake compute second time if we managed to connect to
postgres or if we got it not from cache.
## Problem
`tokio::io::copy_bidirectional` doesn't close the connection once one of
the sides closes it. It's not really suitable for the postgres protocol.
## Summary of changes
Fork `copy_bidirectional` and initiate a shutdown for both connections.
---------
Co-authored-by: Conrad Ludgate <conradludgate@gmail.com>
## 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
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
too many string based IDs. easy to mix up ID types.
## Summary of changes
Add a bunch of `SmolStr` wrappers that provide convenience methods but
are type safe
## Problem
Some fields were missed in the initial spec.
## Summary of changes
Adds a success boolean (defaults to false unless specifically marked as
successful).
Adds a duration_us integer that tracks how many microseconds were taken
from session start through to request completion.
## 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
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)
```
## 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
In snowflake logs currently there is no information about the protocol,
that the client uses.
## Summary of changes
Propagate the information about the protocol together with the app_name.
In format: `{app_name}/{sql_over_http/tcp/ws}`.
This will give to @stepashka more observability on what our clients are
using.
## 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
It looks like because of reallocation of the buckets in previous PR, the
metric is broken in graphana.
## Summary of changes
Renamed the metric.
## Problem
no problem
## Summary of changes
replaces boxstr with arcstr as it's cheaper to clone. mild perf
improvement.
probably should look into other smallstring optimsations tbh, they will
likely be even better. The longest endpoint name I was able to construct
is something like `ep-weathered-wildflower-12345678` which is 32 bytes.
Most string optimisations top out at 23 bytes
## 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
channel binding protects scram from sophisticated MITM attacks where the
attacker is able to produce 'valid' TLS certificates.
## Summary of changes
get the tls-server-end-point channel binding, and verify it is correct
for the SCRAM-SHA-256-PLUS authentication flow
## Problem
The connections.join_next helped but it wasn't enough... The way I
implemented the improvement before was still faulty but it mostly worked
so it looked like it was working correctly.
From [`tokio::select`
docs](https://docs.rs/tokio/latest/tokio/macro.select.html):
> 4. Once an <async expression> returns a value, attempt to apply the
value to the provided <pattern>, if the pattern matches, evaluate
<handler> and return. If the pattern does not match, disable the current
branch and for the remainder of the current call to select!. Continue
from step 3.
The `connections.join_next()` future would complete and `Some(Err(e))`
branch would be evaluated but not match (as the future would complete
without panicking, we would hope). Since the branch doesn't match, it's
disabled. The select continues but never attempts to call `join_next`
again. Getting unlucky, more TCP connections are created than we attempt
to join_next.
## Summary of changes
Replace the `Some(Err(e))` pattern with `Some(e)`. Because of the
auto-disabling feature, we don't need the `if !connections.is_empty()`
step as the `None` pattern will disable it for us.
## Problem
We don't know the number of users with the different kind of
authentication: ["sni", "endpoint in options" (A and B from
[here](https://neon.tech/docs/connect/connection-errors)),
"password_hack"]
## Summary of changes
Collect metrics by sni kind.
## Problem
A user can perform many database connections at the same instant of time
- these will all cache miss and materialise as requests to the control
plane. #5705
## Summary of changes
I am using a `DashMap` (a sharded `RwLock<HashMap>`) of endpoints ->
semaphores to apply a limiter. If the limiter is enabled (permits > 0),
the semaphore will be retrieved per endpoint and a permit will be
awaited before continuing to call the wake_compute endpoint.
### Important details
This dashmap would grow uncontrollably without maintenance. It's not a
cache so I don't think an LRU-based reclamation makes sense. Instead,
I've made use of the sharding functionality of DashMap to lock a single
shard and clear out unused semaphores periodically.
I ran a test in release, using 128 tokio tasks among 12 threads each
pushing 1000 entries into the map per second, clearing a shard every 2
seconds (64 second epoch with 32 shards). The endpoint names were
sampled from a gamma distribution to make sure some overlap would occur,
and each permit was held for 1ms. The histogram for time to clear each
shard settled between 256-512us without any variance in my testing.
Holding a lock for under a millisecond for 1 of the shards does not
concern me as blocking
The idea is to pass neon_* prefixed options to control plane. It can be
used by cplane to dynamically create timelines and computes. Such
options also should be excluded from passing to compute. Another issue
is how connection caching is working now, because compute's instance now
depends not only on hostname but probably on such options too I included
them to cache key.
## Problem
In #5539, I moved the connect_to_compute latency to start counting
before authentication - this is because authentication will perform some
calls to the control plane in order to get credentials and to eagerly
wake a compute server. It felt important to include these times in the
latency metric as these are times we should definitely care about
reducing.
What is not interesting to record in this metric is the roundtrip time
during authentication when we wait for the client to respond.
## Summary of changes
Implement a mechanism to pause the latency timer, resuming on drop of
the pause struct. We pause the timer right before we send the
authentication message to the client, and we resume the timer right
after we complete the authentication flow.
## 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`
## Problem
I recently updated the latency timers to include cache miss and pool
miss, as well as connection protocol. By moving the latency timer to
start before authentication, we count a lot more failures and it's
messed up the latency dashboard.
## Summary of changes
Add another label to LatencyTimer metrics for outcome. Explicitly report
on success
## Problem
We need a flag to require proxy protocol (prerequisite for #5416)
## Summary of changes
Add a cli flag to require client IP addresses. Error if IP address is
missing when the flag is active.
