This is a followup to https://github.com/prometheus/prometheus/pull/2011.
This publishes more of the methods and other names of the chunk code and
moves the chunk code to its own package. There's some unavoidable
ugliness: the chunk and chunkDesc metrics are used by both packages, so
I had to move them to the chunk package. That isn't great, but I don't
see how to do it better without a larger redesign of everything. Same
for the evict requests and some other types.
* Add config, HTTP Basic Auth and TLS support to the generic write path.
- Move generic write path configuration to the config file
- Factor out config.TLSConfig -> tlf.Config translation
- Support TLSConfig for generic remote storage
- Rename Run to Start, and make it non-blocking.
- Dedupe code in httputil for TLS config.
- Make remote queue metrics global.
This is based on https://github.com/prometheus/prometheus/pull/1997.
This adds contexts to the relevant Storage methods and already passes
PromQL's new per-query context into the storage's query methods.
The immediate motivation supporting multi-tenancy in Frankenstein, but
this could also be used by Prometheus's normal local storage to support
cancellations and timeouts at some point.
For Weaveworks' Frankenstein, we need to support multitenancy. In
Frankenstein, we initially solved this without modifying the promql
package at all: we constructed a new promql.Engine for every
query and injected a storage implementation into that engine which would
be primed to only collect data for a given user.
This is problematic to upstream, however. Prometheus assumes that there
is only one engine: the query concurrency gate is part of the engine,
and the engine contains one central cancellable context to shut down all
queries. Also, creating a new engine for every query seems like overkill.
Thus, we want to be able to pass per-query contexts into a single engine.
This change gets rid of the promql.Engine's built-in base context and
allows passing in a per-query context instead. Central cancellation of
all queries is still possible by deriving all passed-in contexts from
one central one, but this is now the responsibility of the caller. The
central query context is now created in main() and passed into the
relevant components (web handler / API, rule manager).
In a next step, the per-query context would have to be passed to the
storage implementation, so that the storage can implement multi-tenancy
or other features based on the contextual information.
CPUs have to serialise write access to a single cache line
effectively reducing level of possible parallelism. Placing
mutexes on different cache lines avoids this problem.
Most gains will be seen on NUMA servers where CPU interconnect
traffic is especially expensive
Before:
go test . -run none -bench BenchmarkFingerprintLocker
BenchmarkFingerprintLockerParallel-4 2000000 932 ns/op
BenchmarkFingerprintLockerSerial-4 30000000 49.6 ns/op
After:
go test . -run none -bench BenchmarkFingerprintLocker
BenchmarkFingerprintLockerParallel-4 3000000 569 ns/op
BenchmarkFingerprintLockerSerial-4 30000000 51.0 ns/op
Due to bad GitHub connectivity, "make" frequently got stuck at the promu
step for me, and I was thinking that "format" was taking a long time
because the promu step wasn't logged. All other Makefile targets have
log statements...
My aim is to support the new grpc generic write path in Frankenstein. On the surface this seems easy - however I've hit a number of problems that make me think it might be better to not use grpc just yet.
The explanation of the problems requires a little background. At weave, traffic to frankenstein need to go through a couple of services first, for SSL and to be authenticated. So traffic goes:
internet -> frontend -> authfe -> frankenstein
- The frontend is Nginx, and adds/removes SSL. Its done this way for legacy reasons, so the certs can be managed in one place, although eventually we imagine we'll merge it with authfe. All traffic from frontend is sent to authfe.
- Authfe checks the auth tokens / cookie etc and then picks the service to forward the RPC to.
- Frankenstein accepts the reads and does the right thing with them.
First problem I hit was Nginx won't proxy http2 requests - it can accept them, but all calls downstream are http1 (see https://trac.nginx.org/nginx/ticket/923). This wasn't such a big deal, so it now looks like:
internet --(grpc/http2)--> frontend --(grpc/http1)--> authfe --(grpc/http1)--> frankenstein
Next problem was golang grpc server won't accept http1 requests (see https://groups.google.com/forum/#!topic/grpc-io/JnjCYGPMUms). It is possible to link a grpc server in with a normal go http mux, as long as the mux server is serving over SSL, as the golang http client & server won't do http2 over anything other than an SSL connection. This would require making all our service to service comms SSL. So I had a go a writing a grpc http1 server, and got pretty far. But is was a bit of a mess.
So finally I thought I'd make a separate grpc frontend for this, running in parallel with the frontend/authfe combo on a different port - and first up I'd need a grpc reverse proxy. Ideally we'd have some nice, generic reverse proxy that only knew about a map from service names -> downstream service, and didn't need to decode & re-encode every request as it went through. It seems like this can't be done with golang's grpc library - see https://github.com/mwitkow/grpc-proxy/issues/1.
And then I was surprised to find you can't do grpc from browsers! See http://www.grpc.io/faq/ - not important to us, but I'm starting to question why we decided to use grpc in the first place?
It would seem we could have most of the benefits of grpc with protos over HTTP, and this wouldn't preclude moving to grpc when its a bit more mature? In fact, the grcp FAQ even admits as much:
> Why is gRPC better than any binary blob over HTTP/2?
> This is largely what gRPC is on the wire.
