* refactor: move targetGroup struct and CheckOverflow() to their own package
* refactor: move auth and security related structs to a utility package, fix import error in utility package
* refactor: Azure SD, remove SD struct from config
* refactor: DNS SD, remove SD struct from config into dns package
* refactor: ec2 SD, move SD struct from config into the ec2 package
* refactor: file SD, move SD struct from config to file discovery package
* refactor: gce, move SD struct from config to gce discovery package
* refactor: move HTTPClientConfig and URL into util/config, fix import error in httputil
* refactor: consul, move SD struct from config into consul discovery package
* refactor: marathon, move SD struct from config into marathon discovery package
* refactor: triton, move SD struct from config to triton discovery package, fix test
* refactor: zookeeper, move SD structs from config to zookeeper discovery package
* refactor: openstack, remove SD struct from config, move into openstack discovery package
* refactor: kubernetes, move SD struct from config into kubernetes discovery package
* refactor: notifier, use targetgroup package instead of config
* refactor: tests for file, marathon, triton SD - use targetgroup package instead of config.TargetGroup
* refactor: retrieval, use targetgroup package instead of config.TargetGroup
* refactor: storage, use config util package
* refactor: discovery manager, use targetgroup package instead of config.TargetGroup
* refactor: use HTTPClient and TLS config from configUtil instead of config
* refactor: tests, use targetgroup package instead of config.TargetGroup
* refactor: fix tagetgroup.Group pointers that were removed by mistake
* refactor: openstack, kubernetes: drop prefixes
* refactor: remove import aliases forced due to vscode bug
* refactor: move main SD struct out of config into discovery/config
* refactor: rename configUtil to config_util
* refactor: rename yamlUtil to yaml_config
* refactor: kubernetes, remove prefixes
* refactor: move the TargetGroup package to discovery/
* refactor: fix order of imports
For special remote read endpoints which have only data for specific
queries, it is desired to limit the number of queries sent to the
configured remote read endpoint to reduce latency and performance
overhead.
* Decouple remote client from ReadRecent feature.
* Separate remote read filter into a small, testable function.
* Use storage.Queryable interface to compose independent
functionalities.
The labelsets returned from remote read are mutated in higher levels
(like seriesFilter.Labels()) and since the concreteSeriesSet didn't
return a copy, the external mutation affected the labelset in the
concreteSeries itself. This resulted in bizarre bugs where local and
remote series would show with identical label sets in the UI, but not be
deduplicated, since internally, a series might come to look like:
{__name__="node_load5", instance="192.168.1.202:12090", job="node_exporter", node="odroid", node="odroid"}
(note the repetition of the last label)
staticcheck fails with:
storage/remote/read_test.go:199:27: do not pass a nil Context, even if a function permits it; pass context.TODO if you are unsure about which Context to use (SA1012)
Currently all read queries are simply pushed to remote read clients.
This is fine, except for remote storage for wich it unefficient and
make query slower even if remote read is unnecessary.
So we need instead to compare the oldest timestamp in primary/local
storage with the query range lower boundary. If the oldest timestamp
is older than the mint parameter, then there is no need for remote read.
This is an optionnal behavior per remote read client.
Signed-off-by: Thibault Chataigner <t.chataigner@criteo.com>
* Re-add contexts to storage.Storage.Querier()
These are needed when replacing the storage by a multi-tenant
implementation where the tenant is stored in the context.
The 1.x query interfaces already had contexts, but they got lost in 2.x.
* Convert promql.Engine to use native contexts
This can happen in the situation where the system scales up the number of shards massively (to deal with some backlog), then scales it down again as the number of samples sent during the time period is less than the number received.
Each remote write endpoint gets its own set of relabeling rules.
This is based on the (yet-to-be-merged)
https://github.com/prometheus/prometheus/pull/2419, which removes legacy
remote write implementations.
This removes legacy support for specific remote storage systems in favor
of only offering the generic remote write protocol. An example bridge
application that translates from the generic protocol to each of those
legacy backends is still provided at:
documentation/examples/remote_storage/remote_storage_bridge
See also https://github.com/prometheus/prometheus/issues/10
The next step in the plan is to re-add support for multiple remote
storages.
* 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.
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.
By splitting the single queue into multiple queues and flushing each individual queue in serially (and all queues in parallel), we can guarantee to preserve the order of timestampsin samples sent to downstream systems.
- fold metric name into labels
- return initialization errors back to main
- add snappy compression
- better context handling
- pre-allocation of labels
- remove generic naming
- other cleanups
This uses a new proto format, with scope for multiple samples per
timeseries in future. This will allow users to pump samples out to
whatever they like without having to change the core Prometheus code.
There's also an example receiver to save users figuring out the
boilerplate themselves.
Specifically, the TestSpawnNotMoreThanMaxConcurrentSendsGoroutines was failing on a fresh checkout of master.
The test had a race condition -- it would only pass if one of the
spawned goroutines happened to very quickly pull a set of samples off an
internal queue.
This patch rewrites the test so that it deterministically waits until
all samples have been pulled off that queue. In case of errors, it also
now reports on the difference between what it expected and what it found.
I verified that, if the code under test is deliberately broken, the test
successfully reports on that.
Prometheus is Apache 2 licensed, and most source files have the
appropriate copyright license header, but some were missing it without
apparent reason. Correct that by adding it.
This gives up on the idea to communicate throuh the Append() call (by
either not returning as it is now or returning an error as
suggested/explored elsewhere). Here I have added a Throttled() call,
which has the advantage that it can be called before a whole _batch_
of Append()'s. Scrapes will happen completely or not at all. Same for
rule group evaluations. That's a highly desired behavior (as discussed
elsewhere). The code is even simpler now as the whole ingestion buffer
could be removed.
Logging of throttled mode has been streamlined and will create at most
one message per minute.
Allows to use graphite over tcp or udp. Metrics labels
and values are used to construct a valid Graphite path
in a way that will allow us to eventually read them back
and reconstruct the metrics.
For example, this metric:
model.Metric{
model.MetricNameLabel: "test:metric",
"testlabel": "test:value",
"testlabel2": "test:value",
)
Will become:
test:metric.testlabel=test:value.testlabel2=test:value
escape.go takes care of escaping values to match Graphite
character set, it basically uses percent-encoding as a fallback
wich will work pretty will in the graphite/grafana world.
The remote storage module also has an optional 'prefix' parameter
to prefix all metrics with a path (for example, 'prometheus.').
Graphite URLs are simply in the form tcp://host:port or
udp://host:port.
Because the InfluxDB client library currently pulls in multiple MBs of
unnecessary dependencies, I have modified and cut up the vendored
version to only pull in the few pieces that are actually needed.
On InfluxDB's side, this dependency issue is tracked in:
https://github.com/influxdb/influxdb/issues/3447
Hopefully, it will be resolved soon.
If a password is needed for InfluxDB, it may be supplied via the
INFLUXDB_PW environment variable.
Allow scrape_configs to have an optional proxy_url option which specifies
a proxy to be used for all connections to hosts in that config.
Internally this modifies the various client functions to take a *url.URL pointer
which currently must point to an HTTP proxy (but has been left open-ended to
allow the url format to be extended to support others, such as maybe SOCKS if
needed).
This change is conceptually very simple, although the diff is large. It
switches logging from "github.com/golang/glog" to
"github.com/prometheus/log", while not actually changing any log
messages. V(1)-style logging has been changed to be log.Debug*().
