mirror of
https://github.com/ceph/ceph-csi.git
synced 2024-11-14 10:20:20 +00:00
248 lines
13 KiB
Markdown
248 lines
13 KiB
Markdown
# Go gRPC Interceptors for Prometheus monitoring
|
|
|
|
[](https://travis-ci.org/grpc-ecosystem/go-grpc-prometheus)
|
|
[](http://goreportcard.com/report/grpc-ecosystem/go-grpc-prometheus)
|
|
[](https://godoc.org/github.com/grpc-ecosystem/go-grpc-prometheus)
|
|
[](https://sourcegraph.com/github.com/grpc-ecosystem/go-grpc-prometheus/?badge)
|
|
[](https://codecov.io/gh/grpc-ecosystem/go-grpc-prometheus)
|
|
[](LICENSE)
|
|
|
|
[Prometheus](https://prometheus.io/) monitoring for your [gRPC Go](https://github.com/grpc/grpc-go) servers and clients.
|
|
|
|
A sister implementation for [gRPC Java](https://github.com/grpc/grpc-java) (same metrics, same semantics) is in [grpc-ecosystem/java-grpc-prometheus](https://github.com/grpc-ecosystem/java-grpc-prometheus).
|
|
|
|
## Interceptors
|
|
|
|
[gRPC Go](https://github.com/grpc/grpc-go) recently acquired support for Interceptors, i.e. middleware that is executed
|
|
by a gRPC Server before the request is passed onto the user's application logic. It is a perfect way to implement
|
|
common patterns: auth, logging and... monitoring.
|
|
|
|
To use Interceptors in chains, please see [`go-grpc-middleware`](https://github.com/mwitkow/go-grpc-middleware).
|
|
|
|
## Usage
|
|
|
|
There are two types of interceptors: client-side and server-side. This package provides monitoring Interceptors for both.
|
|
|
|
### Server-side
|
|
|
|
```go
|
|
import "github.com/grpc-ecosystem/go-grpc-prometheus"
|
|
...
|
|
// Initialize your gRPC server's interceptor.
|
|
myServer := grpc.NewServer(
|
|
grpc.StreamInterceptor(grpc_prometheus.StreamServerInterceptor),
|
|
grpc.UnaryInterceptor(grpc_prometheus.UnaryServerInterceptor),
|
|
)
|
|
// Register your gRPC service implementations.
|
|
myservice.RegisterMyServiceServer(s.server, &myServiceImpl{})
|
|
// After all your registrations, make sure all of the Prometheus metrics are initialized.
|
|
grpc_prometheus.Register(myServer)
|
|
// Register Prometheus metrics handler.
|
|
http.Handle("/metrics", promhttp.Handler())
|
|
...
|
|
```
|
|
|
|
### Client-side
|
|
|
|
```go
|
|
import "github.com/grpc-ecosystem/go-grpc-prometheus"
|
|
...
|
|
clientConn, err = grpc.Dial(
|
|
address,
|
|
grpc.WithUnaryInterceptor(grpc_prometheus.UnaryClientInterceptor),
|
|
grpc.WithStreamInterceptor(grpc_prometheus.StreamClientInterceptor)
|
|
)
|
|
client = pb_testproto.NewTestServiceClient(clientConn)
|
|
resp, err := client.PingEmpty(s.ctx, &myservice.Request{Msg: "hello"})
|
|
...
|
|
```
|
|
|
|
# Metrics
|
|
|
|
## Labels
|
|
|
|
All server-side metrics start with `grpc_server` as Prometheus subsystem name. All client-side metrics start with `grpc_client`. Both of them have mirror-concepts. Similarly all methods
|
|
contain the same rich labels:
|
|
|
|
* `grpc_service` - the [gRPC service](http://www.grpc.io/docs/#defining-a-service) name, which is the combination of protobuf `package` and
|
|
the `grpc_service` section name. E.g. for `package = mwitkow.testproto` and
|
|
`service TestService` the label will be `grpc_service="mwitkow.testproto.TestService"`
|
|
* `grpc_method` - the name of the method called on the gRPC service. E.g.
|
|
`grpc_method="Ping"`
|
|
* `grpc_type` - the gRPC [type of request](http://www.grpc.io/docs/guides/concepts.html#rpc-life-cycle).
|
|
Differentiating between the two is important especially for latency measurements.
|
|
|
|
- `unary` is single request, single response RPC
|
|
- `client_stream` is a multi-request, single response RPC
|
|
- `server_stream` is a single request, multi-response RPC
|
|
- `bidi_stream` is a multi-request, multi-response RPC
|
|
|
|
|
|
Additionally for completed RPCs, the following labels are used:
|
|
|
|
* `grpc_code` - the human-readable [gRPC status code](https://github.com/grpc/grpc-go/blob/master/codes/codes.go).
|
|
The list of all statuses is to long, but here are some common ones:
|
|
|
|
- `OK` - means the RPC was successful
|
|
- `IllegalArgument` - RPC contained bad values
|
|
- `Internal` - server-side error not disclosed to the clients
|
|
|
|
## Counters
|
|
|
|
The counters and their up to date documentation is in [server_reporter.go](server_reporter.go) and [client_reporter.go](client_reporter.go)
|
|
the respective Prometheus handler (usually `/metrics`).
|
|
|
|
For the purpose of this documentation we will only discuss `grpc_server` metrics. The `grpc_client` ones contain mirror concepts.
|
|
|
|
For simplicity, let's assume we're tracking a single server-side RPC call of [`mwitkow.testproto.TestService`](examples/testproto/test.proto),
|
|
calling the method `PingList`. The call succeeds and returns 20 messages in the stream.
|
|
|
|
First, immediately after the server receives the call it will increment the
|
|
`grpc_server_started_total` and start the handling time clock (if histograms are enabled).
|
|
|
|
```jsoniq
|
|
grpc_server_started_total{grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream"} 1
|
|
```
|
|
|
|
Then the user logic gets invoked. It receives one message from the client containing the request
|
|
(it's a `server_stream`):
|
|
|
|
```jsoniq
|
|
grpc_server_msg_received_total{grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream"} 1
|
|
```
|
|
|
|
The user logic may return an error, or send multiple messages back to the client. In this case, on
|
|
each of the 20 messages sent back, a counter will be incremented:
|
|
|
|
```jsoniq
|
|
grpc_server_msg_sent_total{grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream"} 20
|
|
```
|
|
|
|
After the call completes, its status (`OK` or other [gRPC status code](https://github.com/grpc/grpc-go/blob/master/codes/codes.go))
|
|
and the relevant call labels increment the `grpc_server_handled_total` counter.
|
|
|
|
```jsoniq
|
|
grpc_server_handled_total{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream"} 1
|
|
```
|
|
|
|
## Histograms
|
|
|
|
[Prometheus histograms](https://prometheus.io/docs/concepts/metric_types/#histogram) are a great way
|
|
to measure latency distributions of your RPCs. However, since it is bad practice to have metrics
|
|
of [high cardinality](https://prometheus.io/docs/practices/instrumentation/#do-not-overuse-labels)
|
|
the latency monitoring metrics are disabled by default. To enable them please call the following
|
|
in your server initialization code:
|
|
|
|
```jsoniq
|
|
grpc_prometheus.EnableHandlingTimeHistogram()
|
|
```
|
|
|
|
After the call completes, its handling time will be recorded in a [Prometheus histogram](https://prometheus.io/docs/concepts/metric_types/#histogram)
|
|
variable `grpc_server_handling_seconds`. The histogram variable contains three sub-metrics:
|
|
|
|
* `grpc_server_handling_seconds_count` - the count of all completed RPCs by status and method
|
|
* `grpc_server_handling_seconds_sum` - cumulative time of RPCs by status and method, useful for
|
|
calculating average handling times
|
|
* `grpc_server_handling_seconds_bucket` - contains the counts of RPCs by status and method in respective
|
|
handling-time buckets. These buckets can be used by Prometheus to estimate SLAs (see [here](https://prometheus.io/docs/practices/histograms/))
|
|
|
|
The counter values will look as follows:
|
|
|
|
```jsoniq
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="0.005"} 1
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="0.01"} 1
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="0.025"} 1
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="0.05"} 1
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="0.1"} 1
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="0.25"} 1
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="0.5"} 1
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="1"} 1
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="2.5"} 1
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="5"} 1
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="10"} 1
|
|
grpc_server_handling_seconds_bucket{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream",le="+Inf"} 1
|
|
grpc_server_handling_seconds_sum{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream"} 0.0003866430000000001
|
|
grpc_server_handling_seconds_count{grpc_code="OK",grpc_method="PingList",grpc_service="mwitkow.testproto.TestService",grpc_type="server_stream"} 1
|
|
```
|
|
|
|
|
|
## Useful query examples
|
|
|
|
Prometheus philosophy is to provide raw metrics to the monitoring system, and
|
|
let the aggregations be handled there. The verbosity of above metrics make it possible to have that
|
|
flexibility. Here's a couple of useful monitoring queries:
|
|
|
|
|
|
### request inbound rate
|
|
```jsoniq
|
|
sum(rate(grpc_server_started_total{job="foo"}[1m])) by (grpc_service)
|
|
```
|
|
For `job="foo"` (common label to differentiate between Prometheus monitoring targets), calculate the
|
|
rate of requests per second (1 minute window) for each gRPC `grpc_service` that the job has. Please note
|
|
how the `grpc_method` is being omitted here: all methods of a given gRPC service will be summed together.
|
|
|
|
### unary request error rate
|
|
```jsoniq
|
|
sum(rate(grpc_server_handled_total{job="foo",grpc_type="unary",grpc_code!="OK"}[1m])) by (grpc_service)
|
|
```
|
|
For `job="foo"`, calculate the per-`grpc_service` rate of `unary` (1:1) RPCs that failed, i.e. the
|
|
ones that didn't finish with `OK` code.
|
|
|
|
### unary request error percentage
|
|
```jsoniq
|
|
sum(rate(grpc_server_handled_total{job="foo",grpc_type="unary",grpc_code!="OK"}[1m])) by (grpc_service)
|
|
/
|
|
sum(rate(grpc_server_started_total{job="foo",grpc_type="unary"}[1m])) by (grpc_service)
|
|
* 100.0
|
|
```
|
|
For `job="foo"`, calculate the percentage of failed requests by service. It's easy to notice that
|
|
this is a combination of the two above examples. This is an example of a query you would like to
|
|
[alert on](https://prometheus.io/docs/alerting/rules/) in your system for SLA violations, e.g.
|
|
"no more than 1% requests should fail".
|
|
|
|
### average response stream size
|
|
```jsoniq
|
|
sum(rate(grpc_server_msg_sent_total{job="foo",grpc_type="server_stream"}[10m])) by (grpc_service)
|
|
/
|
|
sum(rate(grpc_server_started_total{job="foo",grpc_type="server_stream"}[10m])) by (grpc_service)
|
|
```
|
|
For `job="foo"` what is the `grpc_service`-wide `10m` average of messages returned for all `
|
|
server_stream` RPCs. This allows you to track the stream sizes returned by your system, e.g. allows
|
|
you to track when clients started to send "wide" queries that ret
|
|
Note the divisor is the number of started RPCs, in order to account for in-flight requests.
|
|
|
|
### 99%-tile latency of unary requests
|
|
```jsoniq
|
|
histogram_quantile(0.99,
|
|
sum(rate(grpc_server_handling_seconds_bucket{job="foo",grpc_type="unary"}[5m])) by (grpc_service,le)
|
|
)
|
|
```
|
|
For `job="foo"`, returns an 99%-tile [quantile estimation](https://prometheus.io/docs/practices/histograms/#quantiles)
|
|
of the handling time of RPCs per service. Please note the `5m` rate, this means that the quantile
|
|
estimation will take samples in a rolling `5m` window. When combined with other quantiles
|
|
(e.g. 50%, 90%), this query gives you tremendous insight into the responsiveness of your system
|
|
(e.g. impact of caching).
|
|
|
|
### percentage of slow unary queries (>250ms)
|
|
```jsoniq
|
|
100.0 - (
|
|
sum(rate(grpc_server_handling_seconds_bucket{job="foo",grpc_type="unary",le="0.25"}[5m])) by (grpc_service)
|
|
/
|
|
sum(rate(grpc_server_handling_seconds_count{job="foo",grpc_type="unary"}[5m])) by (grpc_service)
|
|
) * 100.0
|
|
```
|
|
For `job="foo"` calculate the by-`grpc_service` fraction of slow requests that took longer than `0.25`
|
|
seconds. This query is relatively complex, since the Prometheus aggregations use `le` (less or equal)
|
|
buckets, meaning that counting "fast" requests fractions is easier. However, simple maths helps.
|
|
This is an example of a query you would like to alert on in your system for SLA violations,
|
|
e.g. "less than 1% of requests are slower than 250ms".
|
|
|
|
|
|
## Status
|
|
|
|
This code has been used since August 2015 as the basis for monitoring of *production* gRPC micro services at [Improbable](https://improbable.io).
|
|
|
|
## License
|
|
|
|
`go-grpc-prometheus` is released under the Apache 2.0 license. See the [LICENSE](LICENSE) file for details.
|