280eaf33f0
* Use global string map for MatchType.String()
We were unnecessarily creating a new map for each call of String().
This is a 10x improvement in MatchType.String() performance in time,
from 53ns to 4ns on my i7 laptop, and I guess that this method is being
called quite often so why throw out the resources.
I was surprised that benchmark says that there are no allocations made
in the old version.
I also tries using `//go:generate stringer` and the result is even
better, at about 2.8ns, but having to keep the generated code updated
isn't worth the change (at least it's bigger than a small change I was
intended to do)
Benchmark comparison:
name \ time/op old global_map stringer
MatchType_String 53.6ns ± 1% 4.1ns ± 1% 2.8ns ± 1%
name \ alloc/op old global_map stringer
MatchType_String 0.00B 0.00B 0.00B
name \ allocs/op old global_map stringer
MatchType_String 0.00 0.00 0.00
Old benchmark:
goos: darwin
goarch: amd64
pkg: github.com/prometheus/prometheus/pkg/labels
cpu: Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz
BenchmarkMatchType_String 21766578 54.36 ns/op 0 B/op 0 allocs/op
BenchmarkMatchType_String 21742339 53.28 ns/op 0 B/op 0 allocs/op
BenchmarkMatchType_String 21985470 53.37 ns/op 0 B/op 0 allocs/op
BenchmarkMatchType_String 21676282 53.50 ns/op 0 B/op 0 allocs/op
BenchmarkMatchType_String 22075573 53.33 ns/op 0 B/op 0 allocs/op
PASS
ok github.com/prometheus/prometheus/pkg/labels 6.252s
New with global map:
goos: darwin
goarch: amd64
pkg: github.com/prometheus/prometheus/pkg/labels
cpu: Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz
BenchmarkMatchType_String 283412692 4.129 ns/op 0 B/op 0 allocs/op
BenchmarkMatchType_String 294859941 4.091 ns/op 0 B/op 0 allocs/op
BenchmarkMatchType_String 295750158 4.113 ns/op 0 B/op 0 allocs/op
BenchmarkMatchType_String 282827982 4.072 ns/op 0 B/op 0 allocs/op
BenchmarkMatchType_String 292942393 4.047 ns/op 0 B/op 0 allocs/op
PASS
ok github.com/prometheus/prometheus/pkg/labels 8.238s
Signed-off-by: Oleg Zaytsev <mail@olegzaytsev.com>
* Use array instead of map
Since MatchType is an iota type, we can safely use an array here.
This solution is even better:
name \ time/op old global_map stringer array
MatchType_String 53.6ns ± 1% 4.1ns ± 1% 2.8ns ± 1% 1.0ns ± 1%
name \ alloc/op old global_map stringer array
MatchType_String 0.00B 0.00B 0.00B 0.00B
name \ allocs/op old global_map stringer array
MatchType_String 0.00 0.00 0.00 0.00
Signed-off-by: Oleg Zaytsev <mail@olegzaytsev.com>
* Benchmark all MatchType values
Co-authored-by: Ganesh Vernekar <15064823+codesome@users.noreply.github.com>
Signed-off-by: Oleg Zaytsev <mail@olegzaytsev.com>
* Use constants for limits
Signed-off-by: Oleg Zaytsev <mail@olegzaytsev.com>
Co-authored-by: Ganesh Vernekar <15064823+codesome@users.noreply.github.com>
Co-authored-by: Ganesh Vernekar <15064823+codesome@users.noreply.github.com>
|
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|---|---|---|
| .circleci | ||
| .github | ||
| cmd | ||
| config | ||
| console_libraries | ||
| consoles | ||
| discovery | ||
| docs | ||
| documentation | ||
| notifier | ||
| pkg | ||
| prompb | ||
| promql | ||
| rules | ||
| scrape | ||
| scripts | ||
| storage | ||
| template | ||
| tsdb | ||
| util | ||
| web | ||
| .dockerignore | ||
| .gitignore | ||
| .gitpod.yml | ||
| .golangci.yml | ||
| .promu.yml | ||
| .yamllint | ||
| CHANGELOG.md | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| Dockerfile | ||
| LICENSE | ||
| MAINTAINERS.md | ||
| Makefile | ||
| Makefile.common | ||
| NOTICE | ||
| README.md | ||
| RELEASE.md | ||
| SECURITY.md | ||
| VERSION | ||
| go.mod | ||
| go.sum | ||
README.md
Prometheus
Visit prometheus.io for the full documentation, examples and guides.
Prometheus, a Cloud Native Computing Foundation project, is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts when specified conditions are observed.
The features that distinguish Prometheus from other metrics and monitoring systems are:
- A multi-dimensional data model (time series defined by metric name and set of key/value dimensions)
- PromQL, a powerful and flexible query language to leverage this dimensionality
- No dependency on distributed storage; single server nodes are autonomous
- An HTTP pull model for time series collection
- Pushing time series is supported via an intermediary gateway for batch jobs
- Targets are discovered via service discovery or static configuration
- Multiple modes of graphing and dashboarding support
- Support for hierarchical and horizontal federation
Architecture overview
Install
There are various ways of installing Prometheus.
Precompiled binaries
Precompiled binaries for released versions are available in the download section on prometheus.io. Using the latest production release binary is the recommended way of installing Prometheus. See the Installing chapter in the documentation for all the details.
Docker images
Docker images are available on Quay.io or Docker Hub.
You can launch a Prometheus container for trying it out with
$ docker run --name prometheus -d -p 127.0.0.1:9090:9090 prom/prometheus
Prometheus will now be reachable at http://localhost:9090/.
Building from source
To build Prometheus from source code, first ensure that have a working Go environment with version 1.14 or greater installed. You also need Node.js and npm installed in order to build the frontend assets.
You can directly use the go tool to download and install the prometheus
and promtool binaries into your GOPATH:
$ GO111MODULE=on go get github.com/prometheus/prometheus/cmd/...
$ prometheus --config.file=your_config.yml
However, when using go get to build Prometheus, Prometheus will expect to be able to
read its web assets from local filesystem directories under web/ui/static and
web/ui/templates. In order for these assets to be found, you will have to run Prometheus
from the root of the cloned repository. Note also that these directories do not include the
new experimental React UI unless it has been built explicitly using make assets or make build.
An example of the above configuration file can be found here.
You can also clone the repository yourself and build using make build, which will compile in
the web assets so that Prometheus can be run from anywhere:
$ mkdir -p $GOPATH/src/github.com/prometheus
$ cd $GOPATH/src/github.com/prometheus
$ git clone https://github.com/prometheus/prometheus.git
$ cd prometheus
$ make build
$ ./prometheus --config.file=your_config.yml
The Makefile provides several targets:
- build: build the
prometheusandpromtoolbinaries (includes building and compiling in web assets) - test: run the tests
- test-short: run the short tests
- format: format the source code
- vet: check the source code for common errors
- assets: build the new experimental React UI
Building the Docker image
The make docker target is designed for use in our CI system.
You can build a docker image locally with the following commands:
$ make promu
$ promu crossbuild -p linux/amd64
$ make npm_licenses
$ make common-docker-amd64
NB if you are on a Mac, you will need gnu-tar.
React UI Development
For more information on building, running, and developing on the new React-based UI, see the React app's README.md.
More information
- The source code is periodically indexed: Prometheus Core.
- You will find a CircleCI configuration in
.circleci/config.yml. - See the Community page for how to reach the Prometheus developers and users on various communication channels.
Contributing
Refer to CONTRIBUTING.md
License
Apache License 2.0, see LICENSE.