93b70ee4ea
Keeping these around has two problems: 1) Each desc takes 64 bytes, 10 of them is 640B. This is a lot of overhead on a 1024 byte chunk. 2) It can take well over a week to reach a point where this and thus Prometheus memory usage as a whole enters steady state. This makes RAM estimation very hard for users, and makes it difficult to investigate things like memory fragmentation. Instead we'll wipe them during each memory series maintenance cycle, and if a query pulls them in they'll hang around as cache until the next cycle. |
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|---|---|---|
| .github | ||
| cmd | ||
| config | ||
| console_libraries | ||
| consoles | ||
| discovery | ||
| documentation | ||
| notifier | ||
| promql | ||
| relabel | ||
| retrieval | ||
| rules | ||
| scripts | ||
| storage | ||
| template | ||
| util | ||
| vendor | ||
| web | ||
| .dockerignore | ||
| .gitignore | ||
| .promu.yml | ||
| .travis.yml | ||
| AUTHORS.md | ||
| CHANGELOG.md | ||
| circle.yml | ||
| code-of-conduct.md | ||
| CONTRIBUTING.md | ||
| Dockerfile | ||
| LICENSE | ||
| Makefile | ||
| NOTICE | ||
| README.md | ||
| VERSION | ||
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 if some condition is observed to be true.
Prometheus' main distinguishing features as compared to other monitoring systems are:
- a multi-dimensional data model (timeseries defined by metric name and set of key/value dimensions)
- a flexible query language to leverage this dimensionality
- no dependency on distributed storage; single server nodes are autonomous
- timeseries collection happens via a pull model over HTTP
- pushing timeseries is supported via an intermediary gateway
- 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.
Debian packages are available.
Docker images
Docker images are available on Quay.io.
Building from source
To build Prometheus from the source code yourself you need to have a working Go environment with version 1.5 or greater installed.
You can directly use the go tool to download and install the prometheus
and promtool binaries into your GOPATH. We use Go 1.5's experimental
vendoring feature, so you will also need to set the GO15VENDOREXPERIMENT=1
environment variable in this case:
$ GO15VENDOREXPERIMENT=1 go get github.com/prometheus/prometheus/cmd/...
$ prometheus -config.file=your_config.yml
You can also clone the repository yourself and build using make:
$ 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 - test: run the tests
- format: format the source code
- vet: check the source code for common errors
- assets: rebuild the static assets
- docker: build a docker container for the current
HEAD
More information
- The source code is periodically indexed: Prometheus Core.
- You will find a Travis CI configuration in
.travis.yml. - All of the core developers are accessible via the Prometheus Developers Mailinglist and the
#prometheuschannel onirc.freenode.net.
Contributing
Refer to CONTRIBUTING.md
License
Apache License 2.0, see LICENSE.