d284ffab03
The fpIter was kind of cumbersome to use and required a lock for each iteration (which wasn't even needed for the iteration at startup after loading the checkpoint). The new implementation here has an obvious penalty in memory, but it's only 8 byte per series, so 80MiB for a beefy server with 10M memory time series (which would probably need ~100GiB RAM, so the memory penalty is only 0.1% of the total memory need). The big advantage is that now series maintenance happens in order, which leads to the time between two maintenances of the same series being less random. Ideally, after each maintenance, the next maintenance would tackle the series with the largest number of non-persisted chunks. That would be quite an effort to find out or track, but with the approach here, the next maintenance will tackle the series whose previous maintenance is longest ago, which is a good approximation. While this commit won't change the _average_ number of chunks persisted per maintenance, it will reduce the mean time a given chunk has to wait for its persistence and thus reduce the steady-state number of chunks waiting for persistence. Also, the map iteration in Go is non-deterministic but not truly random. In practice, the iteration appears to be somewhat "bucketed". You can often observe a bunch of series with similar duration since their last maintenance, i.e. you see batches of series with similar number of chunks persisted per maintenance. If that batch is relatively young, a whole lot of series are maintained with very few chunks to persist. (See screenshot in PR for a better explanation.) |
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|---|---|---|
| .github | ||
| cmd | ||
| config | ||
| console_libraries | ||
| consoles | ||
| discovery | ||
| documentation | ||
| notifier | ||
| promql | ||
| relabel | ||
| retrieval | ||
| rules | ||
| scripts | ||
| storage | ||
| template | ||
| util | ||
| vendor | ||
| web | ||
| .codeclimate.yml | ||
| .dockerignore | ||
| .gitignore | ||
| .promu.yml | ||
| .travis.yml | ||
| CHANGELOG.md | ||
| circle.yml | ||
| code-of-conduct.md | ||
| CONTRIBUTING.md | ||
| Dockerfile | ||
| LICENSE | ||
| MAINTAINERS.md | ||
| 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.
You can launch a Prometheus container for trying it out with
$ docker run --name prometheus -d -p 127.0.0.1:9090:9090 quay.io/prometheus/prometheus
Prometheus will now be reachable at http://localhost:9090/.
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. - 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.