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# Prometheus Client Library for Modern C++
This library aims to enable
[Metrics-Driven Development](https://sookocheff.com/post/mdd/mdd/) for
C++ services. It implements the
[Prometheus Data Model](https://prometheus.io/docs/concepts/data_model/),
a powerful abstraction on which to collect and expose metrics. We
offer the possibility for metrics to be collected by Prometheus, but
other push/pull collections can be added as plugins.
## Usage
See https://jupp0r.github.io/prometheus-cpp for more detailed interface documentation.
``` c++
#include <prometheus/counter.h>
#include <prometheus/exposer.h>
#include <prometheus/registry.h>
#include <array>
#include <chrono>
#include <cstdlib>
#include <memory>
#include <string>
#include <thread>
int main() {
using namespace prometheus;
// create an http server running on port 8080
Exposer exposer{"127.0.0.1:8080"};
// create a metrics registry
// @note it's the users responsibility to keep the object alive
auto registry = std::make_shared<Registry>();
// add a new counter family to the registry (families combine values with the
// same name, but distinct label dimensions)
//
// @note please follow the metric-naming best-practices:
// https://prometheus.io/docs/practices/naming/
auto& packet_counter = BuildCounter()
.Name("observed_packets_total")
.Help("Number of observed packets")
.Register(*registry);
// add and remember dimensional data, incrementing those is very cheap
auto& tcp_rx_counter =
packet_counter.Add({{"protocol", "tcp"}, {"direction", "rx"}});
auto& tcp_tx_counter =
packet_counter.Add({{"protocol", "tcp"}, {"direction", "tx"}});
auto& udp_rx_counter =
packet_counter.Add({{"protocol", "udp"}, {"direction", "rx"}});
auto& udp_tx_counter =
packet_counter.Add({{"protocol", "udp"}, {"direction", "tx"}});
// add a counter whose dimensional data is not known at compile time
// nevertheless dimensional values should only occur in low cardinality:
// https://prometheus.io/docs/practices/naming/#labels
auto& http_requests_counter = BuildCounter()
.Name("http_requests_total")
.Help("Number of HTTP requests")
.Register(*registry);
// ask the exposer to scrape the registry on incoming HTTP requests
exposer.RegisterCollectable(registry);
for (;;) {
std::this_thread::sleep_for(std::chrono::seconds(1));
const auto random_value = std::rand();
if (random_value & 1) tcp_rx_counter.Increment();
if (random_value & 2) tcp_tx_counter.Increment();
if (random_value & 4) udp_rx_counter.Increment();
if (random_value & 8) udp_tx_counter.Increment();
const std::array<std::string, 4> methods = {"GET", "PUT", "POST", "HEAD"};
auto method = methods.at(random_value % methods.size());
// dynamically calling Family<T>.Add() works but is slow and should be
// avoided
http_requests_counter.Add({{"method", method}}).Increment();
}
return 0;
}
```
## Requirements
Using `prometheus-cpp` requires a C++11 compliant compiler. It has been successfully tested with GNU GCC 7.4 on Ubuntu Bionic (18.04) and Visual Studio 2017 (but Visual Studio 2015 should work, too).
## Building
There are two supported ways to build
`prometheus-cpp` - [CMake](https://cmake.org)
and [bazel](https://bazel.io). Both are tested in CI and should work
on master and for all releases.
In case these instructions don't work for you, looking at
the [GitHub Workflows](.github/workflows) might help.
### via CMake
For CMake builds don't forget to fetch the submodules first. Please note that
[zlib](https://zlib.net/) and [libcurl](https://curl.se/) are not provided by
the included submodules. In the example below their usage is disabled.
Then build as usual.
``` shell
# fetch third-party dependencies
git submodule init
git submodule update
mkdir _build
cd _build
# run cmake
cmake .. -DBUILD_SHARED_LIBS=ON -DENABLE_PUSH=OFF -DENABLE_COMPRESSION=OFF
# build
cmake --build . --parallel 4
# run tests
ctest -V
# install the libraries and headers
cmake --install .
```
### via Bazel
Install [bazel](https://www.bazel.io). Bazel makes it easy to add
this repo to your project as a dependency. Just add the following
to your `WORKSPACE`:
```python
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive", "http_file")
http_archive(
name = "com_github_jupp0r_prometheus_cpp",
strip_prefix = "prometheus-cpp-master",
urls = ["https://github.com/jupp0r/prometheus-cpp/archive/master.zip"],
)
load("@com_github_jupp0r_prometheus_cpp//bazel:repositories.bzl", "prometheus_cpp_repositories")
prometheus_cpp_repositories()
```
Then, you can reference this library in your own `BUILD` file, as
demonstrated with the sample server included in this repository:
```python
cc_binary(
name = "sample_server",
srcs = ["sample_server.cc"],
deps = ["@com_github_jupp0r_prometheus_cpp//pull"],
)
```
When you call `prometheus_cpp_repositories()` in your `WORKSPACE` file,
you load the following dependencies, if they do not exist yet, into your project:
* `civetweb` for [Civetweb](https://github.com/civetweb/civetweb)
* `com_google_googletest` for [Google Test](https://github.com/google/googletest)
* `com_github_google_benchmark` for [Google Benchmark](https://github.com/google/benchmark)
* `com_github_curl` for [curl](https://curl.haxx.se/)
* `net_zlib_zlib` for [zlib](http://www.zlib.net/)
The list of dependencies is also available from file [repositories.bzl](bazel/repositories.bzl).
## Packaging
By configuring CPack you can generate an installer like a
Debian package (.deb) or RPM (.rpm) for the static or dynamic
libraries so they can be easily installed on
other systems.
Please refer to the [CPack](https://cmake.org/cmake/help/latest/module/CPack.html)
documentation for all available generators and their
configuration options.
To generate a Debian package you could follow these steps:
``` shell
# fetch third-party dependencies
git submodule update --init
# run cmake
cmake -B_build -DCPACK_GENERATOR=DEB -DBUILD_SHARED_LIBS=ON # or OFF for static libraries
# build and package
cmake --build _build --target package --parallel $(nproc)
```
This will place an appropriately named .deb in the
`_build` folder. To build a RPM package set the `CPACK_GENERATOR`
variable to `RPM`.
## Consuming the installed project
### CMake
Consuming prometheus-cpp via CMake is the preferred way because all the dependencies
between the three prometheus-cpp libraries are handled correctly.
The `cmake/project-import` directory contains an
example project and minimal [CMakeLists.txt](cmake/project-import-cmake/CMakeLists.txt).
### vcpkg
The [vcpkg](https://github.com/microsoft/vcpkg) package manager contains a
prometheus-cpp port which has been tested on Linux, macOS, and Windows.
### Conan
[Conan](https://conan.io/) package manager contains prometheus-cpp package as well
in [ConanCenter](https://conan.io/center/prometheus-cpp) repository
### Plain Makefiles
When manually linking prometheus-cpp the library order matters. The needed
libraries depend on the individual use case but the following should work for the pull metrics approach:
```
-lprometheus-cpp-pull -lprometheus-cpp-core -lz
```
For the push-workflow please try:
```
-lprometheus-cpp-push -lprometheus-cpp-core -lcurl -lz
```
## Contributing
Please adhere to the [Google C++ Style
Guide](https://google.github.io/styleguide/cppguide.html). Make sure
to clang-format your patches before opening a PR. Also make sure to
adhere to [these commit message
guidelines](https://chris.beams.io/posts/git-commit/).
You can check out this repo and build the library using
``` bash
bazel build //... # build everything
bazel build //core //pull # build just the libraries
```
Run the unit tests using
```
bazel test //...
```
There is also an integration test that
uses [telegraf](https://github.com/influxdata/telegraf) to scrape a
sample server. With telegraf installed, it can be run using
```
bazel test //pull/tests/integration:scrape-test
```
## Benchmarks
There's a benchmark suite you can run:
```
bazel run -c opt //core/benchmarks
INFO: Analysed target //core/benchmarks:benchmarks (0 packages loaded, 0 targets configured).
INFO: Found 1 target...
Target //core/benchmarks:benchmarks up-to-date:
bazel-bin/core/benchmarks/benchmarks
INFO: Elapsed time: 0.356s, Critical Path: 0.01s, Remote (0.00% of the time): [queue: 0.00%, setup: 0.00%, process: 0.00%]
INFO: 0 processes.
INFO: Build completed successfully, 1 total action
INFO: Build completed successfully, 1 total action
2018-11-30 15:13:14
Run on (4 X 2200 MHz CPU s)
CPU Caches:
L1 Data 32K (x2)
L1 Instruction 32K (x2)
L2 Unified 262K (x2)
L3 Unified 4194K (x1)
-----------------------------------------------------------------------------------
Benchmark Time CPU Iterations
-----------------------------------------------------------------------------------
BM_Counter_Increment 13 ns 12 ns 55616469
BM_Counter_Collect 7 ns 7 ns 99823170
BM_Gauge_Increment 12 ns 12 ns 51511873
BM_Gauge_Decrement 12 ns 12 ns 56831098
BM_Gauge_SetToCurrentTime 184 ns 183 ns 3928964
BM_Gauge_Collect 6 ns 6 ns 117223478
BM_Histogram_Observe/0 134 ns 124 ns 5665310
BM_Histogram_Observe/1 122 ns 120 ns 5937185
BM_Histogram_Observe/8 137 ns 135 ns 4652863
BM_Histogram_Observe/64 143 ns 143 ns 4835957
BM_Histogram_Observe/512 259 ns 257 ns 2334750
BM_Histogram_Observe/4096 1545 ns 1393 ns 620754
BM_Histogram_Collect/0 103 ns 102 ns 5654829
BM_Histogram_Collect/1 100 ns 100 ns 7015153
BM_Histogram_Collect/8 608 ns 601 ns 1149652
BM_Histogram_Collect/64 1438 ns 1427 ns 515236
BM_Histogram_Collect/512 5178 ns 5159 ns 114619
BM_Histogram_Collect/4096 33527 ns 33280 ns 20785
BM_Registry_CreateFamily 320 ns 316 ns 2021567
BM_Registry_CreateCounter/0 128 ns 128 ns 5487140
BM_Registry_CreateCounter/1 2066 ns 2058 ns 386002
BM_Registry_CreateCounter/8 7672 ns 7634 ns 91328
BM_Registry_CreateCounter/64 63270 ns 62761 ns 10780
BM_Registry_CreateCounter/512 560714 ns 558328 ns 1176
BM_Registry_CreateCounter/4096 18672798 ns 18383000 ns 35
BM_Summary_Observe/0/iterations:262144 9351 ns 9305 ns 262144
BM_Summary_Observe/1/iterations:262144 9242 ns 9169 ns 262144
BM_Summary_Observe/8/iterations:262144 14344 ns 14195 ns 262144
BM_Summary_Observe/64/iterations:262144 19176 ns 18950 ns 262144
BM_Summary_Collect/0/0 31 ns 30 ns 24873766
BM_Summary_Collect/1/0 166 ns 166 ns 4266706
BM_Summary_Collect/8/0 1040 ns 1036 ns 660527
BM_Summary_Collect/64/0 4529 ns 4489 ns 155600
BM_Summary_Collect/0/1 28 ns 28 ns 24866697
BM_Summary_Collect/1/1 190 ns 188 ns 3930354
BM_Summary_Collect/8/1 1372 ns 1355 ns 535779
BM_Summary_Collect/64/1 9901 ns 9822 ns 64632
BM_Summary_Collect/0/8 29 ns 29 ns 24922651
BM_Summary_Collect/1/8 217 ns 215 ns 3278381
BM_Summary_Collect/8/8 2275 ns 2256 ns 282503
BM_Summary_Collect/64/8 56790 ns 55804 ns 13878
BM_Summary_Collect/0/64 32 ns 31 ns 22548350
BM_Summary_Collect/1/64 395 ns 389 ns 1817073
BM_Summary_Collect/8/64 10187 ns 10064 ns 71928
BM_Summary_Collect/64/64 374835 ns 373560 ns 1812
BM_Summary_Collect/0/512 28 ns 28 ns 25234228
BM_Summary_Collect/1/512 1710 ns 1639 ns 802285
BM_Summary_Collect/8/512 50355 ns 49335 ns 15975
BM_Summary_Collect/64/512 2520972 ns 2493417 ns 295
BM_Summary_Collect/0/4096 31 ns 31 ns 24059034
BM_Summary_Collect/1/4096 2719 ns 2698 ns 286186
BM_Summary_Collect/8/4096 121689 ns 119995 ns 5647
BM_Summary_Collect/64/4096 5660131 ns 5587634 ns 134
BM_Summary_Collect/0/32768 29 ns 29 ns 22217567
BM_Summary_Collect/1/32768 4344 ns 4294 ns 138135
BM_Summary_Collect/8/32768 331563 ns 326403 ns 2017
BM_Summary_Collect/64/32768 16363553 ns 16038182 ns 44
BM_Summary_Collect/0/262144 27 ns 27 ns 23923036
BM_Summary_Collect/1/262144 10457 ns 10332 ns 67690
BM_Summary_Collect/8/262144 930434 ns 869234 ns 792
BM_Summary_Collect/64/262144 39217069 ns 39054846 ns 13
BM_Summary_Observe_Common/iterations:262144 5587 ns 5557 ns 262144
BM_Summary_Collect_Common/0 676 ns 673 ns 1054630
BM_Summary_Collect_Common/1 709 ns 705 ns 990659
BM_Summary_Collect_Common/8 1030 ns 1025 ns 685649
BM_Summary_Collect_Common/64 2066 ns 2055 ns 339969
BM_Summary_Collect_Common/512 5754 ns 5248 ns 156895
BM_Summary_Collect_Common/4096 23894 ns 23292 ns 31096
BM_Summary_Collect_Common/32768 49831 ns 49292 ns 13492
BM_Summary_Collect_Common/262144 128723 ns 126987 ns 5579
```
## Project Status
Stable and used in production.
Parts of the library are instrumented by itself
(bytes scraped, number of scrapes, scrape request latencies). There
is a working [example](pull/tests/integration/sample_server.cc) that's
scraped by telegraf as part of integration tests.
## FAQ
### What scrape formats do you support
Only the [Prometheus Text Exposition
Format](https://github.com/prometheus/docs/blob/master/content/docs/instrumenting/exposition_formats.md#text-format-details).
Support for the protobuf format was removed because it's been removed
from Prometheus 2.0.
## License
MIT
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