This library aims to enable Metrics-Driven Development for C++ services. It implements the Prometheus 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.
#include <chrono>
#include <map>
#include <memory>
#include <string>
#include <thread>
#include <prometheus/exposer.h>
#include <prometheus/registry.h>
int main(int argc, char** argv) {
using namespace prometheus;
// create an http server running on port 8080
Exposer exposer{"127.0.0.1:8080"};
// create a metrics registry with component=main labels applied to all its
// metrics
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)
auto& counter_family = BuildCounter()
.Name("time_running_seconds_total")
.Help("How many seconds is this server running?")
.Labels({{"label", "value"}})
.Register(*registry);
// add a counter to the metric family
auto& second_counter = counter_family.Add(
{{"another_label", "value"}, {"yet_another_label", "value"}});
// ask the exposer to scrape the registry on incoming scrapes
exposer.RegisterCollectable(registry);
for (;;) {
std::this_thread::sleep_for(std::chrono::seconds(1));
// increment the counter by one (second)
second_counter.Increment();
}
return 0;
}Using prometheus-cpp requires a C++11 compliant compiler. It has been successfully tested with GNU GCC 4.8 on Ubuntu Trusty and Visual Studio 2017 (but Visual Studio 2015 should work, too).
There are two supported ways to build
prometheus-cpp - CMake
and bazel. 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 travis build script might help.
For CMake builds don't forget to fetch the submodules first. Then build as usual.
# fetch third-party dependencies
git submodule init
git submodule update
mkdir _build
cd _build
# run cmake
cmake ..
# build
make -j 4
# run tests
ctest -V
# install the libraries and headers
mkdir -p deploy
make DESTDIR=`pwd`/deploy installInstall bazel. Bazel makes it easy to add
this repo to your project as a dependency. Just add the following
to your WORKSPACE:
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//: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:
cc_binary(
name = "sample_server",
srcs = ["sample_server.cc"],
deps = ["@com_github_jupp0r_prometheus_cpp//:prometheus_cpp"],
)When you call prometheus_cpp_repositories() in your WORKSPACE file,
you introduce the following dependencies, if they do not exist yet, to your project:
load_civetweb()to loadcivetwebrules for Civetwebload_com_google_googletest()to loadcom_google_googletestrules for Google gtestload_com_google_googlebenchmark()to loadcom_github_google_benchmarkrules for Googlebenchmarkload_com_github_curl()to loadcom_github_curlrules for curlload_net_zlib_zlib()to loadnet_zlib_zlibrules for zlib
The list of dependencies is also available from file repositories.bzl.
Please adhere to the Google C++ Style Guide. Make sure to clang-format your patches before opening a PR. Also make sure to adhere to these commit message guidelines.
You can check out this repo and build the library using
bazel build //... # build everything
bazel build //core //pull # build just the librariesRun the unit tests using
bazel test //...
There is also an integration test that uses telegraf to scrape a sample server. With telegraf installed, it can be run using
bazel test //pull/tests/integration:scrape-test
There's a benchmark suite you can run:
bazel run -c opt //core/tests/benchmark
INFO: Found 1 target...
Target //core/tests/benchmark:benchmark up-to-date:
bazel-bin/core/tests/benchmark/benchmark
INFO: Elapsed time: 1.682s, Critical Path: 1.56s
INFO: Running command line: bazel-bin/core/tests/benchmark/benchmark
Run on (8 X 2300 MHz CPU s)
2016-10-17 15:56:49
Benchmark Time CPU Iterations
--------------------------------------------------------------------
BM_Counter_Increment 11 ns 11 ns 62947942
BM_Counter_Collect 84 ns 84 ns 8221752
BM_Gauge_Increment 11 ns 11 ns 61384663
BM_Gauge_Decrement 11 ns 11 ns 62148197
BM_Gauge_SetToCurrentTime 199 ns 198 ns 3589670
BM_Gauge_Collect 86 ns 85 ns 7469136
BM_Histogram_Observe/0 122 ns 122 ns 5839855
BM_Histogram_Observe/1 116 ns 115 ns 5806623
BM_Histogram_Observe/8 126 ns 126 ns 5781588
BM_Histogram_Observe/64 138 ns 138 ns 4895550
BM_Histogram_Observe/512 228 ns 228 ns 2992898
BM_Histogram_Observe/4k 959 ns 958 ns 642231
BM_Histogram_Collect/0 328 ns 327 ns 2002792
BM_Histogram_Collect/1 356 ns 354 ns 1819032
BM_Histogram_Collect/8 1553 ns 1544 ns 454921
BM_Histogram_Collect/64 10389 ns 10287 ns 66759
BM_Histogram_Collect/512 75795 ns 75093 ns 9075
BM_Histogram_Collect/4k 615853 ns 610277 ns 1222
BM_Registry_CreateFamily 195 ns 182 ns 3843894
BM_Registry_CreateCounter/0 319 ns 317 ns 1914132
BM_Registry_CreateCounter/1 2146 ns 2131 ns 408432
BM_Registry_CreateCounter/8 8936 ns 8837 ns 82439
BM_Registry_CreateCounter/64 72589 ns 72010 ns 9248
BM_Registry_CreateCounter/512 694323 ns 686655 ns 1056
BM_Registry_CreateCounter/4k 18246638 ns 18150525 ns 40
Beta, getting ready for 1.0. The library is pretty stable and used in production. There are some small breaking API changes that might happen before 1.0 Parts of the library are instrumented by itself (bytes scraped, number of scrapes, scrape request latencies). There is a working example that's scraped by telegraf as part of integration tests.
Only the Prometheus Text Exposition Format. Support for the protobuf format was removed because it's been removed from Prometheus 2.0.
MIT