135 lines
4.1 KiB
Markdown
135 lines
4.1 KiB
Markdown
---
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title: Metrics with Prometheus
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---
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#### 0. Introduction
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This tutorial explains how to export open5gs metrics to Prometheus, which can in
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turn be used to visualize or export them to other systems such as Grafana or
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StatsD.
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When this method is used, any open5gs program exporting metrics becomes a
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Prometheus server, which is basically an HTTP server serving Prometheus data to
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the Prometheus scrapper.
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Note: Only open5gs-smfd supports exporting metrics so far, though other may
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hopefully follow soon.
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#### 1. Enable Prometheus support during build
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Open5GS programs use a generic internal API available in libogsmetrics. This
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library implements the API based on configuration passed during open5gs build
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time. By default, the library will be built using the `void` implementation,
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which is basically a NO-OP implementation.
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In order to use the Prometheus, the `prometheus` metrics implementation needs to
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be selected at build time:
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```
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meson configure -Dmetrics_impl=prometheus build
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```
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This will enable building the implementation under lib/metrics/prometheus/,
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which uses:
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* prometheus-client-c project (libprom): To generate the Prometheus expected
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output format of the metrics
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* libmicrohttpd: To server the content generated by libprom as an HTTP server
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The `prometheus-client-c` project is not currently well maintained, and uses a
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weird mixture of build systems, which makes it difficult to make it available in
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most Linux distributions. As a result, a fork of the project is available under
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Open5GS GitHub namespace, with an extra patch applied making it possible to
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include it as a subproject, which will be fetched and built automatically when
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building the prometheus libmetrics implementation.
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#### 2. Configuring for runtime
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By default the created Prometheus HTTP server will be listening on `0.0.0.0`
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port `9090`.
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This can be configured under the following config file options:
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```
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#
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# metrics:
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#
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# <Metrics Server>
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#
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# o Metrics Server(http://<any address>:9090)
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# metrics:
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# addr: 0.0.0.0
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# port: 9090
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#
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metrics:
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addr: 0.0.0.0
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port: 9090
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```
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Note: You may want to change the default IP address or port if you are running
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the Prometheus scrapper in the same host, since it will also spawn its own
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Prometheus server also in port 9090, which will collide.
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#### 3. Manual visualization
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Simply open the web browser at the following URL (changing IP address and port
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as configured in previous section):
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```
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http://127.0.0.1:9090/metrics
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```
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Note: URL `metrics/` (with a slash at the end) will not work.
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You should see some output similar to this one below:
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```
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# HELP ues_active Active User Equipments
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# TYPE ues_active gauge
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ues_active 2
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# HELP process_max_fds Maximum number of open file descriptors.
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# TYPE process_max_fds gauge
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process_max_fds 1024
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# HELP process_virtual_memory_max_bytes Maximum amount of virtual memory available in bytes.
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# TYPE process_virtual_memory_max_bytes gauge
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process_virtual_memory_max_bytes -1
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# HELP process_cpu_seconds_total Total user and system CPU time spent in seconds.
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# TYPE process_cpu_seconds_total gauge
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process_cpu_seconds_total 0
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# HELP process_virtual_memory_bytes Virtual memory size in bytes.
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# TYPE process_virtual_memory_bytes gauge
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process_virtual_memory_bytes 3156643840
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# HELP process_start_time_seconds Start time of the process since unix epoch in seconds.
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# TYPE process_start_time_seconds gauge
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process_start_time_seconds 402433
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# HELP process_open_fds Number of open file descriptors.
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# TYPE process_open_fds gauge
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process_open_fds 23
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```
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#### 3. Integration with Prometheus scrapper
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Sample Prometheus scrapper configuration (`~/prometheus.yml`):
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```
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global:
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scrape_interval: 10s
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scrape_configs:
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- job_name: open5gs-smfd
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static_configs:
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- targets: ["192.168.1.140:9091"]
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```
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Where `192.168.1.140:9091` is the IP address and port where `open5gs-smfd` is
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serving its metrics, as configured in above sections.
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The Prometheus scrapper can be easily started from a docker container:
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```
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docker run -p 9090:9090 -v /prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus
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```
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Then open your browser to be able to visualize the data: `http://localhost:9090/graph`
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