Version: 5.0 🚧

Prometheus Exporter

The observability of SRS is about metrics(Prometheus Exporter), tracing(APM) and logging(Cloud Logging).

Introduction

For detail specs, please read OpenTelemetry.

Note: Please see Metrics, tracing, and logging

The architecture for Prometheus exporter:

+-----+               +-----------+     +---------+
| SRS +--Exporter-->--| Promethus +-->--+ Grafana +
+-----+   (HTTP)      +-----------+     +---------+

There is special config for exporter.

Config

The config for exporter is bellow. Highly recommend using environment variables to enable it:

# Prometheus exporter config.
# See https://prometheus.io/docs/instrumenting/exporters
exporter {
    # Whether exporter is enabled.
    # Overwrite by env SRS_EXPORTER_ENABLED
    # Default: off
    enabled off;
    # The http api listen port for exporter metrics.
    # Overwrite by env SRS_EXPORTER_LISTEN
    # Default: 9972
    # See https://github.com/prometheus/prometheus/wiki/Default-port-allocations
    listen 9972;
    # The logging label to category the cluster servers.
    # Overwrite by env SRS_EXPORTER_LABEL
    label cn-beijing;
    # The logging tag to category the cluster servers.
    # Overwrite by env SRS_EXPORTER_TAG
    tag cn-edge;
}

Let's start SRS exporter to export metrics to Prometheus.

Usage for SRS Exporter

Build and start SRS 5.0.86+：

./configure && make
env SRS_ENV_ONLY=on SRS_EXPORTER_ENABLED=on SRS_LISTEN=1935 \
  ./objs/srs -e

Note: We use envrionment variables to config SRS, without config file. However, you're able to use config file conf/prometheus.conf to start the demo.

Note: Please open http://localhost:9972/metrics to verify SRS.

Then, use FFmpeg to push a live stream to SRS:

docker run --rm -it ossrs/srs:encoder ffmpeg -re -i doc/source.flv -c copy \
  -f flv rtmp://host.docker.internal/live/livestream

Next, run node_exporter to collect the node data:

docker run --rm -p 9100:9100 prom/node-exporter

Note: Highly recommend downloading from here and startting by binary file.

Note: Please open http://localhost:9100/metrics to verify it.

Finally, create a prometheus.yml for prometheus:

scrape_configs:
  - job_name: "node"
    metrics_path: "/metrics"
    scrape_interval: 5s
    static_configs:
      - targets: ["host.docker.internal:9100"]
  - job_name: "srs"
    metrics_path: "/metrics"
    scrape_interval: 5s
    static_configs:
      - targets: ["host.docker.internal:9972"]

Note: We set the scrape_interval to 5s, which is default to 1m or one minute.

Start Prometheus by：

docker run --rm -v $(pwd)/prometheus.yml:/etc/prometheus/prometheus.yml \
  -p 9090:9090 prom/prometheus

Please ope Prometheus: Targets, or Prometheus: Graph to query the input bitrate:

rate(srs_receive_bytes_total[10s])*8

This query is used to query the input bitrate, which is the bitrate of stream:

Normally we use Grafana to render the graph.

Usage for Grafana

First, start Grafana in docker:

docker run --rm -it -p 3000:3000 \
  -e GF_SECURITY_ADMIN_USER=admin \
  -e GF_SECURITY_ADMIN_PASSWORD=12345678 \
  -e GF_USERS_DEFAULT_THEME=light \
  grafana/grafana

Please access Grafana console by http://localhost:3000/

Note: Please input username admin and password 12345678 then click login.

Run command to add a Prometheus DataSource:

curl -s -H "Content-Type: application/json" \
    -XPOST http://admin:12345678@localhost:3000/api/datasources \
    -d '{
    "name": "prometheus",
    "type": "prometheus",
    "access": "proxy", "isDefault": true,
    "url": "http://host.docker.internal:9090"
}'

Run command to import the HelloWorld dashboard:

data=$(curl https://raw.githubusercontent.com/ossrs/srs-grafana/main/dashboards/helloworld-import.json 2>/dev/null)
curl -s -H "Content-Type: application/json" \
    -XPOST http://admin:12345678@localhost:3000/api/dashboards/db \
    --data-binary "{\"dashboard\":${data},\"overwrite\":true,\"inputs\":[],\"folderId\":0}"