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Turning RTSP into WebRTC: how many cameras will the server withstand?

Flashphoner corporate blog System administration *Working with video *IT Infrastructure *DevOps *

This article continues the series of articles on load tests. Today we will analyze the testing methodology and answer the question: "How many IP cameras can be connected to a WebRTC server?"

Why connect IP cameras to the server? For example, in order to make a simple video surveillance system that broadcasts what's happening in front of the cameras to the website. Of all the variety of IP cameras, we are interested in those instances that transmit video streams over the RTSP protocol. The fact is that browsers don't know how to play RTSP streams directly, so to add video from an IP camera to your website, you need to turn an RTSP video stream from an IP camera into WebRTC. And if everything is more or less clear from the article, with the software implementation, then at the stage of implementing the solution, the question will definitely appear:

"What kind of server do we need and how many cameras can we connect to it?"

Let's get started.

Testing Plan

  1. Publish VOD stream on the WCS#1 server;

  2. Using a script that uses REST requests, publish RTSP streams on the WCS#2 server;

  3. Choose a random RTSP stream on WCS#2 and visually evaluate the stream;

  4. Estimate the load on the WCS#2 server by the metrics values collected by the Prometheus monitoring system for the WCS#2 server.

Testing is considered successful if we can connect 1,000 IP cameras and no degradation of streams is seen in the monitoring results or visually.

Test bench

For testing, we need

  • two WCS servers;

  • script for the test;

We assume that you already have WCS servers installed and configured. If not, install them according to this instruction, make tweaks to boost performance and connect to monitoring.

We used two servers for testing:

WCS#1 (testing) with characteristics:

  • 24 cores, 48 streams;

  • 128 Gb RAM;

  • WCS 5.2.958;

  • OpenJDK version 14.0.1

and

WCS#2 (tested) with characteristics:

  • 12 cores, 24 streams;

  • 96 Gb RAM;

  • WCS 5.2.958;

  • OpenJDK version 14.0.1

Server Settings

File flashphoner.properties (w/o default settings):

#webrtc ports range
media_port_from = 20001
media_port_to = 40000

#websocket ports
ws.port=8080
wss.port=8443

rtsp_activity_timer_timeout=86400000

wcs_agent_port_from=44001
wcs_agent_port_to=55000

global_bandwidth_check_enabled=true
zgc_log_parser_enable=true
zgc_log_time_format=yyyy-MM-dd'T'HH:mm:ss.SSSZ

rtsp_port_from=55001
rtsp_port_to=65000

Here we increased the range of ports for WebRTC, RTSP and WCS agent. We increased the timeout for RTSP streams without subscribers, and also specified settings for collecting additional metrics for network congestion and pauses in ZGC operation.

For the testing server, we added additional settings for VOD — cyclic stream capture and setting the duration of the VOD stream publication after disconnecting subscribers:

vod_live_loop=true
vod_stream_timeout=14400000

File wcs-core.properties (w/o default settings):

-XX:ErrorFile=/usr/local/FlashphonerWebCallServer/logs/error%p.log

# ZGC
-XX:+UnlockExperimentalVMOptions -XX:+UseZGC -Xms24g -Xmx24g -XX:+UseLargePages -XX:ZPath=/hugepages

-Xlog:gc*:/usr/local/FlashphonerWebCallServer/logs/gc-core-:time

Here we changed the settings for naming log files, enabled the use of ZGC, adjusted the Heap size, and enabled the use of memory pages.

Full versions of the configuration files can be downloaded from the Useful Files section at the bottom of the article. There you will also find a panel for Grafana and a script file to start testing.

Test Script

#! /bin/bash
camera=1000

curl -X POST -H 'Content-type: application/json' --data "{\"uri\":\"vod-live://bunny720p-test.mp4\", \"localStreamName\":\"test\"}" "http://localhost:8081/rest-api/vod/startup" 
sleep 5s

for i in `seq 1 $camera`; do
  curl --data "{\"uri\":\"rtsp://172.16.40.2:554/test?"$i"\",\"toStream\":\"RTSP-test-stream"$i"\"}" -X POST -H 'Content-type: application/json'  -s http://172.16.40.3:8081/rest-api/rtsp/startup
  sleep 0.1s
done

where:

  • camera — number of emulated RTSP streams.

We will use 720p video in our tests. More video parameters are shown in the screenshot below:

Testing

On the testing WCS#1 server, run the script for testing:

./RTSP-load-test.sh

Test result for 1,000 captured RTSP streams:

The test was successful. No stream degradation was recorded by metrics. The CPU load according to the Load average 1 metric did not exceed 100 units.

Open the standard example Player on the tested WCS#2 server and start playing a random RTSP stream from the captured ones:

The control stream is played with acceptable quality — no freezing, artifacts and sound quality degradation.

We ran some more tests

for 1,500 RTSP streams:

and for 2,000 RTSP streams:

The results of these tests show an increase in the CPU load and an increase in pauses in ZGC. Metrics show no stream degradation, but the control stream is played with noticeable artifacts.

As you can see, the tests were not very long. Therefore, you cannot make a decision on choosing a server for a video surveillance system based solely on these tests. Indeed, in the long term, the behavior of the system can change.

Let's run another test with 1,000 captured RTSP streams:

This test lasted nearly two hours. During this time, you can see that there are no critical changes in resource utilization. The control stream was also played correctly all the time:

We remind you that the test results directly depend on the environment, therefore, they may be better or worse when tested on your hardware.

Have a good streaming!

Useful Files

Panel for Grafana:

RTSP-720p-testing.json

WCS Settings:

flashphoner.properties

wcs-core.properties

Test Script:

RTSP-load-test.sh

Links

Demo

WCS on Amazon EC2

WCS on DigitalOcean

WCS in Docker

Settings file flashphoner.properties

Settings file wcs-core.properties

Server tuning recommendations

Memory management in Java

Before moving to production

Quick deployment and testing of the server

Load and resource usage information

Monitoring with Prometheus

REST API

Stream capturing from an IP camera via RTSP

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