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Server Profiling

Medplum is designed to be a critical component of system architecture. It is important that Medplum server is robust, performant, and scalable. Hand in hand with Load Testing, profiling the server is critical in understanding performance bottlenecks and scaling challenges.

This document describes how the Medplum team uses the Node.js Profiler to analyze server performance.

Prerequisites​

Make sure you first Clone the repo and Run the stack.

Start the Profiler​

During normal server-side development, developers use npm run dev to run the server in development mode. That

Change directories to packages/server:

cd packages/server

Build the server:

npm run build

Now run the server with the Node.js built-in profiler:

NODE_ENV=production node --prof dist/index.js

If you use a custom config file, you can add that as an optional parameter:

NODE_ENV=production node --prof dist/index.js file:medplum.docker.config.json

The server is now running with the profiler attached. Because we used node directly, the server will not automatically recompile or restart on changes. When the profiler is attached, you must manually rebuild and restart.

Generate Load​

Generating load depends on which aspect of the server that you want to profile.

For general guidance on using Artillery to generate load, see the Medplum guide on Load Testing.

For a quick test of a single HTTP endpoint, we can use Artillery's quick mode:

artillery quick --count 20 --num 100 http://localhost:8103/healthcheck

Sample output:

All VUs finished. Total time: 3 seconds

--------------------------------
Summary report @ 16:54:23(-0700)
--------------------------------

http.codes.200: ................................................ 2000
http.request_rate: ............................................. 1702/sec
http.requests: ................................................. 2000
http.response_time:
  min: ......................................................... 1
  max: ......................................................... 19
  median: ...................................................... 3
  p95: ......................................................... 5
  p99: ......................................................... 6
http.responses: ................................................ 2000
vusers.completed: .............................................. 20
vusers.created: ................................................ 20
vusers.created_by_name.0: ...................................... 20
vusers.failed: ................................................. 0
vusers.session_length:
  min: ......................................................... 237.9
  max: ......................................................... 355.9
  median: ...................................................... 333.7
  p95: ......................................................... 354.3
  p99: ......................................................... 354.3

Analyze Profiler Data​

Switch back to your server, and terminate the process with Ctrl+C.

Since we ran our application using the --prof option, a tick file was generated in the same directory as your local run of the application. It should have the form isolate-0xnnnnnnnnnnnn-v8.log.

In order to make sense of this file, we need to use the tick processor bundled with the Node.js binary. To run the processor, use the --prof-process flag:

node --prof-process isolate-0xnnnnnnnnnnnn-v8.log > processed.txt

Open processed.txt in your favorite text editor. If you have worked with profiler data before, this should look familiar.

See the Node.js Profiling docs for full details on how to process and analyze that file.