Since Open Zaak emphasizes good performance, we need tooling to measure performance. There is no point in optimizing without knowing what you’re optimizing for. Every optimization should be preceded by a base-line profiling run, which provides the information on where to optimize.
The tooling discussed here is only enabled with the development settings. You should verify the results on the same dev-environment, as this keeps the hardware and configuration consistent.
Profiling plain HTML pages
Plain HTML pages follow the classic pattern of a request that gets rendered into a template response, which is eventually displayed in the browser.
In development mode, Django Debug Toolbar (DjDT) is enabled by default. It provides a side-panel with information on timings, SQL queries and where they originate.
Profiling API endpoints
DjDT is not suitable for API endpoints, because there is no HTML body being rendered, thus the panel cannot be displayed. We use Django Silk instead for endpoint profiling.
Django silk is not enabled by default, and you can only use it with the development
settings. To enable profiling, set the environment variable
PROFILE to a truthy
PROFILE=yes DEBUG=no python src/manage.py runserver
The profile data is available on http://localhost:8000/silk/. You can make the API calls using Postman, and they’ll show up in the Silk dashboard.
Silk provides information on total request time, how many and which SQL queries ran, timings of the queries and what caused the queries to run.
Disable DEBUG mode
You should use
DEBUG=no when profiling, which disables some Django internals that
can degrade performance and thus give skewed results. Most notably, in debug mode,
Django keeps track of the database queries in an array.
Queries are usually the bottleneck
In most web-apps, the database is the bottleneck for performance. Large amounts of
queries, or big/complex queries should catch your attention. Especially repeating
queries are suspicious - often they can be mitigated using
Measure relative performance
Expressing performance gains in percentage is usually the most useful. Of course, endpoints taking 5 or 10 seconds in total are both bad, so use common sense when interpreting the results. However, it’s interesting if you can attribute a 20% total request time reduction and 90% less queries to a single change.
If you have profiling numbers in production, you can apply the relative gains in performance to the production numbers to get a ballkpark figure of the production performance.