Web application performance is affected by network latency, bandwidth, database queries, page size and many other factors.
HTTP Load Testing with Vegeta (and a dash of Python) covers getting started with the Vegeta load tester and uses Python to analyze the tool's results.
Four reasons developers should write their own load tests and four load testing mistakes developers love to make are opinionated pieces on how developer should use load testing to ensure their applications work properly under heavy usage.
Idle until urgent explains an issue the author found when measuring First Input Delay (FID) on his site and what techniques he used to fix the problem.
How to measure web app performance is a 20 minute code-first demo that shows how to get a realistic estimate for how many requests per second your web application will be able to handle.
How to Interpret Site Performance Tests covers the difference between client, page and connection speed tests as well as a bit on caching performance.
The [Performance Testing Guidance for Web Applications](https://docs.microsoft.com/en-us/previous-versions/msp-n-p/bb924375(v%3dpandp.10) book from Microsoft is a gem. There are chapters on foundations of performance testing, modeling application usage and many other topics that are critical to working on web app performance.
awesome-scalability provides a list with a crazy number of scaling and performance optimization resources and tools by category.
Every Web Performance Test Tool provides a nice list of tools and provides short summaries of what each one can help with in identifying performance problems.
The Infrastructure Behind Twitter: Scale examines the evolution from having to buy your own hardware from vendors to run a service to the current days of being able to rely on cloud providers for some or all workloads regardless of scale.
Scaling to 100k users covers the architecture scaling techniques commonly used to move up in serving users by orders of magnitude, for example from 100 to 1000.