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Performance Engineering: Profiling and Making Apps Fast by Default

September 4, 2026 · 1 h 17 min

Show notes

How do you plan for the performance of your Python applications? What does a performance budget entail, and where should you spend your resources? This week on the show, we speak with Den Odell about his new book “Fast by Default: Practical Performance Engineering.”

Den has 25 years of experience in building web systems for companies with hundreds of millions of users. Working on public-facing tools has honed his skills in understanding where performance is vital and in guiding decisions based on data from actual users.

Den shares details of his performance framework that works across any platform or stack. We discuss the need for budgeting performance during the planning phase, measuring performance through consistent profiling, and keeping systems fast even as your codebase and user base grow.

Course Spotlight: Profiling Performance in Python

Learn to profile Python programs with built-in and popular third-party tools, and turn performance insights into faster code.

Topics:

  • 00:00:00 – Introduction
  • 00:01:39 – Modern systems run across multiple languages
  • 00:03:52 – What lead you toward performance engineering?
  • 00:12:54 – Frameworks and balancing performance against developer experience
  • 00:17:45 – Measuring performance and profiling
  • 00:24:28 – What is Fast by Default?
  • 00:36:34 – Video Course Spotlight
  • 00:38:16 – Breaking into the methodology
  • 00:42:10 – Performance budget
  • 00:48:27 – End user pain points
  • 00:51:21 – Microservices and monoliths
  • 00:54:01 – Performance questionnaire
  • 01:00:31 – What is easier about performance planning upfront?
  • 01:01:50 – Discoveries during the writing process
  • 01:07:01 – Do LLMs write performant code?
  • 01:12:37 – What are you excited about in the world of Python?
  • 01:13:41 – What do you want to learn next?
  • 01:15:02 – How can people follow your work online?
  • 01:15:43 – Thanks and goodbye

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