Starting a Dedicated Web Performance Team

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The cover of sarah's talk

My notes on the "Starting a Dedicated Web Performance Team" tech talk by Sarah Dapul-Weberman

First Dedicated Performance Team

  • Migration to react
    • better performance gains: 20% improvement in performance and 10-20% engagement increase
    • 30% improvement in performance in unauth pages
    • 15% increase in signups
    • 10% increase in SEO traffic
    • 5-7% increase in logins
  • They started to think about performance, because people were excited about the performance gains
  • Engineers didn't know if the performance metrics were accurate. No documentation of improvements. No ownership of performance problems.
  • They started with a client-focused performance team because it was the biggest bottleneck

Data Confidence

  • They had an internal metric: Pinner Wait Time (PWT)
    • image and the meta data are the most important things in the surface that users engage with
    • it's a composite metric of how long it takes for each of these to load
  • They noticed that there was no correlation between this performance metric and business and engagement metrics. So they changed to a different metric: they changed it to TTI.
  • They wanted to show to the rest of the company that, when a metric changed, it would affect engagement, and it was extremly important to get buy-in from other people
  • Fighting doubt
    1. Set Baselines: validate performance metrics, confidence tests implemented, graphs reflect real user experience
    2. Tie performance metrics to business goals: performance tied to engagement wins and better trust in performance
    3. Run PR Campaign: teams know about the performance team and come to them for help
    4. Fight Regressions: regression prevention could actually be more impactful than shipping optimizations. Better trust in performance, people more willing to do optimizations, and more regressions caught


  • Make regression testing painless: they called it Perf Watch
    • Commits that are regressing performance in Pinterest
      • They do in a batch of commits
    • Run tests for each critical page: run several times to reduce bias
    • Calculate the 90th percentile of Pinner Wait Time
    • Detecting a regression: they are imediately alerted
      • Engineers can fix it
      • Or revert the PR
  • Perf Detective
    • They do in a batch of commits
    • Binary search in the batch of commits to find the commit that caused the regression

Optimization Strategy

  • Analysis and braimstorming: a lot of projects that they could work on
  • Line of sight: only three people so they needed to prioritize
    • log each project in a doc
    • see the impact
    • see the effort
    • and choose projects
  • Prototyping
    • testing to see the possible impact and effort that each project would take
  • Expertimenting
    • A/B experiments


  • A team that works on optimizations? A team that focuses on tools?
  • Five pillars
    • Scalability: not the only people working on optimizations. They wanted to any product team be able to work on performance optimizations
    • Ownership: want the teams to own their own surfaces, they wanted product teams to find performance as one of the key metrics they want to monitor
    • Knowledge: share performance knowledge with the rest of the teams
    • Tools: create the tools that developers can use for Pinterest -specific performance and make sure that they understand how to improve performance at Pinterest, and they can do it quickly and without issue
    • Strategy: continue to be the strategy performance team for Pinterest. How the tooking works, figure out what critical surgace areas they might need to improve in the future

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