Is this you or your team?
- Performance engineering is a lot of work, and very tedious.
- Tools available in the market do not provide informative guidance.
- Without tools, engineering will need to write their own test.
- Performance engineering is very isolated work. It’s difficult to follow people’s traces and I have to work independently.
- APM and observability tools don't show you the root causes
Life without Product Science
- Notify/notice a performance issue
- Write code to run some tests. Spending hours writing logic tests where code cannot go into production.
- Collect a sample of threads/processes instead of traces. No execution paths. Not necessarily a reflection of the user's real-life experience.
- Rely on summary statistics to see what methods call are being called a lot of times. Instead of understanding performance bottlenecks systematically.
- Guessing, guessing, and guessing: am I doing something wrong? Why is this method being called a thousand times?
- Try manually putting all the pieces together to form a performance insights
What is Product Science Tool?
A Product Science Tool (PS Tool) is a set of developer tools for pre-production performance engineering of mobile applications. The first system to combine the following elements into a single tool:
- AI-powered fully automated instrumentation. Pre-trained ML algorithms add meta-data to a pre-production build of your app to map connections between critical processes for fast analysis.
- Code profiler and execution path visualization flame chart use another set of ML algorithms to calculate the critical execution path from any user action to a satisfying app response. Includes direct correlation of app screen recording to code execution with frame-by-frame analysis.
PS Tool in your Development Cycle
- Feature/UI Development. Catch performance issues in your dev builds before it impacts your customer. The code you ship with the PS Tool is 30-70% better optimized.
- Post-release. Use the PS tool to analyze the current performance of the app, and detect bottlenecks and performance opportunities to improve the existing user experience.
