You work in a large codebase and (surprise!) it has performance issues. Realistically, you can’t halt feature development to overhaul your core infrastructure. You also can’t expect a single person to tackle the growing heap of tech debt while everyone else plows ahead. So what can you do? Embrace premature optimizations! As it turns out, they might not be as premature as everyone thinks. Here are a few tricks to thinking like a performance engineer and some tips on convincing even the most stubborn of naysayers that a little forward thinking is the answer to their problems.


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Lawrence Shea at 15:11 on 15 Nov 2017

great talk!

Philip Sharp at 15:51 on 15 Nov 2017

Very interesting talk about real-world scaling issues. Energetic presentation, if a little fast.

The slides were hard to see. Use Guy Kawasaki's standard 10/20/30, (30 point font), the color was also hard, I think you had black titles on blue background. Really interesting content.

Great talk and insights, especially with real-world examples, but wish she had more time to slow down

Joanne Garlow at 14:00 on 16 Nov 2017

Good examples from your own work.

Jill Femister at 14:25 on 16 Nov 2017

Good presentation. Helpful to learn of the problems that came up, how they were detected, and how they were solved. I did have a problem at times with Maude's voice dropping at the end of some sentences which caused me to miss what she was saying.

Ryan Howe at 16:39 on 16 Nov 2017

Great presentation, a lot of good points made and reinforced

david abraham at 01:09 on 18 Nov 2017

really enjoyed the talk, was interesting seeing issues involved with such large user base

Good experiences and advices learned from implementation.

Loved the real world examples, as well as the underlying message of "YAGNI right now, but you'd be best not to build yourself into a corner in case you do need it later."