Yuta Miyama wants to give this talk

Gradual improvement of your Data Pipeline

When you build a data intensive application, it is critical to avoid resource contention at various layer. However, does everything designed/adapted by big companies like LinkedIn, Google, Facebook suit your needs?

I’m a self-taught software engineer, now leading a technical side of data-intensive software dealing with “mid-sized data volume”. Based on the approaches we’ve taken over the past few years, I see a lot of more conventional toolkit to avoid resource contention that you can start using today.

The list of mitigations are also full of anecdotes, with real incidents behind it. So the audience will learn that depending on the type of contention you experience, there are different types of mitigations you should consider implementing.

The audience who’s familiar with Ruby, Redis, Postgres stack will get the most out of it, but is not limited to them, since the type of mitigations are generic, and can be said to other tech stacks as well. I’m personally fascinated about the contention, as it can take down the whole pipeline if badly designed, and building low latency, high throughput system is really a challenging problem to solve :)

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