Liz Fong-Jones and Jessica Kerr, honeycomb.io
In this talk, you will learn how a sub-second latency query engine inspired by Facebook's Scuba was extended from running in RAM only, to querying the most recent data that could still fit on local SSD, to querying months of data at a time using cloud storage and serverless functions. We'll describe the pitfalls of managing lambdas at scale, including impatience, maximum concurrency, runtime and architecture configuration/experimentation, and the price/performance of renting 20,000 parallel workers.
Liz Fong-Jones, Honeycomb
Liz is a developer advocate, labor and ethics organizer, and Site Reliability Engineer (SRE) with 16+ years of experience. She is an advocate at Honeycomb for the SRE and Observability communities, and previously was an SRE working on products ranging from the Google Cloud Load Balancer to Google Flights.
Jessica Kerr, Honeycomb
Jess is a symmathecist, in the medium of code. She sees development teams as learning systems made of people and running software. If we make that software teach us what's happening, it's a better teammate. And if this process makes us into systems thinkers, we can be better persons in the world.
SREcon22 Americas Open Access Sponsored by Blameless
author = {Liz Fong-Jones and Jessica Kerr},
title = {Using Serverless Functions for Real-time Observability},
year = {2022},
address = {San Francisco, CA},
publisher = {USENIX Association},
month = mar
}
