November 30, 2019

182 words 1 min read

Practical performance theory

Practical performance theory

Performance theory offers a rigorous and practical approach to performance tuning and capacity planning. Kavya Joshi dives into elegant results like Littles law and the Universal Scalability Law. You'll also discover how performance theory is used in real systems at companies like Facebook and learn how to leverage it to prepare your systems for flux and scale.
Talk Title Practical performance theory
Speakers Kavya Joshi (Samsara)
Conference Velocity
Conf Tag Build resilient systems at scale
Location New York, New York
Date September 20-22, 2016
URL Talk Page
Slides Talk Slides
Video Talk Video

How does your system perform under load? What are the bottlenecks, and how does it fail at its limits? How do you stay ahead as your system evolves and its workload grows? Performance theory offers a rigorous and practical approach to performance tuning and capacity planning. Kavya Joshi dives into elegant results like Little’s law and the Universal Scalability Law. You’ll also discover how performance theory is used in real systems at companies like Facebook and learn how to leverage it to prepare your systems for flux and scale.

performance facebook book
comments powered by Disqus
Petascale genomics

Petascale genomics

November 17, 2019

The advent of next-generation DNA sequencing technologies is revolutionizing life sciences research by routinely generating extremely large datasets. Tom White explains how big data tools developed to handle large-scale Internet data (like Hadoop) help scientists effectively manage this new scale of data and also enable addressing a host of questions that were previously out of reach.
Sightseeing, venues, and friends: Predictive analytics with Spark ML and Cassandra

Sightseeing, venues, and friends: Predictive analytics with Spark ML and Cassandra

November 17, 2019

Which venues have similar visiting patterns? How can we detect when a user is on vacation? Can we predict which venues will be favorited by users by examining their friends' preferences? Natalino Busa explains how these predictive analytics tasks can be accomplished by using Spark SQL, Spark ML, and just a few lines of Scala code.
Open source lessons from the TODO Group

Open source lessons from the TODO Group

November 7, 2019

Members of the TODO Groupan open group of companies who collaborate on practices, tools, and other ways to run successful and effective open source projects and programsdiscuss why they started open source offices in their respective companies (Twitter, Netflix, Box, Google, Microsoft, and SanDisk) and share the lessons they learned along the way.
Storming the castle: Open source challenges in government

Storming the castle: Open source challenges in government

November 5, 2019

Working for the government presents two major hurdles in open source development: getting your hands on open source developed libraries and finding ways to contribute to open source development in the workplace. Kathy Lee and Morgan Senkal discuss these challenges and offer possible solutions.
Building DistributedLog, a high-performance replicated log service

Building DistributedLog, a high-performance replicated log service

October 27, 2019

DistributedLog is a high-performance replicated log service built on top of Apache BookKeeper that is the foundation of publish-subscribe at Twitter, serving traffic from transactional databases to real-time data analytic pipelines. Sijie Guo offers an overview of DistributedLog, detailing the technical decisions and challenges behind its creation and how it is used at Twitter.
Performance anomaly detection at scale (sponsored by Salesforce)

Performance anomaly detection at scale (sponsored by Salesforce)

November 30, 2019

Automated anomaly detection in production using simple data science techniques enables you to more quickly identify an issue and reduce the time it takes to get customers out of an outage. Tuli Nivas shows how to apply simple statistics to change how performance data is viewed and how to easily and effectively identify issues in production.