Distributed systems often face transient errors and localized component degradation and failure. Verifying that the overall system remains healthy in the face of such failures is challenging. At Netflix, we have built a platform for automatically generating and executing chaos experiments, which check how well the production system can handle component failures and slowdowns. This paper describes
We are pleased to announce the open-source launch of Polynote: a new, polyglot notebook with first-class Scala support, Apache Spark integration, multi-language interoperability including Scala, Python, and SQL, as-you-type autocomplete, and more. Polynote provides data scientists and machine learning researchers with a notebook environment that allows them the freedom to seamlessly integrate our
By Ammar Khaku IntroductionIn a microservice architecture such as Netflix’s, propagating datasets from a single source to multiple downstream destinations can be challenging. These datasets can represent anything from service configuration to the results of a batch job, are often needed in-memory to optimize access and must be updated as they change over time. One example displaying the need for d
Way back in 1992, just as the ‘Internet’ was starting to sound interesting, a company in the UK used technology to disrupt television. Rupert Murdoch’s Sky realised that you could buy football rights for far more than anyone had ever thought of paying before, and you could make your money back by selling the games on subscription instead of pay-per-view or advertising, and you would be able to del
By: Di Lin, Girish Lingappa, Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question — “Can I run a check myself to understand what data is behind this metric?” Now, imagine yourself in the role of a software engineer responsible for a micro-service which publishes dat
We’re excited to release FlameScope: a new performance visualization tool for analyzing variance, perturbations, single-threaded execution, application startup, and other time-based issues. It has been created by the Netflix cloud performance engineering team and just released as open source, and we welcome help from others to develop the project further. (If it especially interests you, you might
This is the third blog of the series on Marketing Technology at Netflix. This blog focuses on the marketing tech systems that are responsible for campaign setup and delivery of our paid media campaigns. The first blog focused on solving for creative development and localization at scale. The second blog focused on scaling advertising at Netflix through easier ad assembly and trafficking. Netflix’s
Faisal Siddiqi presented on machine learning infrastructure for recommendations. He outlined Boson and AlgoCommons, two major ML infra components. Boson focuses on offline training for both ad-hoc exploration and production. It provides utilities for data preparation, feature engineering, training, metrics, and visualization. AlgoCommons provides common abstractions and building blocks for ML like
Like many organizations, Lyft continually looks for ways to address critical risks identified in our organization. Last summer, Lyft’s Security Team identified a lack of two-factor authentication on our ssh logins as an area of concern. Today, we’re sharing our experience implementing two-factor for SSH at Lyft, and announcing our open-source client for interacting with Netflix’s BLESS. Background
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