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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

The Netflix TechBlog

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. We have also noted a great potential for further improvement by model tuning (see the section of Rollout in Production).

Tuning 210
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Bulldozer: Batch Data Moving from Data Warehouse to Online Key-Value Stores

The Netflix TechBlog

Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 243
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QCon London: Lessons Learned From Building LinkedIn’s AI/ML Data Platform

InfoQ

He specifically delved into Venice DB, the NoSQL data store used for feature persistence. The presenter shared the lessons learned from evolving and operating the platform, including cluster management and library versioning. By Rafal Gancarz

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Optimizing data warehouse storage

The Netflix TechBlog

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Storage 203
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Web Performance Bookshelf

Rigor

Take, for example, The Web Almanac , the golden collection of Big Data combined with the collective intelligence from most of the authors listed below, brilliantly spearheaded by Google’s @rick_viscomi. This book presents 14 specific rules that will cut 25% to 50% off response time when users request a page.

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World’s Top Web Performance Leaders To Watch

Rigor

Presented here alphabetically by last name: Rachel Andrew. Vitaly specializes in front-end development, performance optimization, and responsive design, and he has made an epic contribution to the performance industry in addition to many other technology and design-related spaces. Here is our (ever-growing!) Rachel Andrew.

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Microsoft Engineering loves SQLBits

SQL Server According to Bob

When I started to write this post I thought I knew who all was presenting but then I had to go back over the session lineup to see for myself. Best practices on Building a Big Data Analytics Solution – Michael Rys. If you want to learn about Azure Data Lake, there is no one better.