The Netflix TechBlog

DECEMBER 14, 2023

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community! In this video, Sr.

Data Engineering 259

Data Engineering Engineering Software Engineering Best Practices 259

The Netflix TechBlog

MARCH 7, 2024

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

Systems 226

Systems Media Cache Open Source 226

The Netflix TechBlog

JANUARY 11, 2022

To learn about Analytics and Viz Engineering, have a look at Analytics at Netflix: Who We Are and What We Do by Molly Jackman & Meghana Reddy and How Our Paths Brought Us to Data and Netflix by Julie Beckley & Chris Pham. Curious to learn about what it’s like to be a Data Engineer at Netflix?

Innovation 243

Innovation Metrics Engineering Testing 243

All Things Distributed

NOVEMBER 15, 2016

They require companies to provision and maintain complex hardware infrastructure and invest in expensive software licenses, maintenance fees, and support fees that cost upwards of thousands of dollars per user per year.

Analytics 152

Analytics Availability Media Social Media 152

O'Reilly

SEPTEMBER 15, 2021

The results are biased by the survey’s recipients (subscribers to O’Reilly’s Data & AI Newsletter ). Our audience is particularly strong in the software (20% of respondents), computer hardware (4%), and computer security (2%) industries—over 25% of the total. Average salary by data framework or platform. The Last Word.

Azure 145

Azure Social Media Programming AWS 145

O'Reilly

JULY 15, 2020

Success with microservices means owning the software lifecycle. Most (74%) respondents say their teams own the build-test-deploy-maintain phases of the software lifecycle. Software engineers comprise the survey audience’s single largest cluster, over one quarter (27%) of respondents (Figure 1). Success with containers.

Database 134

Database Architecture Education Systems 134

Abhishek Tiwari

JULY 12, 2018

Lastly, we will talk about the internal platform and product divide – one key reason why data pipeline initiatives typically fail – and why it is better working backward from the product. Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. A data pipeline is a software which runs on hardware.

Latency 63

Latency Analytics Scalability Engineering 63