All Things Distributed

NOVEMBER 13, 2018

Currently we have 57 Availability Zones across 19 technology infrastructure Regions. We needed to serve our growing base of startup, government, and enterprise customers across many vertical industries, including automotive, financial services, media and entertainment, high technology, education, and energy. million unique visits.

AWS 167

AWS Energy Automotive Traffic 167

Percona

NOVEMBER 9, 2023

It simplifies infrastructure management and is the driving force behind many cloud-native applications and services. Applications can be horizontally scaled with Kubernetes by adding or deleting containers based on resource allocation and incoming traffic demands.

Efficiency 102

Efficiency Cloud Healthcare Open Source 102

The Netflix TechBlog

NOVEMBER 12, 2019

One way to do this is by running A/B tests. Netflix typically A/B tests all changes before rolling them out to all members. A drawback to this approach is that tests take time to run and require experimental models be ready to run in production. Some examples of stratification types are: Country?

Metrics 124

Metrics Government Systems Testing 124

The Netflix TechBlog

NOVEMBER 12, 2019

One way to do this is by running A/B tests. Netflix typically A/B tests all changes before rolling them out to all members. A drawback to this approach is that tests take time to run and require experimental models be ready to run in production. Some examples of stratification types are: Country?

Metrics 100

Metrics Government Systems Testing 100

The Netflix TechBlog

NOVEMBER 12, 2019

One way to do this is by running A/B tests. Netflix typically A/B tests all changes before rolling them out to all members. A drawback to this approach is that tests take time to run and require experimental models be ready to run in production. Some examples of stratification types are: Country?

Metrics 100

Metrics Government Systems Testing 100

The Netflix TechBlog

JANUARY 11, 2022

Here we describe the role of Experimentation and A/B testing within the larger Data Science and Engineering organization at Netflix, including how our platform investments support running tests at scale while enabling innovation. What more can we learn from this test, to inform the next one?”

Innovation 243

Innovation Metrics Engineering Testing 243

The Netflix TechBlog

JANUARY 25, 2022

Earlier posts covered the basics of A/B tests ( Part 1 and Part 2 ), core statistical concepts ( Part 3 and Part 4 ), how to build confidence in a decision ( Part 5 ), and the the role of Experimentation and A/B testing within the larger Data Science and Engineering organization at Netflix ( Part 6 ).

Education 238

Education Innovation Testing Programming 238