The Netflix TechBlog

MARCH 5, 2019

Central engineering teams enable this operational model by reducing the cognitive burden on innovation teams through solutions related to securing, scaling and strengthening (resilience) the infrastructure. All these micro-services are currently operated in AWS cloud infrastructure.

Infrastructure 182

Infrastructure Cloud Scalability AWS 182

All Things Distributed

NOVEMBER 15, 2016

As I mentioned, we live in a world where massive volumes of data are being generated, every day, from connected devices, websites, mobile apps, and customer applications running on top of AWS infrastructure. Put simply, data is not always readily available and accessible to organizational end users. Enter Amazon QuickSight.

Analytics 152

Analytics Availability Media Social Media 152

All Things Distributed

OCTOBER 7, 2015

In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data. However, the data infrastructure to collect, store and process data is geared toward developers (e.g.,

Cloud 137

Cloud Big Data AWS Analytics 137

Adrian Cockcroft

FEBRUARY 13, 2023

STP213 Scaling global carbon footprint management — Blake Blackwell Persefoni Manager Data Engineering and Michael Floyd AWS Head of Sustainability Solutions. Partner oriented session getting everyone up to speed on what AWS sees as the customer needs, motivations, business outcomes and architectures around sustainability.

AWS 64

AWS Energy Architecture Programming 64

The Netflix TechBlog

MAY 26, 2020

Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the Cloud Network Infrastructure to address the identified problems. As with any sustainable engineering design, focusing on simplicity is very important.

Network 150

Network Tuning AWS Big Data 150

The Netflix TechBlog

DECEMBER 3, 2022

A large number of our data users employ SparkSQL, pyspark, and Scala. A small but growing contingency of data scientists and analytics engineers use R, backed by the Sparklyr interface or other data processing tools, like Metaflow. Centralized Best Practices Data infrastructure evolves continually.

Best Practices 358

Best Practices Code Testing Data Engineering 358