The Netflix TechBlog

MARCH 4, 2024

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. After a fixed number of iterations is exhausted, the optimizer returns the “best” configuration solution (i.e.,

Tuning 214

Tuning Efficiency Big Data Engineering 214

The Netflix TechBlog

DECEMBER 21, 2020

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 209

Storage Latency Efficiency Data Engineering 209

Uber Engineering

AUGUST 14, 2019

Once identified, … The post Less is More: Engineering Data Warehouse Efficiency with Minimalist Design appeared first on Uber Engineering Blog. In our experience, optimizing for operational efficiency requires answering one key question: for which tables does the maintenance cost supersede utility?

Efficiency 96

Efficiency Engineering Design Storage 96

The Netflix TechBlog

MARCH 2, 2021

At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group.

Analytics 213

Analytics C++ Innovation Engineering 213

High Scalability

APRIL 14, 2020

has hours of system design content. They also do live system design discussions every week. Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! Who's Hiring? InterviewCamp.io Try out their platform. Need excellent people?

Education 105

Education Software Engineering Scalability Engineering 105

High Scalability

MAY 12, 2020

has hours of system design content. They also do live system design discussions every week. Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! Who's Hiring? InterviewCamp.io Try out their platform. Need excellent people?

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

APRIL 28, 2020

has hours of system design content. They also do live system design discussions every week. Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! Who's Hiring? InterviewCamp.io Try out their platform. Need excellent people?

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MAY 26, 2020

has hours of system design content. They also do live system design discussions every week. Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! Created by former senior-level AWS engineers of 15 years. Who's Hiring?

Education 100

Education AWS Software Engineering Scalability 100

High Scalability

MARCH 30, 2020

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Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MARCH 24, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! Level up on in-demand technologies and prep for your interviews on Educative.io, featuring popular courses like the bestselling Grokking the System Design Interview. Who's Hiring?

Education 105

Education Software Engineering Engineering Big Data 105

The Netflix TechBlog

OCTOBER 18, 2022

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 208

Java Scalability Traffic Architecture 208

The Netflix TechBlog

MAY 26, 2020

As with any sustainable engineering design, focusing on simplicity is very important. These characteristics allow for an on-call response time that is relaxed and more in line with traditional big data analytical pipelines. And excellent logging is needed for debugging purposes and supportability.

Network 152

Network Tuning AWS Traffic 152

Abhishek Tiwari

JULY 7, 2023

In the era of big data and complex data processing, data pipelines have emerged as a popular solution for managing and manipulating data. They provide a systematic approach to extract, transform, and load (ETL) data from various sources, enabling organizations to derive valuable insights.

Logistics 52

Logistics Transportation Scalability Data Engineering 52

Abhishek Tiwari

DECEMBER 27, 2017

In 2018, we will see new data integration patterns those rely either on a shared high-performance distributed storage interface ( Alluxio ) or a common data format ( Apache Arrow ) sitting between compute and storage. Based on data access pattern i.e. hot, warm and cold Alluxio makes. Machine learning meets data integration.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

InfoQ

APRIL 15, 2024

He specifically delved into Venice DB, the NoSQL data store used for feature persistence. At the QCon London 2024 conference, Félix GV from LinkedIn discussed the AI/ML platform powering the company’s products. By Rafal Gancarz

Artificial Intelligence 109

Artificial Intelligence Big Data Data Engineering Latency 109

InfoQ

JULY 3, 2023

LinkedIn introduced Couchbase as a centralized caching tier for scaling member profile reads to handle increasing traffic that has outgrown their existing database cluster. The new solution achieved over 99% hit rate, helped reduce tail latencies by more than 60% and costs by 10% annually. By Rafal Gancarz

Cache 85

Cache Latency Traffic Database 85

The Netflix TechBlog

SEPTEMBER 10, 2019

Instead of relying on engineers to productionize scientific contributions, we’ve made a strategic bet to build an architecture that enables data scientists to easily contribute. The two main challenges with this approach are establishing an easy contribution framework and handling Netflix’s scale of data.

Metrics 219

Metrics Architecture Infrastructure Innovation 219

All Things Distributed

NOVEMBER 15, 2016

They require teams of data engineers to spend months building complex data models and synthesizing the data before they can generate their first report. Finally, their complex user experiences are designed for power users and not suitable for the fast-growing segment of business users. Enter Amazon QuickSight.

Analytics 141

Analytics Availability Media Social Media 141