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 207

Analytics C++ Innovation Engineering 207

The Netflix TechBlog

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

Processing 210

Processing Big Data Efficiency Engineering 210

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! Learn to balance architecture trade-offs and design scalable enterprise-level software.

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! Learn to balance architecture trade-offs and design scalable enterprise-level software.

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! Learn to balance architecture trade-offs and design scalable enterprise-level software.

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

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! The result is a process that doesn't get you the best employees you could.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MARCH 24, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MARCH 17, 2020

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. Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Try the 30-day free trial!

Education 105

Education Engineering Java Software Engineering 105

High Scalability

MARCH 3, 2020

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. Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Try the 30-day free trial!

Education 114

Education Games Engineering Java 114

High Scalability

FEBRUARY 18, 2020

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. Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Try the 30-day free trial!

Education 113

Education Games Engineering Java 113

High Scalability

FEBRUARY 9, 2020

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. Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Try the 30-day free trial!

Education 108

Education Games Engineering Java 108

The Netflix TechBlog

MARCH 4, 2024

In this way, no human intervention is required in the remediation process. We used feature hashing to process the non-numeric values because they come from a high cardinality and dynamic set of values. Multi-objective optimizations. Auto Remediation generates recommendations by considering both performance (i.e., user name).

Tuning 210

Tuning Efficiency Big Data Engineering 210

The Netflix TechBlog

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 202 A day in the life of a Netflix Engineer Dave Hahn , SRE Engineering Manager Abstract : Netflix is a large, ever-changing ecosystem serving millions of customers across the globe through cloud-based systems and a globally distributed CDN.

AWS 100

AWS Entertainment Open Source Benchmarking 100

The Netflix TechBlog

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 202 A day in the life of a Netflix Engineer Dave Hahn , SRE Engineering Manager Abstract : Netflix is a large, ever-changing ecosystem serving millions of customers across the globe through cloud-based systems and a globally distributed CDN.

AWS 100

AWS Entertainment Open Source Benchmarking 100

Abhishek Tiwari

JULY 12, 2018

In recent times, in order to gain valuable insights or to develop the data-driven products companies such as Netflix, Spotify, Uber, AirBnB have built internal data pipelines. If built correctly, data pipelines can offer strategic advantages to the business. Depending on frameworks, data processing units (a.k.a

Latency 63

Latency Analytics Scalability Engineering 63

Abhishek Tiwari

APRIL 14, 2018

Developing Extract–transform–load (ETL) workflow is a time-consuming activity yet a very important component of data warehousing process. The process to develop ETL workflow is often ad-hoc, complex, trial and error based. It has been suggested that formal modeling of ETL process can alleviate most of these pain points.

Best Practices 40

Best Practices Database Design Efficiency 40

The Netflix TechBlog

DECEMBER 21, 2020

There are several benefits of such optimizations like saving on storage, faster query time, cheaper downstream processing, and an increase in developer productivity by removing additional ETLs written only for query performance improvement. Some of the optimizations are prerequisites for a high-performance data warehouse.

Storage 203

Storage Latency Efficiency Data Engineering 203

O'Reilly

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. The shift to cloud native design is transforming both software architecture and infrastructure and operations. Coincidence?

Software Architecture 132

Software Architecture DevOps Data Engineering Architecture 132

The Symphonia

JUNE 19, 2018

This type of talk is close to my heart since I strongly feel we need to do a lot of deep thinking (and subsequent knowledge sharing) of design and architecture patterns with Serverless. Over the past 9 months John’s been helping our friends at Beyondsoft with their new open-source Serverless data lake project?—?

Serverless 40

Serverless AWS DevOps Open Source 40

The Netflix TechBlog

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 202 A day in the life of a Netflix Engineer Dave Hahn , SRE Engineering Manager Abstract : Netflix is a large, ever-changing ecosystem serving millions of customers across the globe through cloud-based systems and a globally distributed CDN.

AWS 37

AWS Entertainment Open Source Benchmarking 37

The Netflix TechBlog

DECEMBER 3, 2022

Obviously not all tools are made with the same use case in mind, so we are planning to add more code samples for other (than classical batch ETL) data processing purposes, e.g. Machine Learning model building and scoring. The main workflow definition file holds the logic of a single run, in this case one day-worth of data.

Best Practices 358

Best Practices Code Testing Data Engineering 358

The Netflix TechBlog

FEBRUARY 9, 2022

see “data pipeline” Intro The problem of managing scheduled workflows and their assets is as old as the use of cron daemon in early Unix operating systems. The design of a cron job is simple, you take some system command, you pick the schedule to run it on and you are done. workflow ?—?see Example: 0 0 * * MON /home/alice/backup.sh

Storage 201

Storage Data Engineering Testing Code 201

The Netflix TechBlog

MARCH 25, 2019

Finally, imagine yourself in the role of a data platform reliability engineer tasked with providing advanced lead time to data pipeline (ETL) owners by proactively identifying issues upstream to their ETL jobs. Design a flexible data model ? —?Represent Enable seamless integration?—? push or pull.

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

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

The Netflix TechBlog

OCTOBER 18, 2022

In the data domain, it is common to have a super large number of jobs within a single workflow. For example, a workflow to backfill hourly data for the past five years can lead to 43800 jobs (24 * 365 * 5), each of which processes data for an hour. All the requests are processed via distributed queues for message passing.

Java 202

Java Scalability Traffic Architecture 202

Abhishek Tiwari

JULY 20, 2019

One thing stand-out to me is being intentional and practical about your engineering organisation design. First and foremost, being intentional about organisation design requires good and honest discussions about all possible option. Specialisation could be around products, business process, or technologies. Certainly not.

Engineering 61

Engineering Retail Airlines Healthcare 61

Testsigma

NOVEMBER 28, 2019

Udacity Udacity provides nanodegree programs on all automation languages like C++, Machine Learning, Data engineer, Robotics and more. They have diploma courses in Software Testing, Introduction to Python, Diploma in Design Thinking, Diploma in Python Programming. Test Management Improving the Test Process.

Website 53

Website Testing Programming Automotive 53

Abhishek Tiwari

DECEMBER 27, 2017

A common theme across all these trends is to remove the complexity by simplifying data management as a whole. In 2018, we anticipate that ETL will either lose relevance or the ETL process will disintegrate and be consumed by new data architectures. Unified data management architecture.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

O'Reilly

MARCH 2, 2020

When a project is going off track because some requirement wasn’t understood properly, you need to fix that as soon as possible—not after a year-long development process. This has to do with the concept of bounded context from Domain Driven Design.). When processes change, who wins, who loses, and why? Coincidence?

Artificial Intelligence 20

Artificial Intelligence Software Architecture Programming Infrastructure 20

The Netflix TechBlog

SEPTEMBER 10, 2019

Our data scientists faced numerous challenges in our previous infrastructure. Complex business logic was embedded directly into the ETL pipelines by data engineers. In order to replicate results, scientists had to delve deep into the data, code, and documentation.

Metrics 215

Metrics Architecture Infrastructure Innovation 215

All Things Distributed

NOVEMBER 15, 2016

Previously, I wrote about Amazon QuickSight , a new service targeted at business users that aims to simplify the process of deriving insights from a wide variety of data sources quickly, easily, and at a low cost. Put simply, data is not always readily available and accessible to organizational end users.

Analytics 152

Analytics Availability Media Social Media 152