The Netflix TechBlog

NOVEMBER 14, 2023

In the previous installments of this series, we introduced Psyberg and delved into its core operational modes: Stateless and Stateful Data Processing. Pipelines After Psyberg Let’s explore how different modes of Psyberg could help with a multistep data pipeline. This is compatible with both Python and Scala Spark.

Tuning 244

Tuning Processing C++ Efficiency 244

Dynatrace

JULY 6, 2022

At its most basic, automating IT processes works by executing scripts or procedures either on a schedule or in response to particular events, such as checking a file into a code repository. Adding AIOps to automation processes makes the volume of data that applications and multicloud environments generate much less overwhelming.

Artificial Intelligence 185

Artificial Intelligence Tuning Strategy Big Data 185

The Netflix TechBlog

MARCH 5, 2019

As a micro-service owner, a Netflix engineer is responsible for its innovation as well as its operation, which includes making sure the service is reliable, secure, efficient and performant. How can we develop templated detection modules (rules- and ML-based) and data streams to increases speed of development?

Infrastructure 182

Infrastructure Cloud Scalability AWS 182

The Netflix TechBlog

MARCH 4, 2024

Introduction At Netflix, hundreds of thousands of workflows and millions of jobs are running per day across multiple layers of the big data platform. In this way, no human intervention is required in the remediation process. Multi-objective optimizations. Auto Remediation generates recommendations by considering both performance (i.e.,

Tuning 210

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

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

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

Education 102

Education Software Engineering Scalability Engineering 102

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

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 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. Advertise your job here!

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. Advertise your job here!

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. Advertise your job here!

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. Advertise your job here!

Education 108

Education Games Engineering Java 108

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

O'Reilly

FEBRUARY 2, 2020

A model isn’t source code, and it isn’t data; it’s an artifact built from the two. Given source code and the training data, you could re-produce a model, but it almost certainly wouldn’t be the same because of randomization in the training process. Second, the behavior of AI systems changes over time.

Software Architecture 68

Software Architecture Monitoring Software Engineering Architecture 68

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

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Adrian Cockcroft

FEBRUARY 13, 2023

Discussion of the water positive goal and optimizations that let AWS return water directly for irrigation rather than to the sewage system. This is the AWS Professional Services built tooling that customers can use to track the carbon footprint of their operations and processes, along with a customer example.

AWS 64

AWS Energy Architecture Programming 64

All Things Distributed

AUGUST 24, 2012

Werner Vogels weblog on building scalable and robust distributed systems. Which makes this week a good moment to read up on some of the historical work around the costs of data engineering. All Things Distributed. Back-to-Basics Weekend Reading - The 5 Minute Rule. By Werner Vogels on 24 August 2012 04:00 PM. Comments ().

Storage 108

Storage Hardware AWS Data Engineering 108

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. Use cases We found several use cases where a system like AutoOptimize can bring tons of value.

Storage 203

Storage Latency Efficiency Data Engineering 203

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 3, 2022

The dataflow migration command is a special feature, developed single handedly by Stephen Huenneke , to fully automate the communication and tracking of a data warehouse table changes. This allows other processes, consuming our table, to be notified and start their processing. test_sparksql_write.py

Best Practices 358

Best Practices Code Testing Data Engineering 358

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

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. Manually constructed continuous delivery system.

Storage 201

Storage Data Engineering Testing Code 201

O'Reilly

FEBRUARY 18, 2020

Usage specific to Python as a programming language grew by just 4% in 2019; by contrast, usage that had to do with Python and ML—be it in the context of AI, deep learning, and natural language processing, or in combination with any of several popular ML/AI frameworks—grew by 9%. In aggregate, data engineering usage declined 8% in 2019.

Software Architecture 134

Software Architecture DevOps Data Engineering Architecture 134

Testsigma

NOVEMBER 28, 2019

They have an affiliation with universities like MIT, Harvard University, Boston University, The University of Texas System and more. Udacity Udacity provides nanodegree programs on all automation languages like C++, Machine Learning, Data engineer, Robotics and more. Test Management Improving the Test Process.

Website 53

Website Testing Programming Automotive 53

The Netflix TechBlog

JULY 21, 2022

Since memory management is not something one usually associates with classification problems, this blog focuses on formulating the problem as an ML problem and the data engineering that goes along with it. We now explore each of these components individually, while highlighting the nuances of the data pipeline and pre-processing.

Big Data 179

Big Data Cache Engineering Data Engineering 179

The Netflix TechBlog

SEPTEMBER 18, 2020

The Engineer enjoys making data available by piping it in from new sources in optimal ways, building robust data models, prototyping systems, and doing project-specific engineering.

Analytics 240

Analytics Engineering Data Engineering Tuning 240

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. Let’s review a few of these principles: Ensure data integrity ?—?Accurately Enable seamless integration?—?

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

The Netflix TechBlog

OCTOBER 18, 2022

Due to its popularity, the number of workflows managed by the system has grown exponentially. The scheduler on-call has to closely monitor the system during non-business hours. As the usage increased, we had to vertically scale the system to keep up and were approaching AWS instance type limits.

Java 202

Java Scalability Traffic Architecture 202

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

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

Abhishek Tiwari

JULY 20, 2019

Specialisation could be around products, business process, or technologies. One way to create a Spotify model inspired engineering organisation is to organise long-lived squads by retail business process hubs - i.e. specialisation around business process. Let's take an example of retail as a domain of interest.

Engineering 61

Engineering Retail Airlines Healthcare 61

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