Uber Engineering

AUGUST 14, 2019

Maintaining Uber’s large-scale data warehouse comes with an operational cost in terms of ETL functions and storage. In our experience, optimizing for operational efficiency requires answering one key question: for which tables does the maintenance cost supersede utility?

Efficiency 110

Efficiency Engineering Design Storage 110

The Netflix TechBlog

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.

Processing 226

Processing Data Engineering Efficiency Analytics 226

The Netflix TechBlog

NOVEMBER 14, 2023

By focusing solely on updates and avoiding reprocessing of data based on a fixed lookback window, both Stateless and Stateful Data Processing maintain a minimal change footprint. This approach ensures data processing is both efficient and accurate.

Tuning 244

Tuning Processing C++ Efficiency 244

High Scalability

JUNE 15, 2020

This is a guest post by Eunice Do , Data Engineer at TripleLift , a technology company leading the next generation of programmatic advertising. The system is the data pipeline at TripleLift. TripleLift is an adtech company, and like most companies in this industry, we deal with high volumes of data on a daily basis.

Processing 206

Processing Data Engineering Efficiency Engineering 206

Dynatrace

JULY 6, 2022

Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises. Automating IT practices offers enterprises faster data centers and cloud operations, as well as increased flexibility and accuracy. IT automation tools can achieve enterprise-wide efficiency. Read eBook now!

Artificial Intelligence 197

Artificial Intelligence Tuning Strategy Big Data 197

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. In the Efficiency space, our data teams focus on transparency and optimization.

Infrastructure 182

Infrastructure Cloud Scalability AWS 182

The Netflix TechBlog

MARCH 7, 2024

Under the hood, Titus is powered by Kubernetes , but it provides a thick layer of enhancements over off-the-shelf Kubernetes, to make it more observable , secure , scalable , and cost-efficient. Internally, we use a production workflow orchestrator called Maestro.

Systems 226

Systems Media Cache Open Source 226

The Netflix TechBlog

SEPTEMBER 18, 2020

[Julie] Chris and I have the same primary stakeholders (or engineering team that we support): Encoding Technologies. They are continuously innovating compression algorithms to efficiently send high quality audio and video files to our customers over the internet. Is the benefit uniform, or do certain cohorts of members?—?such

Analytics 223

Analytics Education Innovation Engineering 223

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 Innovation C++ Engineering 207

High Scalability

MARCH 17, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 105

Education Engineering Java Software Engineering 105

High Scalability

MARCH 3, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 114

Education Games Engineering Java 114

High Scalability

FEBRUARY 18, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 113

Education Games Engineering Java 113

High Scalability

APRIL 14, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 105

Education Software Engineering Scalability Engineering 105

High Scalability

MAY 12, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MARCH 24, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

FEBRUARY 9, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 108

Education Games Engineering Java 108

High Scalability

APRIL 28, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MARCH 30, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MAY 26, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 100

Education AWS Software Engineering Scalability 100

The Netflix TechBlog

NOVEMBER 22, 2019

3:15pm-4:15pm OPN 209 Netflix’s application deployment at scale Andy Glover , Director Delivery Engineering & Paul Roberts, AWS Abstract : Spinnaker is an open-source continuous-delivery platform created by Netflix to improve its developers’ efficiency and reduce the time it takes to get an application into production.

AWS 100

AWS Entertainment Open Source Benchmarking 100

The Netflix TechBlog

NOVEMBER 22, 2019

3:15pm-4:15pm OPN 209 Netflix’s application deployment at scale Andy Glover , Director Delivery Engineering & Paul Roberts, AWS Abstract : Spinnaker is an open-source continuous-delivery platform created by Netflix to improve its developers’ efficiency and reduce the time it takes to get an application into production.

AWS 100

AWS Entertainment Open Source Benchmarking 100

InfoQ

APRIL 7, 2021

According to the company, the A2 VMs will allow customers to run their NVIDIA CUDA-enabled machine learning (ML) and high-performance computing (HPC) scale-out and scale-up workloads efficiently at a lower cost. By Steef-Jan Wiggers.

Virtualization 55

Virtualization Google Availability Engineering 55

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. 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

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 203

Storage Latency Efficiency Data Engineering 203

The Netflix TechBlog

NOVEMBER 20, 2023

It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. Users configure the workflow to read the data in a window (e.g.

Processing 210

Processing Big Data Efficiency Engineering 210

Abhishek Tiwari

JULY 12, 2018

Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. Not everyone is operating at Netflix or Spotify scale data engineering function. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines.

Latency 63

Latency Analytics Scalability Engineering 63

The Netflix TechBlog

NOVEMBER 22, 2019

This talk explores the journey, learnings, and improvements to performance analysis, efficiency, reliability, and security. Our data scientists are expected to develop and operate large machine learning workflows autonomously without the need to be deeply experienced with systems or data engineering.

AWS 37

AWS Entertainment Open Source Benchmarking 37

Abhishek Tiwari

APRIL 14, 2018

First and foremost, modeling ETL process helps in designing an efficient, robust and evolvable ETL. Second, modeling ETL workflow plays an important role to optimize the data warehousing. Modeling of ETL workflow is important for several reasons.

Best Practices 40

Best Practices Database Efficiency Design 40

The Netflix TechBlog

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

Abhishek Tiwari

JULY 7, 2023

Airflow provides rich scheduling and execution semantics enabling data engineers to easily define complex pipelines, running at regular intervals. Workflow platforms have emerged as a crucial component for these companies, enabling them to orchestrate complex tasks, automate processes, and ensure efficient collaboration.

Logistics 52

Logistics Transportation Scalability Data Engineering 52

The Netflix TechBlog

OCTOBER 18, 2022

It is a general-purpose workflow orchestrator that provides a fully managed workflow-as-a-service (WAAS) to the data platform at Netflix. It serves thousands of users, including data scientists, data engineers, machine learning engineers, software engineers, content producers, and business analysts, for various use cases.

Java 202

Java Scalability Traffic Architecture 202

Abhishek Tiwari

DECEMBER 27, 2017

A unified data management (UDM) system combines the best of data warehouses, data lakes, and streaming without expensive and error-prone ETL. It offers reliability and performance of a data warehouse, real-time and low-latency characteristics of a streaming system, and scale and cost-efficiency of a data lake.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

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

The Netflix TechBlog

JANUARY 11, 2022

To learn about Analytics and Viz Engineering, have a look at Analytics at Netflix: Who We Are and What We Do by Molly Jackman & Meghana Reddy and How Our Paths Brought Us to Data and Netflix by Julie Beckley & Chris Pham. Curious to learn about what it’s like to be a Data Engineer at Netflix?

Innovation 243

Innovation Metrics Engineering Testing 243