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

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! this is going to be a challenging journey for any backend engineer!

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! this is going to be a challenging journey for any backend engineer!

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! this is going to be a challenging journey for any backend engineer!

Education 102

Education Software Engineering Scalability Engineering 102

Dynatrace

MARCH 14, 2022

The healthcare industry is embracing cloud technology to improve the efficiency, quality, and security of patient care, and this year’s HIMSS Conference in Orlando, Fla., AIOps (or “AI for IT operations”) uses artificial intelligence so that big data can help IT teams work faster and more effectively.

Healthcare 226

Healthcare Artificial Intelligence Innovation Strategy 226

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! this is going to be a challenging journey for any backend engineer!

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! this is going to be a challenging journey for any backend engineer!

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! this is going to be a challenging journey for any backend engineer! How to screen candidates efficiently, effectively, and without bias. Who's Hiring? Please apply here.

Education 105

Education Software Engineering Engineering Big Data 105

Scalegrid

MAY 13, 2020

It’s architecture was specially designed to manage large-scale data warehouses and business intelligence workloads by giving you the ability to spread your data out across a multitude of servers. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Percona

JANUARY 19, 2023

For instance, in Percona Managed Services , we have many clients with TBs worth of data that are well performant. In this blog post, we will review key topics to consider for managing large datasets more efficiently in MySQL. InnoDB will sort the data in primary key order, and that will serve to reference actual data pages on disk.

Open Source 91

Open Source Storage Database Big Data 91

Testsigma

MAY 26, 2021

Not only does Testsigma really eases the setup of your data-driven testing, being cloud-based gives you the ability to start with your automation soon after you signup. Opt for quick and efficient data-driven testing with Testsigma. Read about the simplicity of data-driven testing with Testsigma here. Sign up Now.

Testing 70

Testing Healthcare Performance Testing Website 70

KeyCDN

OCTOBER 2, 2018

Codrops Codrops features blogs with topics ranging from UI design and page animations to image formatting and general JavaScript practices. A List Apart A List Apart focuses on UX and branding from business and design-oriented perspectives. Topics include web design, security, web-based tools and workflows and more.

Development 75

Development Website Design Code 75

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. Backfill: Backfilling datasets is a common operation in big data processing.

Processing 210

Processing Big Data Efficiency Engineering 210

Scalegrid

MARCH 28, 2024

As Redis stores data, it supports extensive data key and string lengths, up to 512 MB, while offering complex data structures like: lists sets sorted sets hashes bitmaps These features make Redis much more than a basic caching engine; it is a versatile tool capable of supporting diverse data models.

Cache 130

Cache Storage Scalability Architecture 130

Scalegrid

MARCH 14, 2024

In practice, a hybrid cloud operates by melding resources and services from multiple computing environments, which necessitates effective coordination, orchestration, and integration to work efficiently. Tailoring resource allocation efficiently ensures faster application performance in alignment with organizational demands.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

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

The Netflix TechBlog

FEBRUARY 16, 2021

Membership Engineering at Netflix is responsible for the plan and pricing configurations for every market worldwide. However, with our rapid product innovation speed, the whole approach experienced significant challenges: Business Complexity: The existing SKU management solution was designed years ago when the engagement rules were simple?—?three

Mobile 209

Mobile Engineering Infrastructure Scalability 209

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

OCTOBER 27, 2020

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy.

Latency 243

Latency Storage Big Data Tuning 243

The Netflix TechBlog

APRIL 29, 2019

Various software systems are needed to design, build, and operate this CDN infrastructure, and a significant number of them are written in Python. Python has long been a popular programming language in the networking space because it’s an intuitive language that allows engineers to quickly solve networking problems.

Open Source 279

Open Source Network Infrastructure Big Data 279

Dynatrace

OCTOBER 25, 2022

Organizations adopt DevOps, where developers and operations work together in a continuous loop, so they can develop software and resolve issues efficiently before they affect users. Davis®— the Dynatrace purpose-built AI engine —further uses event proximity and baselined data for automatic correlation and noise suppression.

DevOps 216

DevOps Big Data Cloud Innovation 216

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 202

Java Scalability Traffic Architecture 202

Dynatrace

OCTOBER 14, 2021

Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” But what is AIOps, exactly? And how can it support your organization? What is AIOps? Autonomous operations.

Artificial Intelligence 210

Artificial Intelligence DevOps Innovation Metrics 210

The Morning Paper

OCTOBER 26, 2020

On the surface this is a paper about fast data ingestion from high-volume streams, with indexing to support efficient querying. Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. PVLDB’20.

Cloud 104

Cloud Big Data Latency Architecture 104

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

Dynatrace

JUNE 1, 2020

With our AI engine, Davis, at the core Dynatrace provides precise answers in real-time. Trying to manually keep up, configure, script and source data is beyond human capabilities and today everything must be automated and continuous. Some customers even say, having Davis is like having a whole team of engineers on their side.

Artificial Intelligence 182

Artificial Intelligence Social Media Monitoring IoT 182

Dynatrace

JUNE 1, 2020

With our AI engine, Davis, at the core Dynatrace provides precise answers in real-time. Trying to manually keep up, configure, script and source data is beyond human capabilities and today everything must be automated and continuous. Some customers even say, having Davis is like having a whole team of engineers on their side.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

O'Reilly

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Hardware 99

Hardware Storage Big Data Blockchain 99

Highly Scalable

MARCH 1, 2012

The following figure depicts imaginary “evolution” of the major NoSQL system families, namely, Key-Value stores, BigTable-style databases, Document databases, Full Text Search Engines, and Graph databases: NoSQL Data Models. The main design theme is “ What answers do I have?” ” .

Database 279

Database Ecommerce Efficiency Engineering 279

The Morning Paper

SEPTEMBER 19, 2019

AliGraph covers Alibaba’s distributed graph engine supporting the development of new GNN applications. Their dataset has about 7B edges… Meanwhile, AnalyticDB is Alibaba’s real-time OLAP RDBMS handling 10PB of data (in excess of 100 trillion rows!). .” Could it be Analyzing efficient stream processing on modern hardware ?

Blockchain 46

Blockchain Hardware Google Analytics 46

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

All Things Distributed

NOVEMBER 15, 2010

These trade-offs have even impacted the way the lowest level building blocks in our computer architectures have been designed. Graphics processing is one such area with huge computational requirements, but where each of the tasks is relatively small and often a set of operations are performed on data in the form of a pipeline.

AWS 136

AWS Latency Programming Architecture 136

Highly Scalable

MARCH 10, 2015

This article describes six major optimization problems related to marketing and pricing that can be solved leveraging data mining techniques. Although these problems are very different, we are trying to establish a common framework that helps to design optimization and data mining tasks required for solutions.

Retail 152

Retail C++ Analytics Metrics 152

ACM Sigarch

NOVEMBER 1, 2019

As is the case for many high-quality computer systems conferences, the papers presented here involve a significant amount of engineering and experimentation on real hardware to convincingly evaluate innovative concepts end-to-end in a realistic setting. ATC ’19 was refreshingly different.

Architecture 12

Architecture Hardware Cache Storage 12

Smashing Magazine

JULY 29, 2019

I hope to raise the profile of difficulties faced by real people, which are avoidable if we design and develop in a way that is sympathetic to their needs. Read “ Efficiently load JavaScript with defer and async ” for more information. Last time, I navigated the web for a day using Internet Explorer 8. Anyway, enough Google dissecting.

Cache 96

Cache Google Mobile Network 96

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 215

Metrics Architecture Infrastructure Innovation 215

Testsigma

FEBRUARY 12, 2021

The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. 38% of organisations were expected to introduce machine-learning initiatives in 2019, according to the Capgemini World Efficiency survey. Many changes are rendered through automated testing. from $12.6

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92