The Netflix TechBlog

OCTOBER 27, 2020

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. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 252

Latency Storage Big Data Tuning 252

Dynatrace

FEBRUARY 16, 2023

As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022. Logs on Grail Log data is foundational for any IT analytics. .

Analytics 246

Analytics Innovation Metrics Database 246

The Netflix TechBlog

MAY 26, 2020

And in order to gain visibility into these logs, we need to somehow ingest and enrich this data. It is easier to tune a large Spark job for a consistent volume of data. In other words, we are able to ensure that our Spark app does not “eat” more data than it was tuned to handle. We named this library Sqooby.

Network 154

Network Tuning AWS Big Data 154

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. We have also noted a great potential for further improvement by model tuning (see the section of Rollout in Production).

Tuning 217

Tuning Efficiency Big Data Engineering 217

The Netflix TechBlog

JUNE 20, 2024

To address this, we propose developing an intelligent agent that can automatically discover, map, and query all data within an enterprise. This “Enterprise Data Model/Architect Agent” employs generative AI techniques for autonomous enterprise data modeling and architecture. Until next time!

Data Engineering 206

Data Engineering Engineering Entertainment Software Engineering 206

The Netflix TechBlog

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. Please stay tuned! The audits check for equality (i.e. Endnotes ¹ Inmon, Bill.

Big Data 257

Big Data Government Processing Analytics 257

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 211

Java Scalability Traffic Architecture 211

The Netflix TechBlog

NOVEMBER 3, 2023

The Data Mesh SQL Processor is a platform-managed, parameterized Flink Job that takes schematized sources and a Flink SQL query that will be executed against those sources. By leveraging Flink SQL within a Data Mesh Processor, we were able to support the streaming SQL functionality without changing the architecture of Data Mesh.

Processing 271

Processing Engineering Infrastructure Latency 271

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 212

Storage Latency Efficiency Data Engineering 212

Scalegrid

JANUARY 10, 2025

They keep the features that developers like but can handle much more data, similar to NoSQL systems. Notably, they simplify handling big data flows, offer consistent transactions, and sustain high performance even when they’re used for real-time data analysis and complex queries.

Database 130

Database Best Practices Scalability Blockchain 130

The Netflix TechBlog

NOVEMBER 20, 2023

For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. Backfill: Backfilling datasets is a common operation in big data processing.

Processing 219

Processing Big Data Efficiency Engineering 219

All Things Distributed

MARCH 28, 2011

We see that with our Amazon customers; when they hear a great tune on a radio they may identify it using the Shazam or Soundhound apps on their mobile phone and buy that song instantly from the Amazon MP3 store. Driving down the cost of Big-Data analytics. Introducing the AWS South America (Sao Paulo) Region.

AWS 123

AWS Cloud Storage Internet 123

Percona

JANUARY 19, 2023

ProxySQL: It is a feature-rich open-source MySQL proxy solution, that allows query routing for the most common MySQL architectures (PXC/Galera, Replication, Group Replication, etc.). It was developed for optimizing data storage and access for big data sets. It is available under a paid subscription.

Open Source 111

Open Source Storage Database Big Data 111

Rigor

JANUARY 13, 2020

Take, for example, The Web Almanac , the golden collection of Big Data combined with the collective intelligence from most of the authors listed below, brilliantly spearheaded by Google’s @rick_viscomi. Information Architecture. Web Performance Tuning. Web Performance Daybook-Volume-2. Website Optimization.

Performance 75

Performance Social Media Website Website Performance 75

Brendan Gregg

APRIL 30, 2018

In this year's CFP we’re looking for topics covering the latest trends and best practices in cloud computing, containerization, machine learning, big data, infrastructure, scalability, DevOps, IT management, automation, reliability, monitoring, performance tuning, security, databases, programming, datacenters, and more.

DevOps 41

DevOps Network Best Practices Programming 41

Brendan Gregg

APRIL 29, 2018

In this year's CFP we’re looking for topics covering the latest trends and best practices in cloud computing, containerization, machine learning, big data, infrastructure, scalability, DevOps, IT management, automation, reliability, monitoring, performance tuning, security, databases, programming, datacenters, and more.

DevOps 40

DevOps Network Best Practices Programming 40

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 112

Artificial Intelligence Big Data Data Engineering Latency 112

SQL Server According to Bob

FEBRUARY 15, 2018

Best practices on Building a Big Data Analytics Solution – Michael Rys. If you want to learn about Azure Data Lake, there is no one better. Friday Sessions: SQL Intelligence excels your tuning and security expertise – Veljko Vasic, Ron Matchoro and Frans Lytzen. I’ve known Michael for a very long time.

Engineering 40

Engineering Azure Best Practices Servers 40

The Netflix TechBlog

OCTOBER 15, 2019

In Netflix the microservice architecture is widely adopted and each microservice typically handles only one type of data. The core movie data resides in a microservice called Movie Service, and related data such as movie deals, talents, vendors and so on are managed by multiple other microservices (e.g Please stay tuned.

Transportation 199

Transportation Architecture Processing Storage 199

Adrian Cockcroft

NOVEMBER 18, 2024

Discover data sources to gain insights into your resource efficiency and environmental impact, including the AWS Customer Carbon Footprint Tool and proxy metrics from the AWS Cost & Usage Reports. This lightning talk explores how companies can cut costs and carbon emissions through architectural best practices and workload optimization.

AWS 98

AWS Energy Lambda Government 98