The Netflix TechBlog

JANUARY 11, 2022

Here we describe the role of Experimentation and A/B testing within the larger Data Science and Engineering organization at Netflix, including how our platform investments support running tests at scale while enabling innovation. Curious to learn more about other Data Science and Engineering functions at Netflix?

Innovation 243

Innovation Metrics Engineering Testing 243

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 106

Artificial Intelligence Big Data Data Engineering Latency 106

Simform

JANUARY 25, 2023

Businesses can unlock the value of data only after it is transformed into actionable insights and when those insights are delivered promptly. But implementing such robust data pipelines can be complex and challenging. This blog discusses all the ins and outs of building data pipelines and how they can help strengthen businesses.

Architecture 52

Architecture Data Engineering Engineering 52

The Netflix TechBlog

MARCH 5, 2019

While our engineering teams have and continue to build solutions to lighten this cognitive load (better guardrails, improved tooling, …), data and its derived products are critical elements to understanding, optimizing and abstracting our infrastructure. In the Reliability space, our data teams focus on two main approaches.

Infrastructure 182

Infrastructure Cloud Scalability AWS 182

Abhishek Tiwari

FEBRUARY 26, 2020

The evolution of your technology architecture should depend on the size, culture, and skill set of your engineering organization. There are no hard-and-fast rules to figure out interdependency between technology architecture and engineering organization but below is what I think can really work well for product startup.

Technology 81

Technology Technology Architecture Engineering 81

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

The Netflix TechBlog

SEPTEMBER 10, 2019

After recreating the dataset, you can plot the raw numbers and perform custom analyses to understand the distribution of the data across test cells. However, the default reports only provide a summary view of the data with some powerful but limited filtering options.

Metrics 215

Metrics Architecture Infrastructure Innovation 215

O'Reilly

FEBRUARY 18, 2020

It’s also the data source for our annual usage study, which examines the most-used topics and the top search terms. [1]. 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.

Software Architecture 132

Software Architecture DevOps Data Engineering Architecture 132

Dynatrace

JULY 6, 2022

Scripts and procedures usually focus on a particular task, such as deploying a new microservice to a Kubernetes cluster, implementing data retention policies on archived files in the cloud, or running a vulnerability scanner over code before it’s deployed. The range of use cases for automating IT is as broad as IT itself.

Artificial Intelligence 194

Artificial Intelligence Tuning Strategy Big Data 194

Abhishek Tiwari

JULY 12, 2018

Building data pipelines can offer strategic advantages to the business. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines. Data pipeline initiatives are generally unfinished projects. In this post, we will discuss why you should avoid building data pipelines in first place.

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. Key challenges. Performance.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Abhishek Tiwari

DECEMBER 27, 2017

ETL refers to extract, transform, load and it is generally used for data warehousing and data integration. There are several emerging data trends that will define the future of ETL in 2018. A common theme across all these trends is to remove the complexity by simplifying data management as a whole.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

Uber Engineering

AUGUST 14, 2019

Maintaining Uber’s large-scale data warehouse comes with an operational cost in terms of ETL functions and storage. Once identified, … The post Less is More: Engineering Data Warehouse Efficiency with Minimalist Design appeared first on Uber Engineering Blog.

Efficiency 99

Efficiency Engineering Design Storage 99

The Netflix TechBlog

MAY 26, 2020

By collecting, accessing and analyzing network data from a variety of sources like VPC Flow Logs, ELB Access Logs, Custom Exporter Agents, etc, we can provide Network Insight to users through multiple data visualization techniques like Lumen , Atlas , etc. At Netflix we publish the Flow Log data to Amazon S3.

Network 150

Network Tuning AWS Big Data 150

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. SUS302 Optimizing architectures for sustainability — Katja Philipp AWS SA and Szymon Kochanski AWS SA. Good example, well presented interesting new material.

AWS 64

AWS Energy Architecture Programming 64

Abhishek Tiwari

DECEMBER 23, 2017

Data integration generally requires in-depth domain knowledge, a strong understanding of data schemas and underlying relationships. This can be time-consuming and bit challenging if you are dealing with hundreds of data sources and thousands of event types (see my recent article on ELT architecture ).

Architecture 40

Architecture Engineering Processing Code 40

High Scalability

APRIL 14, 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 Scalability Engineering 105

Simform

FEBRUARY 14, 2023

Stream processing has become a core part of enterprise data architecture today due to the explosive growth of data from sources such as IoT sensors, security logs, and web applications. This blog discusses the topic of stream processing in detail to help you navigate its landscape with ease.

Processing 52

Processing IoT Architecture Data Engineering 52

High Scalability

MAY 12, 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 102

Education Software Engineering Scalability Engineering 102

High Scalability

APRIL 28, 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 102

Education Software Engineering Scalability Engineering 102

High Scalability

MAY 26, 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 100

Education AWS Software Engineering Scalability 100

InfoQ

DECEMBER 29, 2023

Zendesk reduced its data storage costs by over 80% by migrating from DynamoDB to a tiered storage solution using MySQL and S3. The company considered different storage technologies and decided to combine the relational database and the object store to strike a balance between querybility and scalability while keeping the costs down.

Storage 134

Storage Scalability Database Technology 134

O'Reilly

JULY 15, 2020

Software engineers comprise the survey audience’s single largest cluster, over one quarter (27%) of respondents (Figure 1). If you combine the different architectural roles—i.e., Adding architects and engineers, we see that roughly 55% of the respondents are directly involved in software development. Figure 1: Respondent roles.

Database 134

Database Architecture Education Systems 134

O'Reilly

FEBRUARY 2, 2020

First, the behavior of an AI application depends on a model , which is built from source code and training data. A model isn’t source code, and it isn’t data; it’s an artifact built from the two. You need a repository for models and for the training data. Models almost certainly react to incoming data; that’s their point.

Software Architecture 67

Software Architecture Monitoring Software Engineering Architecture 67

InfoQ

JULY 14, 2023

Mei-Chin Tsai, Vinod discuss the internal architecture of Azure Cosmos DB and how it achieves high availability, low latency, and scalability. By Mei-Chin Tsai, Vinod Sridharan

Latency 52

Latency Azure Availability Scalability 52

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

The Symphonia

JUNE 19, 2018

I was fortunate to be both presenting a 2-day workshop (on AWS Serverless Architectures and Continuous Deployment) as well as hosting a full-day Serverless track of talks. One of the catalysts for starting Symphonia was the massive interest in my article on “ Serverless Architectures ” that is published on Martin Fowler’s site.

Serverless 40

Serverless AWS DevOps Open Source 40

Abhishek Tiwari

DECEMBER 22, 2017

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. Then we perform frequent batch ETL from application databases to a data warehouse. Classic ETL. then ELT is a more preferred option.

Big Data 40

Big Data Retail Storage Google 40

Abhishek Tiwari

JULY 20, 2019

The engineering organisation described may not work for you because of a team of 8-10 people is still a very big overhead. In this model, software architecture and code ownership is a reflection of the organisational model. Thirdly, let engineers themselves choose the delivery teams and organise them around the initiative.

Engineering 61

Engineering Retail Airlines Healthcare 61

InfoQ

NOVEMBER 29, 2023

HubSpot adopted routing messages over multiple Kafka topics (called swimlanes) for the same producer to avoid the build-up in the consumer group lag and prioritize the processing of real-time traffic.

Processing 79

Processing Traffic Data Engineering Scalability 79

InfoQ

DECEMBER 20, 2023

InfoQ is delighted to announce a new two-day conference, InfoQ Dev Summit Boston 2024, taking place June 24-25, 2024. This event is designed to help senior developers navigate their immediate development challenges, focusing exclusively on the technical aspects that matter right now. By Artenisa Chatziou

Development 83

Development Design Data Engineering Scalability 83

O'Reilly

MARCH 2, 2020

The most important is discovering how to work with data science and artificial intelligence projects. Radar data points: Recent research and analysis. In “ 5 key areas for tech leaders to watch in 2020 ,” we examined search and usage data from the O’Reilly online learning platform. They’d simply be what we do.

Artificial Intelligence 20

Artificial Intelligence Software Architecture Programming Infrastructure 20

InfoQ

JULY 3, 2023

LinkedIn introduced Couchbase as a centralized caching tier for scaling member profile reads to handle increasing traffic that has outgrown their existing database cluster. The new solution achieved over 99% hit rate, helped reduce tail latencies by more than 60% and costs by 10% annually. By Rafal Gancarz

Cache 83

Cache Latency Traffic Database 83

InfoQ

AUGUST 3, 2023

AWS recently announced the general availability (GA) of Amazon EC2 P5 instances powered by the latest NVIDIA H100 Tensor Core GPUs suitable for users that require high performance and scalability in AI/ML and HPC workloads. The GA is a follow-up to the earlier announcement of the development of the infrastructure. By Steef-Jan Wiggers

AWS 77

AWS Availability Scalability Infrastructure 77

InfoQ

JULY 20, 2023

Microsoft recently announced the general availability (GA) of Azure Managed Lustre, a managed file system for high-performance computing (HPC) and AI workloads. By Steef-Jan Wiggers

Azure 40

Azure Availability Systems Performance 40

InfoQ

APRIL 7, 2021

Recently, Google announced A2 Virtual Machines (VMs)' general availability based on the NVIDIA Ampere A100 Tensor Core GPUs in Compute Engine.

Virtualization 56

Virtualization Google Availability Engineering 56