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 245

Innovation Metrics Engineering Testing 245

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 185

Infrastructure Cloud Scalability AWS 185

VoltDB

DECEMBER 11, 2024

Edge computing has transformed how businesses and industries process and manage data. By bringing computation closer to the data source, edge-based deployments reduce latency, enhance real-time capabilities, and optimize network bandwidth. Data interception during transit. Redundancy and inefficiency in data aggregation.

IoT 52

IoT Energy Logistics Latency 52

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 221

Metrics Architecture Infrastructure Innovation 221

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

InfoQ

NOVEMBER 18, 2024

Uber uses Presto, an open-source distributed SQL query engine, to provide analytics across several data sources, including Apache Hive, Apache Pinot, MySQL, and Apache Kafka. To improve its performance, Uber engineers explored the advantages of dealing with quick queries, a.k.a.

Analytics 80

Analytics Open Source Engineering Performance 80

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 145

Software Architecture DevOps Data Engineering Architecture 145

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 246

Artificial Intelligence Tuning Strategy Big Data 246

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 219

Processing Big Data Efficiency Engineering 219

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 82

Technology Technology Architecture Engineering 82

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 110

Efficiency Engineering Design Storage 110

Simform

JANUARY 8, 2023

Data ingestion is the foremost layer in a data engineering pipeline, acting as a vital pillar in the overall analytics architecture. Thus, it is essential to implement data ingestion just right. Here is everything you need to know to take the first step toward a flawless data pipeline.

Data Engineering 52

Data Engineering Analytics Architecture Engineering 52

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

Big Data 112

Big Data Artificial Intelligence Data Engineering Latency 112

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 154

Network Tuning AWS Big Data 154

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

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

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

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 145

Database Architecture Education Systems 145

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

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 102

Software Architecture Monitoring Software Engineering Code 102

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 126

Analytics Availability Media Social Media 126

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

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 138

Storage Scalability Database Technology 138

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

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

InfoQ

AUGUST 7, 2024

Canva evaluated different data massaging solutions for its Product Analytics Platform, including the combination of AWS SNS and SQS, MKS, and Amazon KDS, and eventually chose the latter, primarily based on its much lower costs. The company compared many aspects of these solutions, like performance, maintenance effort, and cost.

AWS 91

AWS Analytics Performance Data Engineering 91

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

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

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

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

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 89

Development Design Data Engineering Scalability 89

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 85

Processing Traffic Data Engineering Scalability 85

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 88

Cache Latency Traffic Database 88