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. Rule Execution Engine is responsible for matching the collected logs against a set of predefined rules.

Tuning 210

Tuning Efficiency Big Data Engineering 210

The Netflix TechBlog

JANUARY 13, 2022

By Vikram Srivastava and Marcelo Mayworm Netflix has one of the most complex data platforms in the cloud on which our data scientists and engineers run batch and streaming workloads. And we can’t discount the productivity impact it causes on data platform users.

Big Data 238

Big Data Infrastructure Metrics Hardware 238

Uber Engineering

AUGUST 3, 2018

From driver and rider locations and destinations, to restaurant orders and payment transactions, every interaction on Uber’s transportation platform is driven by data.

Big Data 110

Big Data Transportation Engineering Storage 110

DZone

DECEMBER 27, 2023

Welcome to the first post in our exciting series on mastering offline data pipeline's best practices, focusing on the potent combination of Apache Airflow and data processing engines like Hive and Spark. Working together, they form the backbone of many modern data engineering solutions.

Best Practices 140

Best Practices Data Engineering Big Data Games 140

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.

Big Data 63

Big Data Storage Benchmarking Hardware 63

The Morning Paper

DECEMBER 13, 2020

An overview of end-to-end entity resolution for big data , Christophides et al., It’s an important part of many modern data workflows, and an area I’ve been wrestling with in one of my own projects. ACM Computing Surveys, Dec. 2020, Article No.

Big Data 83

Big Data Open Source Processing Analytics 83

DZone

DECEMBER 21, 2020

Applications used in the field of Big Data process huge amounts of information, and this often happens in real time. Naturally, such applications must be highly reliable so that no error in the code can interfere with data processing. It is an open-source framework for distributed processing of large amounts of data.

Code 159

Code Java Big Data Open Source 159

The Netflix TechBlog

SEPTEMBER 18, 2020

and what the role entails by Julie Beckley & Chris Pham This Q&A provides insights into the diverse set of skills, projects, and culture within Data Science and Engineering (DSE) at Netflix through the eyes of two team members: Chris Pham and Julie Beckley. What was your path to working in data? There’s us to the right!

Analytics 223

Analytics Education Innovation Engineering 223

DZone

JULY 17, 2023

Apache Spark is a leading platform in the field of big data processing, known for its speed, versatility, and ease of use. Understanding Apache Spark Apache Spark is a unified computing engine designed for large-scale data processing. However, getting the most out of Spark often involves fine-tuning and optimization.

Big Data 130

Big Data Performance Open Source Tuning 130

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

Dynatrace

JUNE 26, 2023

Software analytics offers the ability to gain and share insights from data emitted by software systems and related operational processes to develop higher-quality software faster while operating it efficiently and securely. This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI.

Software 192

Software Software Analytics Big Data 192

All Things Distributed

AUGUST 18, 2011

Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud. However, this cannot be done without efficient, scalable data analytics.

Big Data 111

Big Data Analytics AWS Cloud 111

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

Uber Engineering

JANUARY 15, 2020

Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform. .

Engineering 115

Engineering Analytics Big Data Database 115

DZone

JULY 29, 2019

In today's world, data is generated in high volumes and to make something out of it, extracted data is needed to be transformed, stored, maintained, governed and analyzed. These processes are only possible with a distributed architecture and parallel processing mechanisms that Big Data tools are based on.

Big Data 162

Big Data Government Open Source Storage 162

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 193

Artificial Intelligence Tuning Strategy Big Data 193

Uber Engineering

DECEMBER 17, 2019

Uber’s busy 2019 included our billionth delivery of an Uber Eats order, 24 million miles covered by bike and scooter riders on our platform, and trips to top destinations such as the Empire State Building, the Eiffel Tower, and the … The post Uber’s Data Platform in 2019: Transforming Information to Intelligence appeared first on Uber Engineering (..)

Engineering 126

Engineering Big Data Infrastructure Analytics 126

Dynatrace

MARCH 24, 2023

Generally, container orchestration tools communicate with a user-created YAML or JSON file — formats that enable data exchange between applications and languages — that describes the configuration of the application or service. Mesos also supports other orchestration engines, including Kubernetes and Docker Swarm.

Infrastructure 190

Infrastructure Open Source Operating System Cloud 190

Scalegrid

MAY 13, 2020

It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. 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

DZone

DECEMBER 21, 2020

Setting up a data warehouse is the first step towards fully utilizing big data analysis. Still, it is one of many that need to be taken before you can generate value from the data you gather. An important step in that chain of the process is data modeling and transformation.

Big Data 196

Big Data Google Scalability Processing 196

Dynatrace

JANUARY 16, 2023

The study analyzes factual Kubernetes production data from thousands of organizations worldwide that are using the Dynatrace Software Intelligence Platform to keep their Kubernetes clusters secure, healthy, and high performing. Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch.

Open Source 346

Open Source Java Operating System Programming 346

Testsigma

MAY 26, 2021

In today’s world where ‘data is the new oil’ ( as said by Clive Humby), not giving proper attention to data-driven testing is not justified. If you have an application that needs data input in some form then it will require data-driven testing. The data repository could be a CSV file, excel sheet, DB table, etc.

Testing 70

Testing Healthcare Performance Testing Website 70

Uber Engineering

APRIL 5, 2018

Three years ago, Uber Engineering adopted Hadoop as the storage ( HDFS ) and compute ( YARN ) infrastructure for our organization’s big data analysis.

Systems 109

Systems Big Data Storage Infrastructure 109

Dynatrace

DECEMBER 15, 2022

Complex cloud computing environments are increasingly replacing traditional data centers. In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. Collect raw data in virtual and nonvirtual environments from multiple feeds, normalize and structure the data, and aggregate it for alerts.

Artificial Intelligence 207

Artificial Intelligence DevOps Hardware Virtualization 207

Uber Engineering

DECEMBER 10, 2019

Michelangelo , Uber’s machine learning (ML) platform, powers machine learning model training across various use cases at Uber, such as forecasting rider demand , fraud detection , food discovery and recommendation for Uber Eats , and improving the accuracy of … The post Productionizing Distributed XGBoost to Train Deep Tree Models with Large (..)

Engineering 104

Engineering Big Data Architecture 104

The Netflix TechBlog

MARCH 2, 2021

Stephanie Lane , Wenjing Zheng , Mihir Tendulkar Source credit: Netflix Within the rapid expansion of data-related roles in the last decade, the title Data Scientist has emerged as an umbrella term for myriad skills and areas of business focus. Learning through data is in Netflix’s DNA. It can be hard to know from the outside.

Analytics 207

Analytics C++ Innovation Engineering 207

Scalegrid

NOVEMBER 25, 2019

ScyllaDB is an open-source distributed NoSQL data store, reimplemented from the popular Apache Cassandra database. Released just four years ago in 2015, Scylla has averaged over 220% year-over-year growth in popularity according to DB-Engines. So what are some of the reasons why users would pick ScyllaDB vs. Cassandra? Google Cloud.

Big Data 187

Big Data Database Open Source Azure 187

Dynatrace

JULY 6, 2020

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. See the health of your big data resources at a glance. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics.

Azure 149

Azure Cloud Big Data Virtualization 149

The Netflix TechBlog

JUNE 7, 2021

At much less than 1% of CPU and memory on the instance, this highly performant sidecar provides flow data at scale for network insight. Berkeley Packet Filter (BPF) is an in-kernel execution engine that processes a virtual instruction set, and has been extended as eBPF for providing a safe way to extend kernel functionality.

Network 325

Network Transportation AWS Cloud 325

Testsigma

JULY 14, 2020

According to Wikipedia, Data-Driven Testing(DDT) is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded. Database tables.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

Dynatrace

SEPTEMBER 15, 2020

Without automation, Performance engineers and developers can no longer ensure that applications perform as planned, and costs are minimized.”. After every experiment run Akamas changes application, runtime, database or cloud configuration based on monitoring data it captured during the previous experiment run.

Performance 189

Performance Java Metrics Cloud 189

ScaleOut Software

JULY 19, 2021

Incoming data is saved into data storage (historian database or log store) for query by operational managers who must attempt to find the highest priority issues that require their attention. Unlike manual or automatic log queries, in-memory computing can continuously run analytics code on all incoming data and instantly find issues.

IoT 78

IoT Analytics Big Data Architecture 78

Uber Engineering

JUNE 1, 2023

Uber runs more than 100K big data workloads per day using Apache Spark–at that scale it’s crucial to write optimized apps. The Delivery Data Solutions team built Spark Analysers, a real-time system to catch anti-patterns in the Spark application at Uber scale, helping Uber developers optimize their apps.

Big Data 65

Big Data Systems Development 65

All Things Distributed

SEPTEMBER 5, 2013

Over the past few years, two important trends that have been disrupting the database industry are mobile applications and big data. The explosive growth in mobile devices and mobile apps is generating a huge amount of data, which has fueled the demand for big data services and for high scale databases.

Big Data 98

Big Data Mobile Latency Database 98

SQL Server According to Bob

FEBRUARY 15, 2018

Microsoft engineering is actually sending quite a few folks over the Atlantic to come talk about SQL Server 2017, SQL Server on Linux, GDPR, Performance, Security, Azure Data Lake, Azure SQL Database, Azure SQL Data Warehouse, and Azure CosmosDB. Best practices on Building a Big Data Analytics Solution – Michael Rys.

Engineering 40

Engineering Azure Best Practices Servers 40

High Scalability

APRIL 14, 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! Triplebyte is unique because they're a team of engineers running their own centralized technical assessment.

Education 105

Education Software Engineering Scalability Engineering 105

Dynatrace

MARCH 14, 2022

Over the past decade, the industry moved from paper-based to electronic health records (EHRs)—digitizing the backbone of patient data. They need automated approaches based on real-time, contextualized data. But the push toward digital experiences was thriving long before the advent of the pandemic. Emerging security threats.

Healthcare 231

Healthcare Artificial Intelligence Innovation Strategy 231