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. As our subscribers grow worldwide and Netflix enters the world of gaming , the number of batch workflows and real-time data pipelines increases rapidly.

Big Data 238

Big Data Infrastructure Metrics Hardware 238

Dynatrace

JUNE 26, 2023

In what follows, we define software automation as well as software analytics and outline their importance. What is software analytics? This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI. We also discuss the role of AI for IT operations (AIOps) and more.

Software 186

Software Software Analytics Big Data 186

Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs.

Big Data 154

Big Data Processing Lambda Database 154

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

Scalegrid

MARCH 14, 2024

Implementing a hybrid cloud solution involves careful decision-making regarding application and data placement, migration strategies, and choosing compatible cloud service providers while ensuring seamless integration and addressing security and compliance challenges. We will examine each of these elements in more detail.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

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. Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the cloud network infrastructure to address the identified problems. What is BPF?

Network 325

Network Transportation AWS Cloud 325

Scalegrid

MARCH 28, 2024

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 130

Cache Storage Scalability Architecture 130

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

Dynatrace

APRIL 11, 2023

Cloud application security remains challenging because organizations lack end-to-end visibility into cloud architecture. As organizations migrate applications to the cloud, they must balance the agility that microservices architecture brings with the complexity and lack of transparency that can also come with it.

Cloud 186

Cloud DevOps Open Source Retail 186

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 188

Artificial Intelligence Tuning Strategy Big Data 188

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 201

Artificial Intelligence DevOps Hardware Virtualization 201

ScaleOut Software

JUNE 15, 2020

thousands of data sources. Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

thousands of data sources. Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

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. The post What is container orchestration? appeared first on Dynatrace news.

Infrastructure 185

Infrastructure Open Source Operating System Cloud 185

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 147

Azure Cloud Big Data Virtualization 147

Dynatrace

OCTOBER 17, 2022

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. The four stages of data processing. There are four stages of data processing: Collect raw data. Analyze the data.

DevOps 195

DevOps Artificial Intelligence Healthcare Innovation 195

ScaleOut Software

NOVEMBER 24, 2020

However, telematics architectures face challenges in responding to telemetry in real time. Current Telematics Architecture. The volume of incoming telemetry challenges current telematics systems to keep up and quickly make sense of all the data. Lastly, all telemetry is archived for future use (not shown here).

Analytics 52

Analytics Architecture Scalability Software Architecture 52

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.” A comprehensive, modern approach to AIOps is a unified platform that encompasses observability, AI, and analytics.

Artificial Intelligence 211

Artificial Intelligence DevOps Innovation Metrics 211

All Things Distributed

DECEMBER 20, 2017

How companies can use ideas from mass production to create business with data. In this way, designers are part of an ecosystem in which the functionalities of simulations, data and people come together, enabling them to develop better products faster. Value creation through data. Strategically, IT doesn't matter.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

Highly Scalable

MARCH 10, 2015

Retail is one of the most important business domains for data science and data mining applications because of its prolific data and numerous optimization problems such as optimal prices, discounts, recommendations, and stock levels that can be solved using data analysis methods.

Retail 152

Retail C++ Analytics Metrics 152

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

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. With the latest Data Mesh Platform, data movement in Netflix Studio reaches a new stage.

Big Data 253

Big Data Government Analytics Processing 253

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

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

ScaleOut Software

APRIL 3, 2020

These questions can be answered using the latest data as it streams in from the field. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins. What gives real-time digital twins their agility compared to complex, enterprise-based data management systems is their simplicity.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

These questions can be answered using the latest data as it streams in from the field. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins. What gives real-time digital twins their agility compared to complex, enterprise-based data management systems is their simplicity.

Logistics 52

Logistics Analytics Scalability Cloud 52

All Things Distributed

SEPTEMBER 6, 2013

These sensors create massive amounts of geological data. Shell leverages AWS for big data analytics to help achieve these goals. In addition, its robust architecture supports ten times as many scientists, all working simultaneously.

Cloud 129

Cloud Energy AWS Healthcare 129

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 Daybook-Volume-2. Building Progressive Apps. Mobile First. Speed Up Your Site.

Performance 75

Performance Social Media Website Website Performance 75

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

All Things Distributed

AUGUST 19, 2011

This team is constantly rethinking the assumptions behind how traditional databases were built and constantly working on building the right database architectures suited for the Cloud environment. Driving down the cost of Big-Data analytics. Introducing the AWS South America (Sao Paulo) Region.

AWS 75

AWS Database Storage Scalability 75

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

All Things Distributed

NOVEMBER 19, 2010

Understanding Throughput-Oriented Architectures - background article in CACM on massively parallel and throughput vs latency oriented architectures. The Big Idea: Biomimetic Architecture - The National Geographic came in the mail this week with a beautiful pull-out of Gaudís Sagrada Família, the online version is only a summary.

AWS 67

AWS Cloud Benchmarking Storage 67

All Things Distributed

SEPTEMBER 30, 2010

Visiting future customers is equally exiting as you get a change to understand their current architecture, if it is a migration, and how they plan to exploit cloud services in their new setup. Driving down the cost of Big-Data analytics. Introducing the AWS South America (Sao Paulo) Region.

AWS 75

AWS Storage Cloud Best Practices 75

All Things Distributed

JULY 13, 2010

Further computationally intensive, highly parallel workloads have found their way to Amazon EC2 as businesses have explored using HPC types of algorithms for other application categories, for example to to process very large unstructured data sets for Business Intelligence applications. Driving down the cost of Big-Data analytics.

Cloud 118

Cloud AWS Automotive Latency 118

The Netflix TechBlog

MAY 26, 2020

Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the Cloud Network Infrastructure to address the identified problems. At Netflix we publish the Flow Log data to Amazon S3. And in order to gain visibility into these logs, we need to somehow ingest and enrich this data.

Network 150

Network Tuning AWS Big Data 150

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

All Things Distributed

DECEMBER 5, 2010

While registrars manage the namespace in the DNS naming architecture, DNS servers are used to provide the mapping between names and the addresses used to identify an access point. Driving down the cost of Big-Data analytics. There are two main types of DNS servers: authoritative servers and caching resolvers.

Cloud 117

Cloud Internet Internet AWS 117