The Netflix TechBlog

JULY 15, 2021

In this post, Kevin talks about his extensive experience in content analytics at Netflix since joining more than 10 years ago. Before joining Netflix, he worked at MySpace, helping implement page categorization, pathing analysis, sessionization, and more. Kevin, what drew you to data engineering? What drew you to Netflix?

Data Engineering 189

Data Engineering Engineering Entertainment Big Data 189

Scalegrid

FEBRUARY 8, 2024

These elements work together to spread data over several locations physically distributed, possibly extending across different data centers while optimizing available storage resources. This process effectively duplicates essential parts of information to safeguard against potential loss.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

JULY 5, 2022

AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. To achieve these AIOps benefits, comprehensive AIOps tools incorporate four key stages of data processing: Collection. Aggregation.

Artificial Intelligence 286

Artificial Intelligence Cloud Innovation Strategy 286

Dynatrace

OCTOBER 25, 2022

NoOps is a concept in software development that seeks to automate processes and eliminate the need for an extensive IT operations team. But it might also result in the entire software development process falling apart. Can organizations really function without an operations team? What is NoOps? Evolution of NoOps.

DevOps 217

DevOps Big Data Cloud Innovation 217

Dynatrace

JULY 6, 2022

At its most basic, automating IT processes works by executing scripts or procedures either on a schedule or in response to particular events, such as checking a file into a code repository. Adding AIOps to automation processes makes the volume of data that applications and multicloud environments generate much less overwhelming.

Artificial Intelligence 188

Artificial Intelligence Tuning Strategy Big Data 188

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., I’ve been excited about the potential for approximate query processing in analytic clusters for some time, and this paper describes its use at scale in production. VLDB’19. Approximate query support.

Big Data 57

Big Data Analytics Latency Azure 57

Dynatrace

DECEMBER 15, 2022

In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. This transition to public, private, and hybrid cloud is driving organizations to automate and virtualize IT operations to lower costs and optimize cloud processes and systems. So, what is ITOps? What is ITOps? ITOps vs. AIOps.

Artificial Intelligence 202

Artificial Intelligence DevOps Hardware Virtualization 202

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. CloudOps includes processes such as incident management and event management. The four stages of data processing. Analyze the data.

DevOps 196

DevOps Artificial Intelligence Healthcare Innovation 196

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

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 21, 2021

On the Dynatrace Business Insights team, we have developed analytical views and an approach to help you get started. To do this effectively, you need a big data processing approach. Core Web Vitals metrics introduced in additional standard Business Insights views to enhance our reporting and analysis. Tell me more!

Traffic 263

Traffic Metrics Mobile Analytics 263

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 189

Big Data Google Scalability Processing 189

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 212

Artificial Intelligence DevOps Innovation Metrics 212

The Netflix TechBlog

JUNE 7, 2021

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. The data is also used by security and other partner teams for insight and incident analysis. What is BPF?

Network 325

Network Transportation AWS Cloud 325

Dynatrace

APRIL 11, 2023

Dynatrace Runtime Vulnerability Analysis now covers the entire application stack – blog Automatic vulnerability detection at runtime and AI-powered risk assessment further enable DevSecOps automation. When DevOps teams move these tasks earlier in the development process, it can aid in finding software flaws before they enter production.

Cloud 186

Cloud DevOps Open Source Retail 186

The Netflix TechBlog

MARCH 2, 2021

At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group.

Analytics 207

Analytics C++ Innovation Engineering 207

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

ScaleOut Software

NOVEMBER 24, 2020

The volume of incoming telemetry challenges current telematics systems to keep up and quickly make sense of all the data. At the same time, telemetry snapshots are stored in a data lake, such as HDFS , for offline batch analysis and visualization using big data tools like Spark.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Testsigma

SEPTEMBER 8, 2021

If I consider current times, it has become a core concept in development, management, analytics, and also – automation testing. In-depth reporting : Testsigma’s reports are of extremely high quality and have been appreciated for the analytical information displayed in them. Cloud-based automation testing is a simple concept.

Cloud 76

Cloud Testing AWS Testing Tools 76

ScaleOut Software

APRIL 3, 2020

This software can simultaneously perform these actions for hundreds of thousands of ventilators to keep this vital logistical information instantly available for real-time analysis. These questions can be answered using the latest data as it streams in from the field.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

This software can simultaneously perform these actions for hundreds of thousands of ventilators to keep this vital logistical information instantly available for real-time analysis. These questions can be answered using the latest data as it streams in from the field.

Logistics 52

Logistics Analytics Scalability Cloud 52

All Things Distributed

DECEMBER 20, 2017

The benefit for customers: Authorized users can view this data and therefore manage their inventories across different sites, making the maintenance processes much more efficient. By knowing this, Kärcher can generate new top-line revenue in the form of subscription models for its analysis portal. More than mere support.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

The Morning Paper

SEPTEMBER 19, 2019

It handles an order of magnitude more throughput than a prototype built on a stream processing engine. Could it be Analyzing efficient stream processing on modern hardware ? .” Crusher is a Google system for automatically discovering email templates (e.g. for machine generated emails sent to humans). What’s their secret???

Blockchain 46

Blockchain Hardware Google Analytics 46

Percona

JANUARY 14, 2019

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. This information can be a mix of analytical (OLAP) queries (i.e. Analytical databases are optimized for a low number of slow queries.

Database 40

Database Analytics Blockchain Healthcare 40

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. In that case, the equation (1.2)

Retail 152

Retail C++ Analytics Metrics 152

Testsigma

MAY 7, 2020

IBM Big Data and Analytics Hub website cited a case study, where a US insurance company was estimating 15% of their testing efforts to be just test data collection for the backend system and the frontend system. The test data management for the company had become a big problem and had to be solved.

Testing 60

Testing Storage Database Processing 60

The Netflix TechBlog

JULY 26, 2021

Operational Reporting is a reporting paradigm specialized in covering high-resolution, low-latency data sets, serving detailed day-to-day activities¹ and processes of a business domain. At Netflix Studio, teams build various views of business data to provide visibility for day-to-day decision making. tactical) in nature.

Big Data 253

Big Data Government Analytics Processing 253

All Things Distributed

JULY 11, 2011

Spot Instances are ideal for use cases like web and data crawling, financial analysis, grid computing, media transcoding, scientific research, and batch processing. Driving down the cost of Big-Data analytics. Introducing the AWS South America (Sao Paulo) Region. No Server Required - Jekyll & Amazon S3.

AWS 85

AWS Storage Cloud Big Data 85

All Things Distributed

OCTOBER 7, 2015

In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data. However, the data infrastructure to collect, store and process data is geared toward developers (e.g.,

Cloud 137

Cloud Big Data AWS Analytics 137

All Things Distributed

DECEMBER 13, 2016

With the launch of the AWS Europe (London) Region, AWS can enable many more UK enterprise, public sector and startup customers to reduce IT costs, address data locality needs, and embark on rapid transformations in critical new areas, such as big data analysis and Internet of Things.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

Smashing Magazine

JULY 29, 2019

It was at this point I accidentally clicked on an ‘Explanation’ URL in the devtools, which took me to the network analysis reference , costing me about 5 MB of my budget. The weightiest of these was 186 KB, which isn’t particularly big — there were just so many of them, and they all downloaded at once. MB of data.

Cache 96

Cache Google Mobile Network 96

All Things Distributed

NOVEMBER 15, 2010

From financial processing and traditional oil & gas exploration HPC applications to integrating complex 3D graphics into online and mobile applications, the applications of GPU processing appear to be limitless. Because of its focus on latency, the generic CPU yielded rather inefficient system for graphics processing.

AWS 136

AWS Latency Programming Architecture 136

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

All Things Distributed

NOVEMBER 30, 2016

There are many more application areas where we use ML extensively: search, autonomous drones, robotics in fulfillment centers, text processing and speech recognition (such as in Alexa) etc. And this process must be repeated for every object, face, voice, and language feature in an application. Amazon Lex.

AWS 165

AWS Lambda Artificial Intelligence Mobile 165