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 257

Big Data Government Processing Analytics 257

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 252

Latency Storage Big Data Tuning 252

Dynatrace

APRIL 20, 2023

Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. At Dynatrace Perform 2023 , Maciej Pawlowski, senior director of product management for infrastructure monitoring at Dynatrace, and a senior software engineer at a U.K.-based

Analytics 246

Analytics Infrastructure Storage Architecture 246

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

The Netflix TechBlog

OCTOBER 28, 2021

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer on the Product Data Science and Engineering team.

Data Engineering 181

Data Engineering Engineering Big Data Software Engineering 181

Dynatrace

FEBRUARY 16, 2023

How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 246

Analytics Innovation Metrics Database 246

Dynatrace

JANUARY 11, 2023

With more organizations taking the multicloud plunge, monitoring cloud infrastructure is critical to ensure all components of the cloud computing stack are available, high-performing, and secure. Cloud monitoring is a set of solutions and practices used to observe, measure, analyze, and manage the health of cloud-based IT infrastructure.

Cloud 295

Cloud Monitoring Best Practices Infrastructure 295

Dynatrace

AUGUST 10, 2021

This year’s conference agenda was packed full of choices, including: Keynotes : Topics included accelerating digital transformation, with Dynatrace CIO Mike Maciag, and Spatial Collapse: The Great Acceleration of Turning Data Into an Asset, with Tricia Wang from Sudden Compass. We’ve all heard it: data is one of your biggest assets.

DevOps 246

DevOps Innovation Big Data Cloud 246

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. Kubernetes infrastructure models differ between cloud and on-premises. Kubernetes moved to the cloud in 2022.

Open Source 358

Open Source Java Operating System Programming 358

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 246

Software Software Analytics Big Data 246

The Netflix TechBlog

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 212

Storage Latency Efficiency Data Engineering 212

The Netflix TechBlog

APRIL 29, 2019

An easy, though imprecise, way of thinking about Netflix infrastructure is that everything that happens before you press Play on your remote control (e.g., Various software systems are needed to design, build, and operate this CDN infrastructure, and a significant number of them are written in Python. are you logged in?

Open Source 280

Open Source Network Infrastructure Big Data 280

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. Challenges The cloud network infrastructure that Netflix utilizes today consists of AWS services such as VPC, DirectConnect, VPC Peering, Transit Gateways, NAT Gateways, etc and Netflix owned devices.

Network 327

Network Transportation AWS Cloud 327

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

Dynatrace

OCTOBER 4, 2022

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Several pain points have made it difficult for organizations to manage their data efficiently and create actual value.

Analytics 264

Analytics Artificial Intelligence Storage Serverless 264

Dynatrace

OCTOBER 25, 2022

DevOps requires infrastructure experts and software experts to work hand in hand. Thus, NoOps became a loosely defined concept that initially proposed only leveraging cloud-based PaaS and IaaS solutions that freed up operations from provisioning infrastructure and deploying applications. Introduction of AIOps.

DevOps 246

DevOps Big Data Cloud Innovation 246

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. ITOps teams are responsible for establishing, maintaining, and growing a reliable, high-performing, and secure IT infrastructure.

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

Dynatrace

MARCH 24, 2023

Containers enable developers to package microservices or applications with the libraries, configuration files, and dependencies needed to run on any infrastructure, regardless of the target system environment. And organizations use Kubernetes to run on an increasing array of workloads.

Infrastructure 246

Infrastructure Open Source Operating System Cloud 246

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 325

Artificial Intelligence Cloud Innovation Strategy 325

O'Reilly

SEPTEMBER 19, 2023

” I’ve called out the data field’s rebranding efforts before; but even then, I acknowledged that these weren’t just new coats of paint. Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” Goodbye, Hadoop.

Hardware 135

Hardware Storage Big Data Blockchain 135

Dynatrace

APRIL 19, 2023

At Dynatrace Perform 2023 , Ben Rushlo, Business Insights leader at Dynatrace, and Navid Mehdiabadi, BCLC’s APM expert, discuss how the right business insights are crucial to making data-driven decisions and improving business outcomes. “It’s a journey in Dynatrace,” Rushlo said. “Our players just see the frontend.

Entertainment 237

Entertainment Analytics Healthcare Games 237

Dynatrace

JUNE 1, 2020

There are many different types of monitoring from APM to Infrastructure Monitoring, Network Monitoring, Database Monitoring, Log Monitoring, Container Monitoring, Cloud Monitoring, Synthetic Monitoring, and End User monitoring. From APM to full-stack monitoring. This is something Dynatrace offers users to make sure monitoring is made easy.

Artificial Intelligence 254

Artificial Intelligence Social Media Monitoring IoT 254

Dynatrace

APRIL 11, 2023

Log4Shell required many organizations to take devices and applications offline to prevent malicious attackers from gaining access to IT systems and sensitive data. As a result, organizations need to be vigilant in identifying and addressing vulnerabilities to protect their systems and data.

Cloud 246

Cloud DevOps Open Source Retail 246

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 154

Network Tuning AWS Traffic 154

DZone

AUGUST 23, 2023

In the era of big data, efficient data management and query performance are critical for organizations that want to get the best operational performance from their data investments.

Big Data 130

Big Data Analytics Innovation Scalability 130

The Netflix TechBlog

FEBRUARY 16, 2021

This critical insight helped us re-envision the SKU catalog as a seamless, scalable platform that empowers our stakeholders to make rapid changes with confidence while the platform ensures suitable guardrails for data accuracy and integrity. SKUDB: SKU catalog data was migrated from the metadata configuration files to a relational database.

Mobile 218

Mobile Engineering Infrastructure Scalability 218

All Things Distributed

DECEMBER 13, 2016

In November 2015, Amazon Web Services announced that it would launch a new AWS infrastructure region in the United Kingdom. Today, I'm happy to announce that the AWS Europe (London) Region, our 16th technology infrastructure region globally, is now generally available for use by customers worldwide.

AWS 154

AWS Cloud Artificial Intelligence IoT 154

All Things Distributed

NOVEMBER 5, 2015

This region will provide even lower latency and strong data sovereignty to local users. We are committed to meeting our customers’ increasing needs for capacity and for powerful AWS services that eliminate the heavy lifting of the underlying IT infrastructure -- allowing them to focus more of their precious resources on their core business.

AWS 167

AWS Retail Entertainment IoT 167

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

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 144

Engineering Big Data Infrastructure Analytics 144

Dynatrace

MARCH 11, 2021

In the fourth part of the series, I’ll show you how I used Dynatrace’s raw problem and event data to find the best fit for optimized anomaly detection settings. I took a big-data-analysis approach, which started with another problem visualization. Statistically analyzing Dynatrace’s event and problem data.

Tuning 264

Tuning Architecture Monitoring Big Data 264

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 246

Healthcare Artificial Intelligence Innovation Strategy 246

Dynatrace

JUNE 1, 2020

There are many different types of monitoring from APM to Infrastructure Monitoring, Network Monitoring, Database Monitoring, Log Monitoring, Container Monitoring, Cloud Monitoring, Synthetic Monitoring and End User monitoring. From APM to full-stack monitoring. This is something Dynatrace offers users, to make sure monitoring is made easy.

Monitoring 173

Monitoring Performance Social Media Artificial Intelligence 173

All Things Distributed

SEPTEMBER 29, 2016

To support our customers’ growth, their digital transformation, and to speed up their innovation and lower the cost of running their IT, we continue to build out additional European infrastructure. By offloading the running of the infrastructure to AWS, today we have customers all over the US, in Asia and also in Europe.

AWS 158

AWS IoT Internet Internet 158

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.” training data) that the algorithm can then learn from. Traditional AIOps solutions are built for vendor-agnostic data ingestion.

Artificial Intelligence 246

Artificial Intelligence DevOps Innovation Metrics 246

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 216

Analytics C++ Innovation Engineering 216

All Things Distributed

OCTOBER 7, 2015

We live in a world where massive volumes of data are generated from websites, connected devices and mobile apps. 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.

Cloud 112

Cloud Big Data AWS Analytics 112