The Netflix TechBlog

OCTOBER 28, 2021

Netflix’s unique work culture and petabyte-scale data problems are what drew me to Netflix. During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics.

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

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. The most notable example is memory configuration errors. the retry success probability) and compute cost efficiency (i.e.,

Tuning 210

Tuning Efficiency Big Data Engineering 210

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., ASPLOS’19. It then provides the cluster manager with recommendations on how to avoid the performance degradation altogether.

Big Data 45

Big Data Cloud Performance Hardware 45

Scalegrid

MAY 13, 2020

When handling large amounts of complex data, or big data, chances are that your main machine might start getting crushed by all of the data it has to process in order to produce your analytics results. Greenplum features a cost-based query optimizer for large-scale, big data workloads. Query Optimization.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

JULY 6, 2022

Vulnerability management is one example of a DevSecOps workflow that teams should automate to ensure vulnerability scans run regularly. This kind of automation can support key IT operations, such as infrastructure, digital processes, business processes, and big-data automation. Big data automation tools.

Artificial Intelligence 182

Artificial Intelligence Tuning Strategy Big Data 182

The Netflix TechBlog

JUNE 1, 2021

For example?—?clinical clinical data was often small enough to fit into memory on an average computer and only in rare cases would its computation require any technical ingenuity or massive computing power. However, most challenges that came with my role were domain-related but not as technically demanding.

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

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. Let’s look at the Azure DB for MariaDB overview as an example. See the health of your big data resources at a glance. Azure Virtual Network Gateways.

Azure 145

Azure Cloud Big Data Virtualization 145

ScaleOut Software

JULY 19, 2021

This architecture does not apply computing resources to track the myriad data sources sending telemetry and continuously look for issues and opportunities that need immediate responses.

IoT 78

IoT Analytics Big Data Architecture 78

DZone

MAY 21, 2019

The demand for more IT resource-intensive applications has significantly increased today, whether it is to process quicker transactions, gain real-time insight, crunch big data sets, or to meet customer expectations. That’s because NVMe provides 6x higher bandwidth and IOPS advantage compared to SAS/SATA SSD.

Performance 100

Performance Big Data Storage Processing 100

The Netflix TechBlog

MAY 4, 2023

For example, if some fields in the responses are timestamps, those will differ. Additionally, for mismatches, we record the normalized and unnormalized responses from both sides to another big data table along with other relevant parameters, such as the diff. We will look at one of them in the follow-up blog post in this series.

Traffic 339

Traffic Latency Tuning Systems 339

Dynatrace

SEPTEMBER 15, 2020

Supported technologies include cloud services, big data, databases, OS, containers, and application runtimes like the JVM. For example, the jvm_gcType parameter already contains the list of GC types that are allowed in OpenJDK 11. Q3: Is Akamas a SaaS offering or on-premise?

Performance 180

Performance Java Metrics Cloud 180

Dynatrace

APRIL 11, 2023

For example, the open source Java library at the heart of the Log4Shell crisis in 2021 was patched within days given the pervasiveness of the code. For example, in a recent study , 55% of security teams say they don’t trust developers, and 49% of developers perceive security teams as a blocker to innovation.

Cloud 180

Cloud DevOps Open Source Retail 180

Percona

JANUARY 19, 2023

However, there are cases where the same column is defined on multiple indexes in order to serve different query patterns, and sometimes some of the indexes created for the same column are redundant, leading to more overhead when inserting or deleting data (as indexes are updated) and increased disk space for storing the indexes for the table.

Open Source 89

Open Source Storage Database Big Data 89

All Things Distributed

NOVEMBER 5, 2015

Here are some examples of how our UK customers are using the AWS platform: Hot Startups – Shazam , Hailo , Omnifone , Yplan , SwiftKey , Aire , GoSquared.

AWS 167

AWS Retail Entertainment IoT 167

All Things Distributed

JUNE 26, 2016

Here are the benefits of a comprehensive platform, with customer examples: A connected platform to sense the business environment. Examples of continuous sensing are found in the managed cloud platform built by Rachio on AWS IoT to enable the secure interaction of its connected devices with cloud applications/other devices.

AWS 90

AWS Cloud Healthcare Blockchain 90

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

Testsigma

MAY 26, 2021

The test results are a huge set of data and they need to be matched against the expected results, which are again stored in files. . Let us see a few scenarios where data-driven testing is useful in providing a quality product. Scenario 1: Tabular data . Scenario 2: Data Arrays. Example: E-commerce applications.

Testing 70

Testing Healthcare Performance Testing Website 70

All Things Distributed

JANUARY 6, 2016

For example, Samsung Electronic Printing used AWS to deploy its Printing Apps Center in a way that didn’t require them to invest up-front capital and kept total costs quite low. We’ve also been hearing many requests from Korean companies, including large enterprises like Samsung and Mirae Asset.

AWS 110

AWS Cloud Games Latency 110

All Things Distributed

DECEMBER 20, 2017

In today's era of global digitalization there are many examples that show that IT does matter. 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. More than mere support.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

All Things Distributed

AUGUST 16, 2011

For example a number of our European customers are subject to data residency requirements when it comes to PII data and they use the EU Region to meet to those requirements. Government and Big Data. One particular early use case for AWS GovCloud (US) will be massive data processing and analytics.

AWS 111

AWS Government Big Data Cloud 111

Testsigma

MAY 14, 2021

Examples are Agile testing, TDD, automation testing, regression testing, etc. Examples are DevOps, AWS, Big Data, Testing as Service, testing environments. One example of a cloud-based testing tool is Testsigma which is a SaaS(Software as Service) based unified platform.

Cloud 67

Cloud Testing Testing Tools Internet 67

ScaleOut Software

JUNE 15, 2020

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

The Netflix TechBlog

OCTOBER 15, 2019

For example, XA transactions block execution if the application process fails during the prepare phase; moreover, XA provides no deadlock detection and no support for optimistic concurrency-control schemes. The tradeoff is potential broker data inconsistencies in various edge scenarios.

Transportation 192

Transportation Architecture Processing Storage 192

ScaleOut Software

APRIL 3, 2020

For example, the parameters for a ventilator could include its identifier, make and model, current location, status (in use, in storage, broken), time in use, technical issues and repairs, and contact information. Consider a simple example in which a message arrives signaling that a ventilator has been activated for a patient.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

For example, the parameters for a ventilator could include its identifier, make and model, current location, status (in use, in storage, broken), time in use, technical issues and repairs, and contact information. Consider a simple example in which a message arrives signaling that a ventilator has been activated for a patient.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

JUNE 15, 2020

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

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. Progressive Web App Dev by Example. Inclusive Components. Using Webpagetest. Progressive Web Apps Dean.

Performance 75

Performance Social Media Website Website Performance 75

Rigor

MAY 22, 2019

Big data is like the pollution of the information age. The Big Data Struggle and Performance Reporting. As the big data era brings in multiple options for visualization, it has become apparent that not all solutions are created equal. Conclusion.

Big Data 76

Big Data Monitoring Performance Metrics 76

Scalegrid

FEBRUARY 8, 2024

Within Amazon S3’s offerings are features like metadata tagging, different classes of data movement and storage options, configuring control over access permissions, and ensuring safety against disasters through data replication mechanisms.

Storage 130

Storage Systems Big Data Azure 130

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. There is a strong argument for ELT i.e. extract, load, and transform model. Classic ETL. Late transformation. Different audience.

Big Data 40

Big Data Retail Storage Google 40

Dynatrace

MAY 1, 2023

IT operations analytics is the process of unifying, storing, and contextually analyzing operational data to understand the health of applications, infrastructure, and environments and streamline everyday operations. ITOA collects operational data to identify patterns and anomalies for faster incident management and near-real-time insights.

Analytics 181

Analytics Artificial Intelligence Big Data Open Source 181

All Things Distributed

SEPTEMBER 6, 2013

Europe is a continent with much diversity and for each country there are great AWS customer examples to tell. Here are some great examples from different industries each with unique use cases. Shell leverages AWS for big data analytics to help achieve these goals.

Cloud 129

Cloud Energy AWS Healthcare 129

All Things Distributed

SEPTEMBER 26, 2014

Topics include Introduction to AWS, Big Data, Compute & Networking, Architecture, Mobile & Gaming, Databases, Operations, Security, and more. For example, join us next week in the Loft for this special event: The Future of IT: Startups at the NASA Jet Propulsion Laboratory. AWS Technical Bootcamps.

AWS 111

AWS Games Education Innovation 111

ScaleOut Software

NOVEMBER 24, 2020

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. It comprises message-processing code and state variables which host dynamically evolving contextual information about the data source.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

All Things Distributed

DECEMBER 8, 2016

Some examples of how current customers use AWS are: Cost-effective solutions. It adopted Amazon Redshift, Amazon EMR and AWS Lambda to power its data warehouse, big data, and data science applications, supporting the development of product features at a fraction of the cost of competing solutions.

AWS 155

AWS Cloud Lambda Innovation 155

DZone

JUNE 3, 2019

Using local SSDs inside of the GPU node delivers fast access to data during training, but introduces challenges that impact the overall solution in terms of scalability, data access, and data protection.

Storage 100

Storage Performance Network Scalability 100

The Netflix TechBlog

JULY 26, 2021

However, the Data Mesh platform team strives to provide and manage the most highly leveraged processors (e.g. We will cover a few core concepts in the Data Mesh Schema domain. Consumer schema Consumer schema defines how data is consumed by the downstream processors. See example below. Two Types of Processors 1.

Big Data 253

Big Data Government Analytics Processing 253