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. For example, consider the adoption of a multicloud framework that enables companies to use best-fit clouds for important operational tasks.

Artificial Intelligence 285

Artificial Intelligence Cloud Innovation Strategy 285

The Netflix TechBlog

MAY 4, 2023

This blog series will examine the tools, techniques, and strategies we have utilized to achieve this goal. In this testing strategy, we execute a copy (replay) of production traffic against a system’s existing and new versions to perform relevant validations. This approach has a handful of benefits.

Traffic 339

Traffic Latency Tuning Systems 339

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. Let’s say, for example, an application is experiencing a slowdown in receiving its search requests. Deterministic AI.

DevOps 196

DevOps Artificial Intelligence Healthcare Innovation 196

Dynatrace

JULY 6, 2020

As adoption rates for Microsoft Azure continue to skyrocket, Dynatrace is developing a deeper integration with the platform to provide even more value to organizations that run their businesses on Azure or use it as a part of their multi-cloud strategy. Let’s look at the Azure DB for MariaDB overview as an example.

Azure 147

Azure Cloud Big Data Virtualization 147

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 186

Cloud DevOps Open Source Retail 186

Testsigma

MAY 14, 2021

Is there a possibility that moving testing to the cloud may lead to a change in the test strategy or foundation of testing? Process: Chalking out the strategy to make a move to cloud-based testing. Examples are Agile testing, TDD, automation testing, regression testing, etc. Do we need to learn new skills?

Cloud 67

Cloud Testing Testing Tools Internet 67

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. The US Federal Cloud Computing Strategy lays out a â??Cloud Government and Big Data. Cloud First. Cloud Firstâ?? With AWSâ??s

AWS 111

AWS Government Big Data Cloud 111

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. This book shares guidelines and innovative techniques that will help you plan and execute a comprehensive SEO strategy.

Performance 75

Performance Social Media Website Website Performance 75

Testsigma

SEPTEMBER 8, 2021

This is just a small example that we all can relate to and understand the cloud. Dynamic locator strategy : Cloud automation testing in Testsigma comes with a dynamic locator strategy that helps in creating stable and reliable test cases. In IT, however, the cloud means a lot more than just streaming media on the system.

Cloud 76

Cloud Testing AWS Testing Tools 76

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.

Big Data 40

Big Data Retail Storage Google 40

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

ACM Sigarch

APRIL 8, 2019

big-data processing, machine learning, quantum computing, and so on). For example, the existence and support of open-source frameworks such as LLVM or Tensorflow/Pytorch are an attractive element to many newcomers. This post reflects their own opinions and does not represent Google’s or Baidu’s positions, strategies or opinions.

Architecture 74

Architecture Open Source Hardware Software Engineering 74

All Things Distributed

JUNE 29, 2011

For example, when our retail customers contributed to create larger economies of scale for Amazon.com, we used the savings to lower pricing such that our customers could also benefit. Often customers are surprised about our strategy to help them drive their costs down. Driving down the cost of Big-Data analytics.

AWS 104

AWS Retail Innovation Strategy 104

O'Reilly

JANUARY 13, 2020

Will the incremental strategy of delivering pattern matching and algebraic data types ( Project Amber ) pay off? Swift for TensorFlow also brings full Python support to Swift, allowing data scientists to mix and match the useful and familiar Python frameworks they need, with clean expressive Swift code. ” What lies ahead?

Programming 130

Programming Java Google C++ 130

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

The Netflix TechBlog

JULY 21, 2022

We at Netflix, as a streaming service running on millions of devices, have a tremendous amount of data about device capabilities/characteristics and runtime data in our big data platform. With large data, comes the opportunity to leverage the data for predictive and classification based analysis.

Big Data 179

Big Data Cache Engineering Data Engineering 179

Highly Scalable

MARCH 10, 2015

In this article we are trying to take a more rigorous approach and provide a systematic view of econometric models and objective functions that can leverage data analysis to make more automated decisions. The goals above can be achieved by means of dimensionality reduction because of correlations in the original data representation R.

Retail 152

Retail C++ Analytics Metrics 152

The Netflix TechBlog

NOVEMBER 20, 2023

To compensate for that, ETL workflows often use a lookback window, based on which they reprocess the data in that certain time window. For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing.

Processing 210

Processing Big Data Efficiency Engineering 210

The Netflix TechBlog

FEBRUARY 16, 2021

As we expand offerings rapidly across the globe, our ideas and strategies around plans and offers are evolving as well. For example, the mobile plan launch in India and Southeast Asia was a huge success. For the longest time, Netflix had three plans (basic/standard/premium) with a single 30-day free trial offer at signup.

Mobile 209

Mobile Engineering Infrastructure Scalability 209

All Things Distributed

OCTOBER 7, 2015

Today, I am excited to share with you a brand new service called Amazon QuickSight that aims to simplify the process of deriving insights from a wide variety of data sources in a fast and affordable manner. Big data challenges. We believe this is one of the critical parts of our big data offerings.

Cloud 137

Cloud Big Data AWS Analytics 137

Smashing Magazine

JULY 29, 2019

This metric is a little difficult to comprehend, so here’s an example: if the average cost of broadband packages in a country is $22, and the average download speed offered by the packages is 10 Mbps, then the cost ‘per megabit per month’ would be $2.20. For example, HTML5 form validation ). Is the convenience worth the weight?

Cache 97

Cache Google Mobile Network 97

O'Reilly

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” Isn’t it nice to uncover that in a simulated environment, where we can map out our risk mitigation strategies with calm, level heads? The NASA ST5 antenna is another example.

Hardware 98

Hardware Storage Big Data Blockchain 98

The Netflix TechBlog

DECEMBER 21, 2020

Design Principles For AutoOptimize to efficiently optimize the data layout, we’ve made the following choices: Just in time vs. periodic optimization Only optimize a given data set when required (based on what changed) instead of blind periodic runs.

Storage 203

Storage Latency Efficiency Data Engineering 203

Smashing Magazine

AUGUST 9, 2021

Refactoring CSS: Strategy, Regression Testing And Maintenance written by Adrian Bece. She is the Principal Designer at 8th Light, where she designs and builds custom software and consults on safe and inclusive design strategy. The Inclusive Safety Project. Eva on Twitter. Eva’s personal site. Weekly Update. There’s no alert.

Design 99

Design Education Network Google 99