The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., Seer is also tested on a 100-server GCE cluster with the Social Network microservices application. ASPLOS’19. This was deployed for a two-month period and had 582 registered users with 165 daily actives.

Big Data 45

Big Data Cloud Performance Hardware 45

Testsigma

FEBRUARY 12, 2021

With the latest developments in IT sector services, the sector of QA testing has seen significant improvement and growth. The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. Many changes are rendered through automated testing. IoT Test Automation.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

Testsigma

MAY 14, 2021

Cloud-based testing has become quite integral these days. Most businesses have already done the shift towards cloud-based testing. The traditional testing that was done on the software installed on local servers is now slowly fading away. Cloud-based testing comprises cloud-based test automation as well.

Cloud 67

Cloud Testing Testing Tools Internet 67

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. But before that new code can be deployed, it needs to be tested and reviewed from a security perspective. Taking AIOps to the next level.

DevOps 205

DevOps Artificial Intelligence Healthcare Innovation 205

Testsigma

MAY 26, 2021

In today’s world where ‘data is the new oil’ ( as said by Clive Humby), not giving proper attention to data-driven testing is not justified. If you have an application that needs data input in some form then it will require data-driven testing. Scenario 1: Tabular data . Scenario 2: Data Arrays.

Testing 70

Testing Healthcare Performance Testing Website 70

Dynatrace

MARCH 14, 2022

As patient care continues to evolve, IT teams have accelerated this shift from legacy, on-premises systems to cloud technology to more build, test, and deploy software, and fuel healthcare innovation. Amid so much change, teams can no longer rely on time-consuming, manual approaches for building, testing, operating, and upgrading software.

Healthcare 234

Healthcare Artificial Intelligence Innovation Strategy 234

The Netflix TechBlog

SEPTEMBER 18, 2020

I bring my breadth of big data tools and technologies while Julie has been building statistical models for the past decade. They are continuously innovating compression algorithms to efficiently send high quality audio and video files to our customers over the internet. Is the benefit uniform, or do certain cohorts of members?—?such

Analytics 223

Analytics Education Innovation Engineering 223

Testsigma

JULY 14, 2020

According to Wikipedia, Data-Driven Testing(DDT) is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

The Netflix TechBlog

APRIL 29, 2019

Demand Engineering Demand Engineering is responsible for Regional Failovers , Traffic Distribution, Capacity Operations and Fleet Efficiency of the Netflix cloud. Orchestration The Big Data Orchestration team is responsible for providing all of the services and tooling to schedule and execute ETL and Adhoc pipelines.

Open Source 279

Open Source Network Infrastructure Big Data 279

The Netflix TechBlog

JUNE 1, 2021

His favorite TV shows: Bojack Horseman , Marco Polo , and The Witcher His favorite movies: Scarface, I Am Legend and The Old Guard Sam, what drew you to data engineering? Many healthcare practitioners had strong hunches and wild theories that were exciting to test against an empirical study. You’re in the right place!

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

The Morning Paper

OCTOBER 26, 2020

On the surface this is a paper about fast data ingestion from high-volume streams, with indexing to support efficient querying. Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. PVLDB’20.

Cloud 104

Cloud Big Data Latency Architecture 104

The Netflix TechBlog

FEBRUARY 16, 2021

Operational Efficiency: The majority of the changes require metadata configuration files and library code changes, usually taking days of testing and service release to adopt the updates. Overall, it simplified SKU selections and increased our testing and product delivery confidence.

Mobile 209

Mobile Engineering Infrastructure Scalability 209

Percona

JANUARY 19, 2023

For instance, in Percona Managed Services , we have many clients with TBs worth of data that are well performant. In this blog post, we will review key topics to consider for managing large datasets more efficiently in MySQL. InnoDB will sort the data in primary key order, and that will serve to reference actual data pages on disk.

Open Source 86

Open Source Storage Database Big Data 86

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

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.” But what is AIOps, exactly? And how can it support your organization? What is AIOps?

Artificial Intelligence 221

Artificial Intelligence DevOps Innovation Metrics 221

The Netflix TechBlog

SEPTEMBER 10, 2019

Toby Mao , Sri Sri Perangur , Colin McFarland Another day, another custom script to analyze an A/B test. You can look at ABlaze (our centralized A/B testing platform) and take a quick look at how it’s performing. At any point a Netflix user is in many different A/B tests orchestrated through ABlaze. Not at Netflix.

Metrics 215

Metrics Architecture Infrastructure Innovation 215

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.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Hardware 97

Hardware Storage Big Data Blockchain 97

The Netflix TechBlog

MARCH 2, 2021

Learning through data is in Netflix’s DNA. We use A/B tests to introduce new product features, such as our daily Top 10 row that help our members discover their next favorite show. I was doing data science without realizing it. Data scientists can take on any aspect of an experimentation project.

Analytics 207

Analytics C++ Innovation Engineering 207

All Things Distributed

DECEMBER 20, 2017

Take the example of industrial manufacturing: in prototyping, drafts for technologically complex products are no longer physically produced; rather, their characteristics can be tested in a purely virtual fashion at every location across the globe by using simulations. The German startup SimScale makes use of this trend.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

All Things Distributed

DECEMBER 12, 2018

Winning in this race requires that we become much more customer oriented, much more efficient in all of our operations, and at the same time shift our culture towards more lean and experimental. The first platform is a real time, big data platform being used for analyzing traffic usage patterns to identify congestion and connectivity issues.

AWS 124

AWS Cloud Games Serverless 124

Highly Scalable

MAY 1, 2012

On the other hand, when one is interested only in simple additive metrics like total page views or average price of conversion, it is obvious that raw data can be efficiently summarized, for example, on a daily basis or using simple in-stream counters. what is the cardinality of the data set)? bits per unique value. Case Study.

Analytics 191

Analytics Traffic Big Data Efficiency 191

Highly Scalable

MARCH 1, 2012

Of course, Atomic Aggregates as a data modeling technique is not a complete transactional solution, but if the store provides certain guaranties of atomicity, locks, or test-and-set instructions then Atomic Aggregates can be applicable. cannot be handled efficiently using an inverted index if the number of categories is big.

Database 279

Database Ecommerce Efficiency Engineering 279

Highly Scalable

JUNE 5, 2012

In this article I describe several useful techniques that are based on SSE instructions and provide results of performance testing for Lucene, Java, and C implementations. When this short mask of common elements is obtained, we have to efficiently copy out common elements. in this article. and gcc 4.5.2 with -O3 option) were used.

C++ 102

C++ Java Performance Testing Efficiency 102

KeyCDN

OCTOBER 2, 2018

If you frequently rely on Pens to test ideas, this blog is a must-read for its highlights of new functionalities. It’s awesome for discovering how grid systems, CSS animation, Big Data, etc all play roles in real-world web design. Visit website 10. Visit website 12. Visit website 14. Visit website 22.

Development 75

Development Website Design Code 75

Highly Scalable

JANUARY 31, 2012

Each Mapper runs simulation for specified amount of data which is 1/Nth of the required sampling and emit error rate. Applications: Physical and Engineering Simulations, Numerical Analysis, Performance Testing. In other words, it can be more efficient to sort data once during insertion than sort them for each MapReduce query.

C++ 144

C++ Network Ecommerce Processing 144

Highly Scalable

MARCH 10, 2015

user behavior cannot be precisely predicted) or because it’s impossible to extrapolate the existing data to the case of interest (e.g. A/B testing and panel surveys are used in such cases to get additional data points that improve the precision of the model. the action is to introduce a completely new service).

Retail 152

Retail C++ Analytics Metrics 152

Smashing Magazine

JULY 29, 2019

Read “ Efficiently load JavaScript with defer and async ” for more information. In Amazon’s case, there is room to make some big data savings on the desktop site and we shouldn’t get complacent just because the screen size suggests I’m not on a mobile device. MB of data. This makes the script completely non-blocking.

Cache 96

Cache Google Mobile Network 96