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. For testing purposes, usually, a mix of static and dynamic data is needed. Copy production data i.

Testing 60

Testing Storage Database Processing 60

All Things Distributed

JUNE 29, 2011

AWS also applies the same customer oriented pricing strategy: as the AWS platform grows, our scale enables us to operate more efficiently, and we choose to pass the benefits back to customers in the form of cost savings. a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. Expanding the Cloud â??

AWS 106

AWS Retail Innovation Strategy 106

KeyCDN

OCTOBER 2, 2018

Codrops Codrops features blogs with topics ranging from UI design and page animations to image formatting and general JavaScript practices. A List Apart A List Apart focuses on UX and branding from business and design-oriented perspectives. Topics include web design, security, web-based tools and workflows and more.

Development 75

Development Website Design Code 75

Scalegrid

MARCH 14, 2024

In practice, a hybrid cloud operates by melding resources and services from multiple computing environments, which necessitates effective coordination, orchestration, and integration to work efficiently. Tailoring resource allocation efficiently ensures faster application performance in alignment with organizational demands.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

The Netflix TechBlog

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

The Netflix TechBlog

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Storage 203

Storage Latency Efficiency Data Engineering 203

The Netflix TechBlog

OCTOBER 27, 2020

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. The processed data is typically stored as data warehouse tables in AWS S3. Moving data with Bulldozer at Netflix.

Latency 243

Latency Storage Big Data Tuning 243

All Things Distributed

DECEMBER 13, 2009

The broad Amazon EC2 customer base brings such diversity in workload and utilization patterns that it allows us to operate Amazon EC2 with extreme efficiency. A highly efficient purchasing model such as Spot Instances is another way in which Amazon EC2 customers benefit from the unique economies of scale found in AWS Infrastructure Services.

Cloud 63

Cloud AWS Storage Innovation 63

The Netflix TechBlog

FEBRUARY 16, 2021

However, with our rapid product innovation speed, the whole approach experienced significant challenges: Business Complexity: The existing SKU management solution was designed years ago when the engagement rules were simple?—?three SKUDB: SKU catalog data was migrated from the metadata configuration files to a relational database.

Mobile 209

Mobile Engineering Infrastructure Scalability 209

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

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support. And I’m sure we’ve all experienced frustration when an application crashes, is slow to load, or doesn’t load at all.

Artificial Intelligence 183

Artificial Intelligence Social Media Monitoring IoT 183

The Netflix TechBlog

OCTOBER 18, 2022

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 202

Java Scalability Traffic Architecture 202

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support. And I’m sure we’ve all experienced frustration when an application crashes, is slow to load, or doesn’t load at all.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

Highly Scalable

MARCH 1, 2012

NoSQL databases are often compared by various non-functional criteria, such as scalability, performance, and consistency. At the same time, NoSQL data modeling is not so well studied and lacks the systematic theory found in relational databases. Document databases advance the BigTable model offering two significant improvements.

Database 279

Database Ecommerce Efficiency Engineering 279

The Morning Paper

SEPTEMBER 19, 2019

MongoDB is an important database, and this paper explains the tunable (per-operation) consistency models that MongoDB provides and how they are implemented under the covers. Microsoft have a paper describing their new recovery mechanism in Azure SQL Database , the key feature being that it can recovery in constant time.

Blockchain 46

Blockchain Hardware Google Analytics 46

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.

Analytics 191

Analytics Traffic Big Data Efficiency 191

Abhishek Tiwari

DECEMBER 27, 2017

ETL refers to extract, transform, load and it is generally used for data warehousing and data integration. ETL is a product of the relational database era and it has not evolved much in last decade. There are several emerging data trends that will define the future of ETL in 2018. Machine learning meets data integration.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

The Morning Paper

JUNE 23, 2019

Coupled with stateless application servers to execute business logic and a database-like system to provide persistent storage, they form a core component of popular data center service archictectures. Why are developers using RInK systems as part of their design? Fetching too much data in a single query (i.e.,

Cache 79

Cache Latency Google Lambda 79

All Things Distributed

NOVEMBER 15, 2010

These trade-offs have even impacted the way the lowest level building blocks in our computer architectures have been designed. Graphics processing is one such area with huge computational requirements, but where each of the tasks is relatively small and often a set of operations are performed on data in the form of a pipeline.

AWS 136

AWS Latency Programming Architecture 136

Highly Scalable

MARCH 10, 2015

This article describes six major optimization problems related to marketing and pricing that can be solved leveraging data mining techniques. Although these problems are very different, we are trying to establish a common framework that helps to design optimization and data mining tasks required for solutions.

Retail 152

Retail C++ Analytics Metrics 152

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. However, ClickHouse is super efficient for timeseries and provides “sharding” out of the box (scalability beyond one node).

Database 40

Database Analytics Blockchain Healthcare 40