ScaleOut Software

JULY 19, 2021

We are increasingly surrounded by intelligent IoT devices, which have become an essential part of our lives and an integral component of business and industrial infrastructures. The technology that can do this is called in-memory computing. Conventional streaming analytics architectures have not kept up with the growing demands of IoT.

IoT 78

IoT Analytics Big Data Architecture 78

Adrian Cockcroft

FEBRUARY 13, 2023

Margaret leads the worldwide solution architect program for sustainability, and gives an excellent talk on how customers should think about optimizing their workloads. PEX201 Building a sustainable practice for tomorrow  — Mansi Vaghela AWS SA, Deborshi Choudhury AWS Partner SA, Rolf Korski Knowit VP Technology.

AWS 64

AWS Energy Architecture Programming 64

ScaleOut Software

JUNE 22, 2020

Going back to the mid-1990s, online systems have seen relentless, explosive growth in usage, driven by ecommerce, mobile applications, and more recently, IoT. For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

ScaleOut Software

JUNE 22, 2020

Going back to the mid-1990s, online systems have seen relentless, explosive growth in usage, driven by ecommerce, mobile applications, and more recently, IoT. For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time. The list goes on.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time. The list goes on.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JANUARY 9, 2020

In addition, real-time information on sales and inventory gives managers new tools that help optimize overall performance and maximize profits. To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

In addition, real-time information on sales and inventory gives managers new tools that help optimize overall performance and maximize profits. To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

In addition, real-time information on sales and inventory gives managers new tools that help optimize overall performance and maximize profits. With this ground-breaking technology, logistics managers now can easily keep track of thousands of retail outlets, immediately identify and respond to issues, and optimize operations in real time.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

AUGUST 20, 2020

Digital twin models used in product lifecycle management (PLM) or in IoT device modeling (for example, Azure Digital Twins ) just describe the properties of physical entities, usually to allow querying by business processes. In contrast, real-time digital twins analyze incoming telemetry from each data source and track changes in its state.

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

AUGUST 20, 2020

Digital twin models used in product lifecycle management (PLM) or in IoT device modeling (for example, Azure Digital Twins ) just describe the properties of physical entities, usually to allow querying by business processes. In contrast, real-time digital twins analyze incoming telemetry from each data source and track changes in its state.

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

JULY 14, 2021

The population of intelligent IoT devices is exploding, and they are generating more telemetry than ever. The Microsoft Azure IoT ecosystem offers a rich set of capabilities for processing IoT telemetry, from its arrival in the cloud through its storage in databases and data lakes.

IoT 52

IoT Azure Analytics Serverless 52

Dynatrace

APRIL 5, 2021

Similar to AWS Lambda , Azure Functions is a serverless compute service by Microsoft that can run code in response to predetermined events or conditions (triggers), such as an order arriving on an IoT system, or a specific queue receiving a new message. Azure IoT Functions, for instance, processes requests for Azure IoT Edge.

Azure 136

Azure Serverless IoT Lambda 136

Dynatrace

JANUARY 26, 2021

The phrase “serverless computing” appears contradictory at first, but for years now, successful companies have understood the benefit of using serverless technologies to streamline operations and reduce costs. Inefficiencies cost technology companies up to $100 billion per year. Dynatrace news.

Serverless 241

Serverless Efficiency Lambda Azure 241

ScaleOut Software

SEPTEMBER 20, 2018

This model organizes key information about each data source (for example, an IoT device, e-commerce shopper, or medical patient) in a software component that tracks the data source’s evolving state and encapsulates algorithms, such as predictive analytics, for interpreting that state and generating real-time feedback.

Programming 63

Programming IoT Java Analytics 63

Testsigma

JANUARY 7, 2022

2015 saw the trend of scriptless testing and IoT focussed methodologies. With the end of 2021, we are here after careful analysis of the market trend and the latest prioritised technologies that we believe will be important in the future. IoT automation testing. The story has continued since then for each year. Signup now.

Artificial Intelligence 89

Artificial Intelligence IoT Software Software 89

Tech News Gather

JULY 19, 2023

Smart home automation is the process of automating your house by using Internet of Things (IoT) devices to manage your lights, appliances, HVAC, entertainment, security cameras, and alarms, and other sensors for things like water or gas leaks. Connect the architectural pieces of your program using secure gateways.

Wireless 52

Wireless IoT Development Internet 52

ScaleOut Software

SEPTEMBER 20, 2018

This model organizes key information about each data source (for example, an IoT device, e-commerce shopper, or medical patient) in a software component that tracks the data source’s evolving state and encapsulates algorithms, such as predictive analytics, for interpreting that state and generating real-time feedback.

Programming 40

Programming IoT Java Analytics 40

All Things Distributed

DECEMBER 13, 2016

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. The British Government is also helping to drive innovation and has embraced a cloud-first policy for technology adoption.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

JULY 14, 2015

In this blog post, I will explain how these three new capabilities empower you to build applications with distributed systems architecture and create responsive, reliable, and high-performance applications using DynamoDB that work at any scale. DynamoDB Streams simplifies and improves this design pattern with a distributed systems approach.

Database 167

Database Lambda AWS IoT 167

All Things Distributed

APRIL 9, 2015

At Amazon we have hundreds of teams using machine learning and by making use of the Machine Learning Service we can significantly speed up the time they use to bring their technologies into production. One of the most exciting technologies we have built lately at AWS is Amazon Lambda. Amazon Lambda.

Lambda 122

Lambda Cloud IoT AWS 122

ScaleOut Software

MAY 19, 2020

This highly scalable cloud service is designed to simultaneously and cost-effectively track telemetry from millions of data sources and provide real-time feedback in milliseconds while simultaneously performing continuous, aggregate analytics every few seconds.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

MAY 19, 2020

This highly scalable cloud service is designed to simultaneously and cost-effectively track telemetry from millions of data sources and provide real-time feedback in milliseconds while simultaneously performing continuous, aggregate analytics every few seconds.

Logistics 52

Logistics IoT Analytics Azure 52

All Things Distributed

MAY 21, 2018

We already have an idea of how digitalization, and above all new technologies like machine learning, big-data analytics or IoT, will change companies' business models — and are already changing them on a wide scale. Only parts of the processes are being performed by machines, or at least supported by them.

Artificial Intelligence 76

Artificial Intelligence Technology Technology IoT 76

Enprowess

SEPTEMBER 7, 2021

Quick summary : Node vs React Comparison is not correct because both technologies are entirely different things. We have started our introduction with the words “JavaScript-based” technologies. JavaScript is one of the most famous and loved programming languages nowadays. IoT-based applications. JavaScript. Network: Node.js

Open Source 52

Open Source Virtualization Programming Servers 52

ScaleOut Software

DECEMBER 10, 2019

For these reasons, most streaming applications only perform rudimentary analysis (often in the form of queries) on the incoming data stream and push most of the event messages into a data lake for offline examination. Note that the platform can seamlessly scale its performance by running thousands of real-time digital twins in parallel.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

For these reasons, most streaming applications only perform rudimentary analysis (often in the form of queries) on the incoming data stream and push most of the event messages into a data lake for offline examination. Note that the platform can seamlessly scale its performance by running thousands of real-time digital twins in parallel.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

For these reasons, most streaming applications only perform rudimentary analysis (often in the form of queries) on the incoming data stream and push most of the event messages into a data lake for offline examination. Note that the platform can seamlessly scale its performance by running thousands of real-time digital twins in parallel.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

JULY 27, 2018

Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.

Scalability 40

Scalability Cache Airlines Healthcare 40

ScaleOut Software

JULY 27, 2018

Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.

Scalability 40

Scalability Cache Airlines Healthcare 40

Dynatrace

SEPTEMBER 30, 2022

Business processes and events may be written to system logs or tracked and stored by an ERP solution, exposed via an application programming interface (API). Much has been written about breaking down IT silos through cultural shifts and technology alignment. Break down IT and business silos. The a bility to measure outcomes.

Analytics 168

Analytics Best Practices Metrics IoT 168