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.

Analytics 52

Analytics IoT Lambda Big Data 52

All Things Distributed

MARCH 11, 2015

Many of these innovations will have a significant analytics component or may even be completely driven by it. For example many of the Internet of Things innovations that we have seen come to life in the past years on AWS all have a significant analytics components to it. Cloud analytics are everywhere.

Analytics 135

Analytics Cloud Healthcare Retail 135

ScaleOut Software

AUGUST 18, 2018

In previous blogs , we have explored the power of the digital twin model for stateful stream-processing. Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g.,

IoT 45

IoT Ecommerce Analytics Latency 45

ScaleOut Software

AUGUST 18, 2018

In previous blogs , we have explored the power of the digital twin model for stateful stream-processing. Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g.,

IoT 40

IoT Ecommerce Analytics Latency 40

ScaleOut Software

APRIL 6, 2021

With the ScaleOut Digital Twin Streaming Service , an Azure-hosted cloud service, ScaleOut Software introduced breakthrough capabilities for streaming analytics using the real-time digital twin concept. This simplifies the installation process and ensures portability across operating systems.

IoT 52

IoT Azure Analytics Healthcare 52

Dynatrace

NOVEMBER 8, 2021

Organizations use APM to ensure system availability, optimize service performance and response times, and improve user experiences. By carefully considering the various APM tools available and how well they meet your needs, you’ll have the best chance of picking the right one for your organization. APM solutions: A primer.

Artificial Intelligence 229

Artificial Intelligence Monitoring Infrastructure Cloud 229

Dynatrace

SEPTEMBER 30, 2021

What kinds of AWS certifications are available today? AWS Certified Data Analytics – Specialty: Highly knowledgeable data analytics pros who have already worked with AWS for some time should consider getting this certification. Data analytics. As of June 2021, Amazon currently offers 11 certifications. Machine learning.

AWS 205

AWS Best Practices Analytics Cloud 205

Dynatrace

JUNE 1, 2020

Application Performance Monitoring (APM) in its simplest terms is what practitioners use to ensure consistent availability, performance, and response times to applications. And this isn’t even the full extent of the types of monitoring tools available out there.

Artificial Intelligence 181

Artificial Intelligence Social Media Monitoring IoT 181

Dynatrace

JUNE 1, 2020

Application Performance Monitoring (APM) in its simplest terms is what practitioners use to ensure consistent availability, performance, and response times to applications. And this isn’t even the full extent of the types of monitoring tools available out there. That’s why we extended the Dynatrace platform to the edge device and API.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

Dynatrace

OCTOBER 1, 2021

As more organizations adopt cloud-native architectures, they are also looking for ways to implement AIOps, harnessing AI as a way to automate more processes throughout the DevSecOps life cycle. An advanced observability solution can also be used to automate more processes, increasing efficiency and innovation among Ops and Apps teams.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

Testsigma

FEBRUARY 12, 2021

The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. With all of these processes in place, cost optimization is also a high concern for organizations worldwide. IoT Test Automation. Many changes are rendered through automated testing. Hyperautomation.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. It’s called the ScaleOut Digital Twin Streaming Service , and it’s now available for production use. Sign up to use the service here.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. It’s called the ScaleOut Digital Twin Streaming Service , and it’s now available for production use. Sign up to use the service here.

Logistics 52

Logistics IoT Analytics Azure 52

Dynatrace

JULY 6, 2020

Get insights into various aspects of database performance, including SQL queries or procedures, SQL modifications, SQL transactions, any detected problems or availability issues, hotspots, and more—all the valuable information that a DevOps team could ask for to optimize database performance. What’s next?

Azure 146

Azure Cloud Big Data Virtualization 146

All Things Distributed

JUNE 7, 2017

This is because data gets more valuable when it can be processed together with other data. At the same time, it can be valuable to process some data right at the source where it is generated. When you can't address scenarios such as these, the value of data you don't process is lost. Law of Economics.

AWS 118

AWS IoT Lambda Storage 118

ScaleOut Software

AUGUST 20, 2020

Simplifying the Development Process with Mock Environments. This blog post explains how a new software construct called a real-time digital twin running in a cloud-hosted service can create a breakthrough for streaming analytics. The method contains domain-specific knowledge, such as a predictive analytics algorithm for truck engines.

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

AUGUST 20, 2020

Simplifying the Development Process with Mock Environments. This blog post explains how a new software construct called a real-time digital twin running in a cloud-hosted service can create a breakthrough for streaming analytics. The method contains domain-specific knowledge, such as a predictive analytics algorithm for truck engines.

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

SEPTEMBER 20, 2018

These are exciting times in the evolution of stream-processing. As we have seen in previous blogs , the digital twin model offers a breakthrough approach to structuring stateful stream-processing applications. It represents a big step forward for building stream-processing applications.

Programming 63

Programming IoT Java Analytics 63

ScaleOut Software

DECEMBER 10, 2019

The problem with this approach is that important insights requiring quick action are not immediately available. Here is an illustration of real-time digital twins processing telemetry from towers in a power grid from the above example application: Real-time digital twins dramatically simplify application code in two ways.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

The problem with this approach is that important insights requiring quick action are not immediately available. Here is an illustration of real-time digital twins processing telemetry from towers in a power grid from the above example application: Real-time digital twins dramatically simplify application code in two ways.

Code 52

Code Analytics Healthcare 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. It can also take advantage of the elastic computing resources available in cloud infrastructures to quickly and cost-effectively scale throughput to meet changes in demand.

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. It can also take advantage of the elastic computing resources available in cloud infrastructures to quickly and cost-effectively scale throughput to meet changes in demand.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

ScaleOut Software

DECEMBER 10, 2019

The problem with this approach is that important insights requiring quick action are not immediately available. Here is an illustration of real-time digital twins processing telemetry from towers in a power grid from the above example application: Real-time digital twins dramatically simplify application code in two ways.

Code 52

Code Analytics Healthcare IoT 52

All Things Distributed

MAY 3, 2017

Most of Germany's hidden champions have earned their reputation through hard work: they have been optimizing their processes over decades. They have invested the time to perfect their processes and develop high-quality products for their customers. The power of persistence versus the speed of adjustment.

Logistics 72

Logistics IoT Analytics Innovation 72

ScaleOut Software

SEPTEMBER 20, 2018

These are exciting times in the evolution of stream-processing. As we have seen in previous blogs , the digital twin model offers a breakthrough approach to structuring stateful stream-processing applications. It represents a big step forward for building stream-processing applications.

Programming 40

Programming IoT Java Analytics 40

Tech News Gather

JULY 17, 2023

Wallet and Payment Apps The widespread availability of payment and wallet apps has dramatically simplified and increased the safety of online financial transactions. These apps save financial data in a safe place and simplify the payment process by removing the need to enter the same information often.

FinTech 40

FinTech Development IoT Mobile 40

Dynatrace

JUNE 1, 2021

Practitioners use APM to ensure system availability, optimize service performance and response times, and improve user experiences. User experience and business analytics. Experience and outcomes matter, whether the application is mobile app-to-user, IoT device-to-customers, or a web application behind the scenes.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

Dynatrace

JUNE 13, 2019

The Dynatrace platform automatically integrates OpenTelemetry data, thereby providing the highest possible scalability, enterprise manageability, seamless processing of data, and, most importantly the best analytics through Davis (our AI-driven analytics engine), and automation support available.

IoT 45

IoT C++ Analytics Java 45

Apica

NOVEMBER 15, 2019

including iPhones/ mobile devices, set-top boxes, game stations, and IoT devices. Built for DevOps –Rich API support for test automation and command control of the full test process should allow the integration between Operations and Development to be as seamless as possible.

Performance Testing 40

Performance Testing Testing Performance Games 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. Take GoSquared , a UK startup that runs all its development and production processes on AWS, as an example. Take Peterborough City Council as an example.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

OCTOBER 7, 2015

However, the data infrastructure to collect, store and process data is geared toward developers (e.g., However, the process of deriving actionable insights out of this wide variety of data sources is not easy. Put simply, data is not always readily available and accessible to organizational end users. Big data challenges.

Cloud 137

Cloud Big Data AWS Analytics 137

All Things Distributed

JUNE 21, 2018

As I have talked about before, one of the reasons why we built Amazon DynamoDB was that Amazon was pushing the limits of what was a leading commercial database at the time and we were unable to sustain the availability, scalability, and performance needs that our growing Amazon.com business demanded. The opposite is true.

Database 167

Database AWS Games Latency 167

Abhishek Tiwari

NOVEMBER 3, 2018

Most of the CMS vendors dodge questions of evolution by talking about incremental innovation primarily focused on customer experience (CX) such as analytics and personalisation. This made whole publishing process really slow and painful and CMS was part of growing pain. Eventually, we decided to move them to Jekyll.

Systems 63

Systems Cache Website Network 63

All Things Distributed

NOVEMBER 15, 2016

Previously, I wrote about Amazon QuickSight , a new service targeted at business users that aims to simplify the process of deriving insights from a wide variety of data sources quickly, easily, and at a low cost. Today, I am very happy to announce that QuickSight is now generally available in the N.

Analytics 152

Analytics Availability Media Social Media 152