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

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

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

SEPTEMBER 30, 2021

Not only will they get much more out of the tools they use daily, but they’ll also be able to deliver superior functionality, efficiency, and performance to your customers. Data analytics. By carving the right AWS certification path, developers can even use their certification and training to advance their careers long term.

AWS 205

AWS Best Practices Analytics Cloud 205

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. 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 list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

ScaleOut Software

AUGUST 18, 2018

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., Because real-world IoT applications can track thousands of devices or other entities (e.g.,

IoT 45

IoT Ecommerce Analytics Latency 45

Dynatrace

NOVEMBER 8, 2021

Application performance monitoring (APM) solutions have evolved in recent years, and organizations now have plenty of options to choose from when selecting the right tools for their needs. APM solutions track key software application performance metrics using monitoring software and telemetry data. Dynatrace news.

Artificial Intelligence 229

Artificial Intelligence Monitoring Infrastructure Cloud 229

ScaleOut Software

AUGUST 18, 2018

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., 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. Scaleout StreamServer® DT was created to meet this need.

IoT 52

IoT Azure Analytics Healthcare 52

VoltDB

JUNE 9, 2017

Historically, telco analytics have been limited and difficult. Analytics and insights have always taken a back seat to the first two priorities – accurate data processing and billing. Does this affect our analytics strategy? Information needs to be handled in real-time, not via batch processing. The answer: Absolutely!

Analytics 40

Analytics Strategy Network Games 40

VoltDB

JUNE 9, 2017

Historically, telco analytics have been limited and difficult. Analytics and insights have always taken a back seat to the first two priorities – accurate data processing and billing. Does this affect our analytics strategy? Information needs to be handled in real-time, not via batch processing. The answer: Absolutely!

Analytics 40

Analytics Strategy Network Games 40

Dynatrace

JULY 6, 2020

Effortlessly optimize Azure database performance. Database-service views provide all the metrics you need to set up high-performance database services. Let’s look at the Azure DB for MariaDB overview as an example. Get full observability into your Azure MySQL database. Get a comprehensive view of your batch jobs.

Azure 146

Azure Cloud Big Data Virtualization 146

Dynatrace

JUNE 1, 2021

Application performance monitoring (APM) is the practice of tracking key software application performance metrics using monitoring software and telemetry data. Practitioners use APM to ensure system availability, optimize service performance and response times, and improve user experiences. Application performance management.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

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. For example, heart-rate telemetry from a smart watch cannot be effectively evaluated in isolation. 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. For example, heart-rate telemetry from a smart watch cannot be effectively evaluated in isolation. Sign up to use the service here.

Logistics 52

Logistics IoT Analytics Azure 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 63

Programming IoT Java Analytics 63

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

ACM Sigarch

DECEMBER 6, 2018

smart cameras & analytics) to interactive/immersive environments and autonomous driving (e.g. One such example is activity recognition in motion video (such as LRCN , Convnets ) which may entail running combinations of both convolutional as well as recurrent neural networks simultaneously. Quality vs Bandwidth.

Wireless 54

Wireless IoT Analytics Architecture 54

ScaleOut Software

AUGUST 20, 2020

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. For example, a PLM digital twin of a truck engine might describe the properties of the engine, such as its temperature and oil pressure.

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

AUGUST 20, 2020

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. For example, a PLM digital twin of a truck engine might describe the properties of the engine, such as its temperature and oil pressure.

Cloud 52

Cloud Development Analytics Azure 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

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 example, one of ScaleOut Software’s customers recently upgraded from just using distributed caching to scale its ecommerce application.

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 example, one of ScaleOut Software’s customers recently upgraded from just using distributed caching to scale its ecommerce application.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

Adrian Cockcroft

FEBRUARY 13, 2023

This is the AWS Professional Services built tooling that customers can use to track the carbon footprint of their operations and processes, along with a customer example. Good example, well presented interesting new material. AWS Inferentia 2.6x shorter training time, saving 54% energy and 75% cost.

AWS 64

AWS Energy Architecture Programming 64

Dynatrace

JUNE 13, 2019

Data analysis within large and highly dynamic microservices environments is the biggest challenge that Application Performance Monitoring (APM) vendors face today. Agents will continue to be the primary and best means of performance-data collection going forward. Dynatrace has now also officially joined the OpenTelemetry project.

IoT 45

IoT C++ Analytics Java 45

ScaleOut Software

MAY 4, 2018

For example, if an IoT application is attempting to detect whether data from a temperature sensor is predicting the failure of the medical freezer to which it is attached, it looks at patterns in the temperature changes, such as sudden spikes or a continuously upward trend, without regard to the freezer’s usage or service history.

Processing 40

Processing IoT Programming Software Engineering 40

ScaleOut Software

MAY 4, 2018

For example, if an IoT application is attempting to detect whether data from a temperature sensor is predicting the failure of the medical freezer to which it is attached, it looks at patterns in the temperature changes, such as sudden spikes or a continuously upward trend, without regard to the freezer’s usage or service history.

Processing 40

Processing IoT Programming Software Engineering 40

All Things Distributed

DECEMBER 13, 2016

Take Peterborough City Council as an example. The council has deployed IoT Weather Stations in Schools across the City and is using the sensor information collated in a Data Lake to gain insights on whether the weather or pollution plays a part in learning outcomes. Fraud.net is a good example of this.

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

OCTOBER 7, 2015

Most business users continue to struggle answering key business questions such as “Who are my top customers and what are they buying?”, “How is my marketing campaign performing?”, SPICE enables QuickSight to scale to many terabytes of analytical data and deliver response time for most visualization queries in milliseconds.

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

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

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. I am yet to find a traditional CMS vendor who can deliver this level of performance on the scale (millions of page views per day).

Systems 63

Systems Cache Website Network 63