Dynatrace

APRIL 26, 2022

Understanding why a user is experiencing transactional or performance issues enables organizations to achieve greater observability that goes beyond metrics, traces and logs. Digital experience monitoring (DEM) allows an organization to optimize customer experiences by taking into account the context surrounding digital experience metrics.

Monitoring 200

Monitoring Social Media IoT Metrics 200

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. APM can also be referred to as: Application performance management. Performance monitoring. Dynatrace news. Application monitoring.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

Dynatrace

AUGUST 27, 2020

Each service comes with zero-configuration, automatic instance detection, continuous data capture in context, and what’s most important – thanks to our AI engine Davis – is each service provides answers, not just data. AWS IoT Analytics. AWS IoT Things Graph. AWS Elastic Beanstalk. AWS Elemental MediaPackage.

AWS 267

AWS Cloud IoT Database 267

ScaleOut Software

JUNE 15, 2020

thousands of data sources. Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

thousands of data sources. Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

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

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

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. 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

Dynatrace

OCTOBER 1, 2021

In IT and cloud computing, observability is the ability to measure a system’s current state based on the data it generates, such as logs, metrics, and traces. As teams begin collecting and working with observability data, they are also realizing its benefits to the business, not just IT. What is observability? In short, no.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

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

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 45

IoT Ecommerce Analytics Latency 45

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. APM can be referred to as: Application performance monitoring. Application performance management. Performance monitoring. Dynatrace news.

Artificial Intelligence 181

Artificial Intelligence Social Media Monitoring IoT 181

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

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

Dynatrace

JULY 6, 2020

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. Effortlessly optimize Azure database performance. Database-service views provide all the metrics you need to set up high-performance database services.

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. Performance monitoring.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

VoltDB

JUNE 9, 2017

Historically, telco analytics have been limited and difficult. Handling the data generated by these networks is a herculean task. 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? The answer: Absolutely!

Analytics 40

Analytics Strategy Network Games 40

VoltDB

JUNE 9, 2017

Historically, telco analytics have been limited and difficult. Handling the data generated by these networks is a herculean task. 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? The answer: Absolutely!

Analytics 40

Analytics Strategy Network Games 40

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. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

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. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

Logistics 52

Logistics IoT Analytics Azure 52

Testsigma

FEBRUARY 12, 2021

When more companies transition into digital-first projects, there must be an expanded number of processes and IT data departments to keep IT teams on track. The latest trend in hyperautomation – Gartner projects that by the year 2023, 25% of tasks by the organisations will be able to perform autonomously and hence reducing the cost.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

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. It’s not enough just to pick out interesting events from an aggregated data stream and then send them to a database for offline analysis using Spark.

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. It’s not enough just to pick out interesting events from an aggregated data stream and then send them to a database for offline analysis using Spark.

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. Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications such as these require.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

DECEMBER 10, 2019

Event streams typically combine messages from many data sources, as shown below. 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.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

Event streams typically combine messages from many data sources, as shown below. 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.

Code 52

Code Analytics Healthcare IoT 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

Event streams typically combine messages from many data sources, as shown below. 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.

Code 52

Code Analytics Healthcare IoT 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. The key to meeting these challenges is to process incoming telemetry in the context of unique state information maintained for each individual data source.

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. The key to meeting these challenges is to process incoming telemetry in the context of unique state information maintained for each individual data source.

Cloud 52

Cloud Development Analytics Azure 52

ACM Sigarch

DECEMBER 6, 2018

smart cameras & analytics) to interactive/immersive environments and autonomous driving (e.g. Analyzing visual data is predominantly accomplished using deep learning. Apart from putting unprecedented strain on the computing subsystems, such workloads are heavy on data usage requiring a new way to analyze, store and retrieve data.

Wireless 54

Wireless IoT Analytics Architecture 54

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. The pace of these changes has made it challenging for server-based infrastructures to manage fast-growing populations of users and data sources while maintaining fast response times.

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. The pace of these changes has made it challenging for server-based infrastructures to manage fast-growing populations of users and data sources while maintaining fast response times.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

Adrian Cockcroft

FEBRUARY 13, 2023

STP213 Scaling global carbon footprint management — Blake Blackwell Persefoni Manager Data Engineering and Michael Floyd AWS Head of Sustainability Solutions. SUS312 How innovators are driving more sustainable manufacturing  — Marcus Ulmefors Northvolt Director Data and ML Platforms and Muhammad Sajid AWS SA. AWS Inferentia 2.6x

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. While data collection itself is an integral part of APM, it’s ultimately only a means to an end. The real challenge is robust and effective analysis of such data.

IoT 45

IoT C++ Analytics Java 45