Dynatrace

NOVEMBER 8, 2021

Here’s a brief primer on APM and how it has changed for cloud-native environments, and some tips on what to look for in modern APM solutions. In recent years, APM has expanded to encompass cloud-native environments and distributed applications composed of microservices. Root-cause analysis. APM solutions: A primer.

Artificial Intelligence 236

Artificial Intelligence Monitoring Infrastructure Cloud 236

Dynatrace

OCTOBER 1, 2021

As dynamic systems architectures increase in complexity and scale, IT teams face mounting pressure to track and respond to conditions and issues across their multi-cloud environments. Observability relies on telemetry derived from instrumentation that comes from the endpoints and services in your multi-cloud computing environments.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

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 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. Their analysis determines whether immediate action needs to be taken to resolve an issue (or identify an opportunity). What Are Real-Time Digital Twins?

Cloud 52

Cloud Development Analytics Azure 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., The higher-level digital twins continue to run in the cloud or on-premises – wherever the required computing resources are located.

IoT 45

IoT Ecommerce Analytics Latency 45

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. Their analysis determines whether immediate action needs to be taken to resolve an issue (or identify an opportunity). What Are Real-Time Digital Twins?

Cloud 52

Cloud Development Analytics Azure 52

All Things Distributed

OCTOBER 7, 2015

In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data. QuickSight is a fast, cloud native, scalable, business intelligence service for the 1/10th the cost of old-guard BI solutions.

Cloud 137

Cloud Big Data AWS Analytics 137

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., The higher-level digital twins continue to run in the cloud or on-premises – wherever the required computing resources are located.

IoT 40

IoT Ecommerce Analytics Latency 40

Dynatrace

JUNE 1, 2021

Millions of lines of code comprise these apps, and they include hundreds of interconnected digital services and open-source solutions , and run in containerized environments hosted across multiple cloud services. Why cloud-native applications make APM challenging. Cloud-native apps also produce many kinds of data.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

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. It’s not enough to just 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

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

All Things Distributed

JUNE 7, 2017

We have seen that such devices can benefit greatly from the elastic resources of the cloud. Some applications – medical equipment, industrial machinery, and building automation are just a few – can't rely exclusively on the cloud for control, and require some form of local storage and execution. and deployed down from the cloud.

AWS 118

AWS IoT Lambda Storage 118

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. Others include fleet and traffic management, healthcare, financial services, IoT, and e-commerce recommendations.

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. Others include fleet and traffic management, healthcare, financial services, IoT, and e-commerce recommendations.

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. Others include fleet and traffic management, healthcare, financial services, IoT, and e-commerce recommendations.

Code 52

Code Analytics Healthcare IoT 52

ACM Sigarch

DECEMBER 6, 2018

smart cameras & analytics) to interactive/immersive environments and autonomous driving (e.g. To foster research in these categories, we provide an overview of each of these categories to understand the implications on workload analysis and HW/SW architecture research. interactive AR/VR, gaming and critical decision making).

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 63

Programming IoT Java Analytics 63

All Things Distributed

JUNE 21, 2018

Use cases such as gaming, ad tech, and IoT lend themselves particularly well to the key-value data model where the access patterns require low-latency Gets/Puts for known key values. The data warehouse also persists the processed data directly into Aurora MySQL and Amazon Redshift to support both operational and analytical queries.

Database 167

Database AWS Games Latency 167

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