Dynatrace

DECEMBER 22, 2019

AWS offers a broad set of global, cloud-based services including computing, storage, networking, Internet of Things (IoT), and many others. Therefore, the ability to view a real-time map of your applications, services, and cloud resources is key to your success. Amazon Kinesis Data Analytics. Dynatrace news.

AWS 136

AWS Metrics IoT Storage 136

Dynatrace

DECEMBER 22, 2019

AWS offers a broad set of global, cloud-based services including computing, storage, networking, Internet of Things (IoT), and many others. Therefore, the ability to view a real-time map of your applications, services, and cloud resources is key to your success. Amazon Kinesis Data Analytics. Dynatrace news.

AWS 133

AWS Metrics IoT Storage 133

Dynatrace

JUNE 1, 2020

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course end-users that access these applications – including your customers and employees. Advanced Cloud Observability. APM can also be referred to as: Application performance management.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

Dynatrace

JUNE 1, 2021

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course, end-users that access these applications — including a company’s customers and employees. Why cloud-native applications make APM challenging. What does APM stand for?

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

Testsigma

FEBRUARY 12, 2021

IoT Test Automation. The Internet of Things is generally referred to as IoT which encompasses computers, cars, houses or some other technological system related. There is a huge expansion and the need for a good IoT research plan. . In 2019, we had previously projected the demand for IoT research at $781.96billion.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

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

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

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

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

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

Apica

NOVEMBER 15, 2019

including iPhones/ mobile devices, set-top boxes, game stations, and IoT devices. Support for capacity planning, including “prescale clustering” –The Cloud, by definition, has no capacity limit, and many organizations rely on dynamic scaling to address usage spikes.

Performance Testing 40

Performance Testing Testing Performance Games 40

All Things Distributed

DECEMBER 13, 2016

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

AWS 166

AWS Cloud Artificial Intelligence IoT 166

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. Typical use cases for a graph database include social networking, recommendation engines, fraud detection, and knowledge graphs.

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. Although some vendors have added support for APIs and cloud services most have not even bothered to adapt with changing technology landscape.

Systems 63

Systems Cache Website Network 63