Dynatrace

MARCH 6, 2024

Platform engineering creates and manages a shared infrastructure and set of tools, such as internal developer platforms (IDPs) , to enable software developers to build, deploy, and operate applications more efficiently. “IDPs are not constrained to building microservices or a new serverless app,” Grabner noted.

Engineering 241

Engineering Development DevOps Infrastructure 241

Dynatrace

NOVEMBER 17, 2020

Every tap in a mobile app triggers requests that, potentially, travel through a myriad of microservices, routed from one service to the next by service meshes, calling several serverless functions. An effective solution to this problem must be able to handle scale, depth, breadth, and heterogeneity across the software lifecycle.

Analytics 156

Analytics Technology Technology Cloud 156

Dynatrace

NOVEMBER 10, 2022

Cloud-native architecture is a structural approach to planning and implementing an environment for software development and deployment that uses resources and processes common with public clouds like Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Immutable infrastructure. The principles of cloud-native architecture.

Cloud 162

Cloud Architecture Serverless Infrastructure 162

ScaleOut Software

JANUARY 31, 2020

Real-time digital twins offer a compelling new software model for tracking and analyzing telemetry from large numbers of data sources. These query results are then forwarded to a data lake for offline analytics using tools such as Spark and for data visualization.

Analytics 59

Analytics Social Media Ecommerce Serverless 59

O'Reilly

MAY 19, 2020

AWS is far and away the cloud leader, followed by Azure (at more than half of share) and Google Cloud. But most Azure and GCP users also use AWS; the reverse isn’t necessarily true. Software engineers represent the largest cohort, comprising almost 20% of all respondents (see Figure 1 ). Respondent Demographics.

Cloud 141

Cloud Serverless AWS Architecture 141

ScaleOut Software

JANUARY 31, 2020

Real-time digital twins offer a compelling new software model for tracking and analyzing telemetry from large numbers of data sources. These query results are then forwarded to a data lake for offline analytics using tools such as Spark and for data visualization.

Analytics 52

Analytics Social Media Serverless Cloud 52

Dynatrace

OCTOBER 1, 2021

In these modern environments, every hardware, software, and cloud infrastructure component and every container, open-source tool, and microservice generates records of every activity. The architects and developers who create the software must design it to be observed.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

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

Dynatrace

JUNE 1, 2021

Application performance monitoring (APM) is the practice of tracking key software application performance metrics using monitoring software and telemetry data. Faster and higher-quality software releases. AI assistance enables teams to automate operations, release software faster, and deliver better business outcomes.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

Abhishek Tiwari

NOVEMBER 3, 2018

Recently I was asked about content management systems (CMS) of the future - more specifically how they are evolving in the era of microservices, APIs, and serverless computing. In addition, traditional CMS solutions lack integration with modern software stack, cloud services, and software delivery pipelines.

Systems 63

Systems Cache Website Network 63