With the year coming to an end and temperatures dropping in much of the Northern Hemisphere, you might be feeling the urge to gather some loved ones, curl up at home, and laze about doing not much of ...

Thousands of Microsoft engineers build and test hundreds of software products several times a day. It is essential that this continuous integration scales, guarantees short feedback cycles, and ...

In today’s digital economy, high-scale applications must perform flawlessly, even during peak demand periods. With modern caching strategies, organizations can deliver high-speed experiences at scale.

Author: Dr. William Bain, CEO, ScaleOut Software. Modern enterprise applications are under constant pressure to respond instantly, scale seamlessly, and deliver reliable results. From retail and ...

ScaleOut Software is offering Version 6 of its ScaleOut Product Suite, its distributed caching and in-memory data grid software, introducing breakthrough capabilities “not found in today’s distributed ...

ScaleOut Software today is introducing Version 6 of its ScaleOut Product Suite, distributed caching and in-memory data grid software. This release introduces breakthrough capabilities not found in ...

Learn how to use in-memory caching, distributed caching, hybrid caching, response caching, or output caching in ASP.NET Core to boost the performance and scalability of your minimal API applications.

Today’s energy landscape demands fundamental transformation. Utilities face multiple challenges: aging infrastructure, increasingly complex grid environments, integrating renewable energy sources, and ...

A Quarkus extension for embedded Infinispan integrates in-memory data grid features directly into Quarkus applications, enabling efficient caching and data storage. A high-performance distributed ...

A high-performance distributed caching system built with .NET 9 and Redis, featuring cache invalidation, multiple caching strategies (Cache-Aside, Write-Through), and Clean Architecture. This project ...

Abstract: We investigate a distributed caching strategy based on multi-agent reinforcement learning (MARL) in a cache-aided network, where all wireless nodes have limited storage capacity and serve ...