Performance in Cloud Applications: A Technical Review

Abstract

Cloud computing has fundamentally transformed how applications are delivered and accessed at scale globally. However, this transition introduces new performance challenges that organizations must address, particularly around geographic distribution, network latency, and real-time application requirements. Moving to cloud-native architectures presents performance challenges for organizations in many ways, especially when it comes to delivering geographic distribution, network latency, and the performance profile of real-time applications. As a response to these performance challenges, there are now remarkably comprehensive tools available from today's cloud providers for automated infrastructure management, resource scaling with intelligence, and optimization frameworks. Edge computing promises solutions for performance, as it can deliver compute and content delivery close to the end user by moving computing to the edge of the network. The value of edge computing becomes obvious in media applications and cloud gaming apps that demand real-time processing. Artificial intelligence is also increasingly becoming part of the performance optimization landscape. AI-based systems provide predictive scaling, smart decisions on routing, and automated tuning of performance that continually optimizes the application's configuration. With next-generation wireless networks, machine learning, and edge computing evolving at the same time, applications can, in theory, interact with distributed infrastructure in an entirely different way.