Abstract
The rapid proliferation of distributed cloud systems has revolutionized software deployment and scalability, enabling organizations to meet dynamic demands efficiently. However, optimizing software performance in such environments presents unique challenges, including resource heterogeneity, network latency, and dynamic workload variations. This paper explores the critical factors influencing software performance in distributed cloud systems, highlighting common bottlenecks and their root causes. It also presents a comprehensive analysis of state-of-the-art solutions, such as advanced resource allocation algorithms, load balancing techniques, and containerized microservices. Additionally, the study introduces a framework for evaluating performance metrics and proposes strategies to mitigate inefficiencies while ensuring scalability and cost-effectiveness. By addressing these challenges, this research aims to provide actionable insights and foster innovation in the design and optimization of software systems for distributed clouds.
Published Version
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