Optimizing Serverless Function Orchestration for Complex Workflows in Cloud Platforms

Anaswara Thekkan Rajan ()

American Journal of Computing and Engineering, 2024, vol. 7, issue 5, 1 - 11

Abstract: Purpose: This paper aims to investigate ways of increasing the efficiency of various workloads of serverless function orchestration in cloud systems while decreasing latency and optimizing resources. Materials and Methods: The report suggests adaptive learning systems and a feedback loop framework for managing the orchestrating serverless environment. Findings: It has also been affirmed that case studies help validate the framework rather than presenting the practical implications of the proposed techniques. Implications to Theory, Practice and Policy: The paper recommends focusing on managing performance, dependencies, and expenses in serverless function orchestration by employing adaptive learning systems and feedback loop frameworks.

Keywords: Serverless Computing (C61); Function Orchestration (C63); Cloud Platforms (L86); Workflow Optimization (C61); Adaptive Learning Systems (D83); Feedback Loops (D83) (search for similar items in EconPapers)
Date: 2024
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