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Optimizing Serverless Function Orchestration for Complex Workflows in Cloud Platforms

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  • Anaswara Thekkan Rajan

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.

Suggested Citation

  • Anaswara Thekkan Rajan, 2024. "Optimizing Serverless Function Orchestration for Complex Workflows in Cloud Platforms," American Journal of Computing and Engineering, AJPO Journals Limited, vol. 7(5), pages 1-11.
    • Handle: RePEc:bfy:ojajce:v:7:y:2024:i:5:p:1-11:id:2458
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    File URL: https://ajpojournals.org/journals/index.php/AJCE/article/view/2458/3256
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