Optimizing Serverless Function Orchestration for Complex Workflows in Cloud Platforms
DOI:
https://doi.org/10.47672/ajce.2458Keywords:
Serverless Computing (C61), Function Orchestration (C63), Cloud Platforms (L86), Workflow Optimization (C61), Adaptive Learning Systems (D83), Feedback Loops (D83)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.
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Copyright (c) 2024 Anaswara Thekkan Rajan
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