Containerized Microservices: A Survey of Resource Management Frameworks

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    23 Scopus citations

    Abstract

    The growing adoption of microservice architectures (MSAs) has led to major research and development efforts to address their challenges and improve their performance, reliability, and robustness. Important aspects of MSA that are not sufficiently covered in the open literature include efficient cloud resource allocation and optimal power management. Other aspects of MSA remain widely scattered in the literature, including cost analysis, service level agreements (SLAs), and demand-driven scaling. In this article, we examine recent cloud frameworks for containerized microservices with a focus on efficient resource utilization using auto-scaling. We classify these frameworks on the basis of their resource allocation models and underlying hardware resources. We highlight current MSA trends and identify workload-driven resource sharing within microservice meshes and SLA streamlining as two key areas for future microservice research.

    Original languageBritish English
    Pages (from-to)3775-3796
    Number of pages22
    JournalIEEE Transactions on Network and Service Management
    Volume21
    Issue number4
    DOIs
    StatePublished - 2024

    Keywords

    • Microservices
    • container orchestration
    • containers
    • machine learning
    • predictive allocation
    • reactive allocation
    • resource management
    • workload forecasting

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