Containerized Microservices Orchestration and Provisioning in Cloud Computing: A Conceptual Framework and Future Perspectives
Cloud computing is a rapidly growing paradigm which has evolved from having a monolithic to microservices architecture. The importance of cloud data centers has expanded dramatically in the previous decade, and they are now regarded as the backbone of the modern economy. Cloud-based microservices ar...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/12/5793 |
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| author | Abdul Saboor Mohd Fadzil Hassan Rehan Akbar Syed Nasir Mehmood Shah Farrukh Hassan Saeed Ahmed Magsi Muhammad Aadil Siddiqui |
| author_facet | Abdul Saboor Mohd Fadzil Hassan Rehan Akbar Syed Nasir Mehmood Shah Farrukh Hassan Saeed Ahmed Magsi Muhammad Aadil Siddiqui |
| author_sort | Abdul Saboor |
| collection | DOAJ |
| description | Cloud computing is a rapidly growing paradigm which has evolved from having a monolithic to microservices architecture. The importance of cloud data centers has expanded dramatically in the previous decade, and they are now regarded as the backbone of the modern economy. Cloud-based microservices architecture is incorporated by firms such as Netflix, Twitter, eBay, Amazon, Hailo, Groupon, and Zalando. Such cloud computing arrangements deal with the parallel deployment of data-intensive workloads in real time. Moreover, commonly utilized cloud services such as the web and email require continuous operation without interruption. For that purpose, cloud service providers must optimize resource management, efficient energy usage, and carbon footprint reduction. This study presents a conceptual framework to manage the high amount of microservice execution while reducing response time, energy consumption, and execution costs. The proposed framework suggests four key agent services: (1) intelligent partitioning: responsible for microservice classification; (2) dynamic allocation: used for pre-execution distribution of microservices among containers and then makes decisions for dynamic allocation of microservices at runtime; (3) resource optimization: in charge of shifting workloads and ensuring optimal resource use; (4) mutation actions: these are based on procedures that will mutate the microservices based on cloud data center workloads. The suggested framework was partially evaluated using a custom-built simulation environment, which demonstrated its efficiency and potential for implementation in a cloud computing context. The findings show that the engrossment of suggested services can lead to a reduced number of network calls, lower energy consumption, and relatively reduced carbon dioxide emissions. |
| first_indexed | 2024-03-10T00:32:21Z |
| format | Article |
| id | doaj.art-4775fbf17eb44c308df36b713b7ae446 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T00:32:21Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-4775fbf17eb44c308df36b713b7ae4462023-11-23T15:22:25ZengMDPI AGApplied Sciences2076-34172022-06-011212579310.3390/app12125793Containerized Microservices Orchestration and Provisioning in Cloud Computing: A Conceptual Framework and Future PerspectivesAbdul Saboor0Mohd Fadzil Hassan1Rehan Akbar2Syed Nasir Mehmood Shah3Farrukh Hassan4Saeed Ahmed Magsi5Muhammad Aadil Siddiqui6High-Performance Cloud Computing Centre (HPC3), Department of Computer & Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, MalaysiaCentre for Research in Data Science (CeRDaS), Department of Computer & Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, MalaysiaPositive Computing (+COMP), Department of Computer & Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, MalaysiaKICSIT, Institute of Space Technology (IST), Islamabad 44000, PakistanHigh-Performance Cloud Computing Centre (HPC3), Department of Computer & Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, MalaysiaDepartment of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, MalaysiaDepartment of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, MalaysiaCloud computing is a rapidly growing paradigm which has evolved from having a monolithic to microservices architecture. The importance of cloud data centers has expanded dramatically in the previous decade, and they are now regarded as the backbone of the modern economy. Cloud-based microservices architecture is incorporated by firms such as Netflix, Twitter, eBay, Amazon, Hailo, Groupon, and Zalando. Such cloud computing arrangements deal with the parallel deployment of data-intensive workloads in real time. Moreover, commonly utilized cloud services such as the web and email require continuous operation without interruption. For that purpose, cloud service providers must optimize resource management, efficient energy usage, and carbon footprint reduction. This study presents a conceptual framework to manage the high amount of microservice execution while reducing response time, energy consumption, and execution costs. The proposed framework suggests four key agent services: (1) intelligent partitioning: responsible for microservice classification; (2) dynamic allocation: used for pre-execution distribution of microservices among containers and then makes decisions for dynamic allocation of microservices at runtime; (3) resource optimization: in charge of shifting workloads and ensuring optimal resource use; (4) mutation actions: these are based on procedures that will mutate the microservices based on cloud data center workloads. The suggested framework was partially evaluated using a custom-built simulation environment, which demonstrated its efficiency and potential for implementation in a cloud computing context. The findings show that the engrossment of suggested services can lead to a reduced number of network calls, lower energy consumption, and relatively reduced carbon dioxide emissions.https://www.mdpi.com/2076-3417/12/12/5793cloud computingvirtual machinecontainersmicroservicesmulticloud |
| spellingShingle | Abdul Saboor Mohd Fadzil Hassan Rehan Akbar Syed Nasir Mehmood Shah Farrukh Hassan Saeed Ahmed Magsi Muhammad Aadil Siddiqui Containerized Microservices Orchestration and Provisioning in Cloud Computing: A Conceptual Framework and Future Perspectives Applied Sciences cloud computing virtual machine containers microservices multicloud |
| title | Containerized Microservices Orchestration and Provisioning in Cloud Computing: A Conceptual Framework and Future Perspectives |
| title_full | Containerized Microservices Orchestration and Provisioning in Cloud Computing: A Conceptual Framework and Future Perspectives |
| title_fullStr | Containerized Microservices Orchestration and Provisioning in Cloud Computing: A Conceptual Framework and Future Perspectives |
| title_full_unstemmed | Containerized Microservices Orchestration and Provisioning in Cloud Computing: A Conceptual Framework and Future Perspectives |
| title_short | Containerized Microservices Orchestration and Provisioning in Cloud Computing: A Conceptual Framework and Future Perspectives |
| title_sort | containerized microservices orchestration and provisioning in cloud computing a conceptual framework and future perspectives |
| topic | cloud computing virtual machine containers microservices multicloud |
| url | https://www.mdpi.com/2076-3417/12/12/5793 |
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