{"title":"HCA操作员:用于微服务工作负载的混合云自动扩展工具","authors":"Yuyang Wang, Fan Zhang, S. Khan","doi":"10.1109/MSN57253.2022.00143","DOIUrl":null,"url":null,"abstract":"Elastic cloud platform, e.g. Kubernetes, enables dy-namically scale in or out computing resources in accordance with the workloads fluctuation. As the cloud evolves to hybrid, where public and private clouds co-exist as the underline substrate, autoscaling applications within a hybrid cloud is no longer straightforward. The difficulty lies in all aspects, e.g. global load balancing, hybrid-cloud monitoring and alerting, storage sharing and replication, security and privacy, etc. However, it will significantly pay off if hybrid-cloud autoscaling is supported and boundless computing resources can be utilized per request. In this paper, we design Hybrid Cloud Autoscaler Operator (HCA Operator), a customized Kubernetes Controller that leverages the Kubernetes Custom Resource to auto-scale microservice applications across hybrid clouds. HCA Operator load balances across hybrid clouds, monitors metrics, and autoscales to des-tination clusters that exist in other clouds. We discuss the implementation details and perform experiments in a hybrid cloud environment. The experimental results demonstrate that if the workload changes quickly, our Operator can properly auto-scale the microservice applications across hybrid cloud in order to meet the Service Level Agreement (SLA) requirements.","PeriodicalId":114459,"journal":{"name":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","volume":"41 6","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"HCA Operator: A Hybrid Cloud Auto-scaling Tooling for Microservice Workloads\",\"authors\":\"Yuyang Wang, Fan Zhang, S. Khan\",\"doi\":\"10.1109/MSN57253.2022.00143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Elastic cloud platform, e.g. Kubernetes, enables dy-namically scale in or out computing resources in accordance with the workloads fluctuation. As the cloud evolves to hybrid, where public and private clouds co-exist as the underline substrate, autoscaling applications within a hybrid cloud is no longer straightforward. The difficulty lies in all aspects, e.g. global load balancing, hybrid-cloud monitoring and alerting, storage sharing and replication, security and privacy, etc. However, it will significantly pay off if hybrid-cloud autoscaling is supported and boundless computing resources can be utilized per request. In this paper, we design Hybrid Cloud Autoscaler Operator (HCA Operator), a customized Kubernetes Controller that leverages the Kubernetes Custom Resource to auto-scale microservice applications across hybrid clouds. HCA Operator load balances across hybrid clouds, monitors metrics, and autoscales to des-tination clusters that exist in other clouds. We discuss the implementation details and perform experiments in a hybrid cloud environment. The experimental results demonstrate that if the workload changes quickly, our Operator can properly auto-scale the microservice applications across hybrid cloud in order to meet the Service Level Agreement (SLA) requirements.\",\"PeriodicalId\":114459,\"journal\":{\"name\":\"2022 18th International Conference on Mobility, Sensing and Networking (MSN)\",\"volume\":\"41 6\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 18th International Conference on Mobility, Sensing and Networking (MSN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MSN57253.2022.00143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 18th International Conference on Mobility, Sensing and Networking (MSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSN57253.2022.00143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
HCA Operator: A Hybrid Cloud Auto-scaling Tooling for Microservice Workloads
Elastic cloud platform, e.g. Kubernetes, enables dy-namically scale in or out computing resources in accordance with the workloads fluctuation. As the cloud evolves to hybrid, where public and private clouds co-exist as the underline substrate, autoscaling applications within a hybrid cloud is no longer straightforward. The difficulty lies in all aspects, e.g. global load balancing, hybrid-cloud monitoring and alerting, storage sharing and replication, security and privacy, etc. However, it will significantly pay off if hybrid-cloud autoscaling is supported and boundless computing resources can be utilized per request. In this paper, we design Hybrid Cloud Autoscaler Operator (HCA Operator), a customized Kubernetes Controller that leverages the Kubernetes Custom Resource to auto-scale microservice applications across hybrid clouds. HCA Operator load balances across hybrid clouds, monitors metrics, and autoscales to des-tination clusters that exist in other clouds. We discuss the implementation details and perform experiments in a hybrid cloud environment. The experimental results demonstrate that if the workload changes quickly, our Operator can properly auto-scale the microservice applications across hybrid cloud in order to meet the Service Level Agreement (SLA) requirements.