基于微服务特性的容器自动扩缩容研究
|
摘要
基于微服务特性和其在Docker容器中的应用,提出了基于请求频次和响应时间的容器自动扩缩容策略.不同于传统基于阈值扩容策略中使用单一系统指标,通过对微服务REST API访问的监控,使用应用级指标请求频次和响应时间,定量描述应用特征.通过测试得到不同大小容器规格与服务请求频次、响应时间的关系数据.在应用部署时,可根据服务所需请求频次选择合适的容器资源配置,在应用扩容时,可将响应时间作为扩容阈值.实验验证,该扩容策略可在满足服务SLA(响应时间等)的同时,在应用部署与扩容过程中最大化地利用计算资源.
Based on the microservice characteristics and the Docker container, a container auto-scaling strategy is proposed by using service request frequency and response time. Different with traditional threshold-based autoscaling using single system-level index, we apply the application-level characteristics,the request frequency and the response time,to describe an application quantitatively by monitoring the micro-service REST API. We can measure the relationship between container-size, service request frequency and response time. According to the relationship data, we can select the appropriate container-size by the different required service request frequency when deploy an application and we can take the response time as auto-scaling threshold when scale. The experiments results prove that our auto-scaling strategy could make the application maximizing the usage of computing resources while satisfy the service SLA, no matter deploying or scaling.
Based on the microservice characteristics and the Docker container, a container auto-scaling strategy is proposed by using service request frequency and response time. Different with traditional threshold-based autoscaling using single system-level index, we apply the application-level characteristics,the request frequency and the response time,to describe an application quantitatively by monitoring the micro-service REST API. We can measure the relationship between container-size, service request frequency and response time. According to the relationship data, we can select the appropriate container-size by the different required service request frequency when deploy an application and we can take the response time as auto-scaling threshold when scale. The experiments results prove that our auto-scaling strategy could make the application maximizing the usage of computing resources while satisfy the service SLA, no matter deploying or scaling.
引文
[1]Amazon AWS Services[EB/OL].[2017-05-20].https://aws.amazon.com/.
[2]Google Cloud Platform[EB/OL].[2017-05-20].https://cloud.google.com/.
[3]Microsoft Azure[EB/OL].[2017-05-20].https://azure.microsoft.com/enus/?b=16.48/.
[4]阿里云[EB/OL].[2017-05-20].https://www.aliyun.com/.
[5]腾讯云[EB/OL].[2017-05-20].https://www.qcloud.com/.
[6]华为云[EB/OL].[2017-05-20].http://www.hwclouds.com/.
[7]网易云[EB/OL].[2017-05-20].https://c.163.com/.
[8]Merkel D.Docker:lightweight Linux containers for consistent development and deployment[J].Linux Journal,2014,2014(239):76-91.
[9]Richardson C.Building microservices:inter-process communication in a microservices architecture[EB/OL].[2015-07-24].https://www.nginx.com/blog/building-microservices-inter-process-communication/.
[10]Lorido-Botran T,Miguel-Alonso J,Lozano J A.Areview of auto-scaling techniques for elastic applications in cloud environments[J].Journal of Grid Computing,2014,12(4):559-592.
[11]Dutreilh X,Moreau A,Malenfant J,et al.From data center resource allocation to control theory and back[C]//IEEE International Conference on Cloud Computing,IEEE,2010:410-417.
[12]Han R,Guo L,Ghanem M M,et al.Lightweight resource scaling for cloud applications[C]//IEEEInternational Symposium on Cluster,Cloud and Grid Computing,2012:644-651.
[13]Hasan M Z,Magana E,Clemm A,et al.Integrated and autonomic cloud resource scaling[C]//IEEENetwork Operations and Management Symposium,IEEE,2012:1327-1334.
[14]Koperek P,Funika W Odzimierz.Dynamic business metrics-driven resource provisioning in cloud environments[C]//International Conference on Parallel Processing and Applied Mathematics.SpringerVerlag,2011:171-180.
[15]Chieu T C,Mohindra A,Karve A A,et al.Dynamic scaling of web applications in a virtualized cloud computing environment[C]//IEEE International Conference on e-Business Engineering,IEEE,2009:281-286.
[16]Chieu T C,Mohindra A,Karve A A,et al.Scalability and performance of web applications in a compute cloud[C]//IEEE International Conference on e-Business Engineering,IEEE,2011:317-323
[17]RightScale[EB/OL].[2017-05-20].http://www.rightscale.com/.
[18]Simmons B,Ghanbari H,Litoiu M,et al.Managing a SaaS application in the cloud using PaaS policy sets and a strategy-tree[C]//International Conference on Network and Service Management,IEEE,2011:1-5.
[19]Lorido-Botran T,Miguel-Alonso J,Lozano J A.Comparison of auto-scaling techniques for cloud environments[R].Technical Report EHU-KAT-IK,2012:1-44.
[20]Docker:What is Docker[EB/OL].[2017-05-20]https://www.Docker.com/what-Docker/.
[21]Xavier M G,Neves M V,Rose C A F D.Aperformance comparison of container-Based virtualization systems for MapReduce clusters[C]//Euromicro International Conference on Parallel,Distributed,and Network-Based Processing,IEEEComputer Society,2014:299-306.
[22]Dua R,Raja A R,Kakadia D.Virtualization vs containerization to support PaaS[C]//IEEEInternational Conference on Cloud Engineering,IEEE,2014:610-614.
[23]Felter W,Ferreira A,Rajamony R,et al.An updated performance comparison of virtual machines and Linux containers[C]//IEEE International Symposium on Performance Analysis of Systems and Software(ISPASS),IEEE,2015:171-172.
[24]Joy A M.Performance comparison between Linux containers and virtual machines[C]//Computer Engineering and Applications,IEEE,2015:342-346.
[25]Seo K T,Hwang H S,Moon I Y,et al.Performance comparison analysis of Linux container and virtual machine for building cloud[J].Advanced Science and Technology Letters,2014,66(25):105-111.
[26]Scheepers M J.Virtualization and containerization of application infrastructure:A comparison[C]//21st Twente Student Conference on IT,2014:1-7.
[27]Barham P,Dragovic B,Fraser K,et al.Xen and the art of virtualization[J].ACM SIGOPS Operating Systems Review,2003,37(5):164-177.
[28]Qumranet A K,Qumranet Y K,Qumranet D L,et al.KVM:the Linux virtual machine monitor[C]//Proc Linux Symposium,2007:225-230
[29]Lewis J,Fowler M.Microservices:a definition of this new architectural term[EB/OL].[2017-05-20].https://martinfowler.com/articles/microservices.html/.
[30]Richardson C.Introduction to microservices[EB/OL].[2015-05-19].https://www.nginx.com/blog/introduction-to-microservices/.
[31]Richardson C.Choosing a microservices deployment strategy[EB/OL].[2016-02-10].https://www.nginx.com/blog/deploying-microservices/.
[2]Google Cloud Platform[EB/OL].[2017-05-20].https://cloud.google.com/.
[3]Microsoft Azure[EB/OL].[2017-05-20].https://azure.microsoft.com/enus/?b=16.48/.
[4]阿里云[EB/OL].[2017-05-20].https://www.aliyun.com/.
[5]腾讯云[EB/OL].[2017-05-20].https://www.qcloud.com/.
[6]华为云[EB/OL].[2017-05-20].http://www.hwclouds.com/.
[7]网易云[EB/OL].[2017-05-20].https://c.163.com/.
[8]Merkel D.Docker:lightweight Linux containers for consistent development and deployment[J].Linux Journal,2014,2014(239):76-91.
[9]Richardson C.Building microservices:inter-process communication in a microservices architecture[EB/OL].[2015-07-24].https://www.nginx.com/blog/building-microservices-inter-process-communication/.
[10]Lorido-Botran T,Miguel-Alonso J,Lozano J A.Areview of auto-scaling techniques for elastic applications in cloud environments[J].Journal of Grid Computing,2014,12(4):559-592.
[11]Dutreilh X,Moreau A,Malenfant J,et al.From data center resource allocation to control theory and back[C]//IEEE International Conference on Cloud Computing,IEEE,2010:410-417.
[12]Han R,Guo L,Ghanem M M,et al.Lightweight resource scaling for cloud applications[C]//IEEEInternational Symposium on Cluster,Cloud and Grid Computing,2012:644-651.
[13]Hasan M Z,Magana E,Clemm A,et al.Integrated and autonomic cloud resource scaling[C]//IEEENetwork Operations and Management Symposium,IEEE,2012:1327-1334.
[14]Koperek P,Funika W Odzimierz.Dynamic business metrics-driven resource provisioning in cloud environments[C]//International Conference on Parallel Processing and Applied Mathematics.SpringerVerlag,2011:171-180.
[15]Chieu T C,Mohindra A,Karve A A,et al.Dynamic scaling of web applications in a virtualized cloud computing environment[C]//IEEE International Conference on e-Business Engineering,IEEE,2009:281-286.
[16]Chieu T C,Mohindra A,Karve A A,et al.Scalability and performance of web applications in a compute cloud[C]//IEEE International Conference on e-Business Engineering,IEEE,2011:317-323
[17]RightScale[EB/OL].[2017-05-20].http://www.rightscale.com/.
[18]Simmons B,Ghanbari H,Litoiu M,et al.Managing a SaaS application in the cloud using PaaS policy sets and a strategy-tree[C]//International Conference on Network and Service Management,IEEE,2011:1-5.
[19]Lorido-Botran T,Miguel-Alonso J,Lozano J A.Comparison of auto-scaling techniques for cloud environments[R].Technical Report EHU-KAT-IK,2012:1-44.
[20]Docker:What is Docker[EB/OL].[2017-05-20]https://www.Docker.com/what-Docker/.
[21]Xavier M G,Neves M V,Rose C A F D.Aperformance comparison of container-Based virtualization systems for MapReduce clusters[C]//Euromicro International Conference on Parallel,Distributed,and Network-Based Processing,IEEEComputer Society,2014:299-306.
[22]Dua R,Raja A R,Kakadia D.Virtualization vs containerization to support PaaS[C]//IEEEInternational Conference on Cloud Engineering,IEEE,2014:610-614.
[23]Felter W,Ferreira A,Rajamony R,et al.An updated performance comparison of virtual machines and Linux containers[C]//IEEE International Symposium on Performance Analysis of Systems and Software(ISPASS),IEEE,2015:171-172.
[24]Joy A M.Performance comparison between Linux containers and virtual machines[C]//Computer Engineering and Applications,IEEE,2015:342-346.
[25]Seo K T,Hwang H S,Moon I Y,et al.Performance comparison analysis of Linux container and virtual machine for building cloud[J].Advanced Science and Technology Letters,2014,66(25):105-111.
[26]Scheepers M J.Virtualization and containerization of application infrastructure:A comparison[C]//21st Twente Student Conference on IT,2014:1-7.
[27]Barham P,Dragovic B,Fraser K,et al.Xen and the art of virtualization[J].ACM SIGOPS Operating Systems Review,2003,37(5):164-177.
[28]Qumranet A K,Qumranet Y K,Qumranet D L,et al.KVM:the Linux virtual machine monitor[C]//Proc Linux Symposium,2007:225-230
[29]Lewis J,Fowler M.Microservices:a definition of this new architectural term[EB/OL].[2017-05-20].https://martinfowler.com/articles/microservices.html/.
[30]Richardson C.Introduction to microservices[EB/OL].[2015-05-19].https://www.nginx.com/blog/introduction-to-microservices/.
[31]Richardson C.Choosing a microservices deployment strategy[EB/OL].[2016-02-10].https://www.nginx.com/blog/deploying-microservices/.