Investigating resource interference and scaling on multitenant PaaS clouds

Platform as a Service (PaaS) clouds are capable of both transparently allocating computing resources as well as providing part of the software stack and related services to tenant applications that execute on a subset of available cloud VMs. To deal with increased load, PaaS clouds enable applications to scale out, by creating extra instances, or scale up, by adding resources to the existing instances. However, good scalability is not necessarily attainable; in this paper we investigate the reasons for this. In particular, we propose a mathematical model that describes CPU allocation per tenant depending on interference from other tenants on the same VM, which we use to make predictions and confirm them in a variety of experimental situations. Furthermore, using a set of cloud tenants that target specific resources, we propose and evaluate a methodology for profiling the resource-intensiveness of cloud applications that uses slowdown in the presence of a resource-intensive cloud burner.

[1]  Rouven Krebs,et al.  Metrics and techniques for quantifying performance isolation in cloud environments , 2014, Sci. Comput. Program..

[2]  Xi Chen,et al.  CloudScope: Diagnosing and Managing Performance Interference in Multi-tenant Clouds , 2015, 2015 IEEE 23rd International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems.

[3]  Fermín Galán Márquez,et al.  From infrastructure delivery to service management in clouds , 2010, Future Gener. Comput. Syst..

[4]  Franz J. Hauck,et al.  Component-based scalability for cloud applications , 2013, CloudDP '13.

[5]  Ian Lumb,et al.  A Taxonomy and Survey of Cloud Computing Systems , 2009, 2009 Fifth International Joint Conference on INC, IMS and IDC.

[6]  Wei-Tek Tsai,et al.  A cloud-based TaaS infrastructure with tools for SaaS validation, performance and scalability evaluation , 2012, 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings.

[7]  Elisa Bertino,et al.  Privacy preserving delegated access control in the storage as a service model , 2012, 2012 IEEE 13th International Conference on Information Reuse & Integration (IRI).

[8]  Jeanna Neefe Matthews,et al.  Quantifying the performance isolation properties of virtualization systems , 2007, ExpCS '07.

[9]  Michael J. Kavis,et al.  Architecting the Cloud: Design Decisions for Cloud Computing Service Models (Saas, Paas, and Iaas) , 2014 .

[10]  Jun Wei,et al.  Application-Level CPU Consumption Estimation: Towards Performance Isolation of Multi-tenancy Web Applications , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[11]  Ernesto Damiani,et al.  Scalability Patterns for Platform-as-a-Service , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[12]  Kenneth B. Kent,et al.  Multitenancy benefits in application servers , 2015, CASCON.

[13]  Bo Gao,et al.  A Framework for Native Multi-Tenancy Application Development and Management , 2007, The 9th IEEE International Conference on E-Commerce Technology and The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services (CEC-EEE 2007).

[14]  Wei-Tek Tsai,et al.  SaaS performance and scalability evaluation in clouds , 2011, Proceedings of 2011 IEEE 6th International Symposium on Service Oriented System (SOSE).

[15]  Rajkumar Buyya,et al.  Dynamically scaling applications in the cloud , 2011, CCRV.

[16]  Steven Hand,et al.  Self-adaptive and self-configured CPU resource provisioning for virtualized servers using Kalman filters , 2009, ICAC '09.

[17]  Calton Pu,et al.  An Analysis of Performance Interference Effects in Virtual Environments , 2007, 2007 IEEE International Symposium on Performance Analysis of Systems & Software.

[18]  Hakan Hacigümüs,et al.  Providing database as a service , 2002, Proceedings 18th International Conference on Data Engineering.

[19]  Samuel Kounev,et al.  Evaluating and Modeling Virtualization Performance Overhead for Cloud Environments , 2011, CLOSER.

[20]  M. Litoiu,et al.  Economics-Driven Resource Scalability on the Cloud , 2016, 2016 IEEE/ACM 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS).

[21]  Alexandru Iosup,et al.  On the Performance Variability of Production Cloud Services , 2011, 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.

[22]  Sanjay Chaudhary,et al.  Application Performance Isolation in Virtualization , 2009, 2009 IEEE International Conference on Cloud Computing.

[23]  Hovav Shacham,et al.  Hey, you, get off of my cloud: exploring information leakage in third-party compute clouds , 2009, CCS.

[24]  Seetharami R. Seelam,et al.  Polyglot Application Auto Scaling Service for Platform as a Service Cloud , 2015, 2015 IEEE International Conference on Cloud Engineering.

[25]  Claus Pahl,et al.  Scalable Architectures for Platform-as-a-Service Clouds: Performance and Cost Analysis , 2014, ECSA.

[26]  Wei-Tek Tsai,et al.  Testing the scalability of SaaS applications , 2011, 2011 IEEE International Conference on Service-Oriented Computing and Applications (SOCA).