CASViD: Application Level Monitoring for SLA Violation Detection in Clouds

• Published in: 2012 IEEE 36th Annual Computer Software and Applications Conference pp. 499 - 508
• Main Authors: Emeakaroha, V. C., Ferreto, T. C., Netto, M. A. S., Brandic, I., De Rose, C. A. F.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2012
• Subjects: Application Monitoring; Cloud Resource Provisioning; Computer architecture; Electronic mail; Java; Measurement; Monitoring; Quality of service; Scalability; Service Level Agreement; SLA Management
• ISBN: 9781467319904; 1467319902
• ISSN: 0730-3157
• DOI: 10.1109/COMPSAC.2012.68

Cloud resources and services are offered based on Service Level Agreements (SLAs) that state usage terms and penalties in case of violations. Although, there is a large body of work in the area of SLA provisioning and monitoring at infrastructure and platform layers, SLAs are usually assumed to be guaranteed at the application layer. However, application monitoring is a challenging task due to monitored metrics of the platform or infrastructure layer that cannot be easily mapped to the required metrics at the application layer. Sophisticated SLA monitoring among those layers to avoid costly SLA penalties and maximize the provider profit is still an open research challenge. This paper proposes an application monitoring architecture named CASViD, which stands for Cloud Application SLA Violation Detection architecture. CASViD architecture monitors and detects SLA violations at the application layer, and includes tools for resource allocation, scheduling, and deployment. Different from most of the existing monitoring architectures, CASViD focuses on application level monitoring, which is relevant when multiple customers share the same resources in a Cloud environment. We evaluate our architecture in a real Cloud testbed using applications that exhibit heterogeneous behaviors in order to investigate the effective measurement intervals for efficient monitoring of different application types. The achieved results show that our architecture, with low intrusion level, is able to monitor, detect SLA violations, and suggest effective measurement intervals for various workloads.