High-Confidence SLA Assurance for Cloud Computing Systems and Services

1. High-Confidence SLA Assurance for Cloud Computing Systems and Services Project Lead: Farokh B. Bastani, I-Ling Yen, Krishna Kavi, and Jeff Tian Date: April 7, 2011

2. Problem Description • Emerging cloud computing paradigm enables • On-demand access to storage, computing, software, and physical resources • Integrated capabilities of a large spectrum of networked services and resources for realizing tasks that are far beyond current practices  Need SLA to enhance cloud system usability and dependability • Existing SLA (service level agreement) research: Siloed • SLA model: Consider agreement for each QoS aspect independently • Client perspective • Need to establish SLAs one service at a time, lacking an end-to-end approach for the client task that require composing multiple services/resources • Consider individual QoS aspects independently, not potential tradeoffs • Provider perspective • Each provider operates independently, lacks a collaborative concept to globally achieve high SLA assurance while maximizing resource utilization • No satisfactory solutions to security issues across all layers • Challenges: Develop a comprehensive SLA model and supporting environment

3. Proposed Solution • Perform end-to-end QoS analysis before SLAs • May need reservations to avoid new failures • Consider QoS aspects holistically and directly determine • the configuration parameters to fully control tradeoffs •  Improve SLA model to support holistic SLA client Provider 1 Resource Management Admission Control client feedback Local QoS Monitoring S R S R . . . R R Improved SLA protocol: First determine with which providers and levels of QoS Then preliminarily check the possibility of getting the SLAs Finally establish the SLAs S Service Composer Form cloud community SLA for first service • Integrated SLA Monitoring • Agent based distributed monitoring and • behavior integration • - Rule based approach, formalize SLAs • as rules, events as facts, and use reasoning • to derive the violation situations • - Consider fuzzy violation decision models • - Across providers and resource types • Proactive SLA assurance (recovery) Provider 2 SLA for second service Resource Management Admission Control . . . Fail to get agreement feedback Local QoS Monitoring R Probabilistic SLAs to collaboratively get backup resources under failure or extreme load R S S R • At each provider: • Consider strict & flexible SLAs • Develop optimal resource management • and admission control schemes • - Formulation: optimization problem with the objective of • maximizing the gain, given task completion rewards and • violation penalties and the available resources • - Admit only if positive gain • Local monitoring and online reconfiguration • - Ensure SLAs are satisfied if resources are sufficient; • if not, adjust resource decisions Provider 3 Resource Management Admission Control Provider N Resource Management Admission Control feedback Local QoS Monitoring feedback Local QoS Monitoring

4. 2011 New Project SummaryHigh-Confidence SLA Assurance for Cloud Computing Systems and Services Tasks: Comprehensive model of cloud SLAs considering correlations of QoS aspects and end-to-end QoS requirements Integrated SLA monitoring approach across providers and resource types Optimal adaptive strategies for assuring SLAs under normal and failure situations Method of assessing system-level SLAs based on component-level SLAs Layered collaborative approach for optimally achieving global SLA assurance by leveraging resources from multiple cloud domains Project Schedule: Task 3: Optimal adaptive SLA assurance Task 2: Integrated SLA monitoring Task 1: SLA model A M J J A S O N D J F M A 11 12 Research Goals: Improved SLA models and protocols to facilitate highly dependable and practically usable cloud computing Optimal supporting environment for SLA assurance considering end-to-end QoS and QoS tradeoffs and achieving local as well as global monitoring, resource management, and admission control Benefits to Industry Partners: Advanced cloud technologies to meet specified SLAs to a high degree of confidence in spite of multiple failures Enable cloud computing to be used for critical applications, including health-care systems, emergency response systems, defense systems, transportation systems, etc.