Scalability and performance of a virtualized SAP system

Enterprise resource planning systems (ERP), like SAP systems, build the backbone of the business processes in today’s large enterprises. This is why a weak performance of a SAP system tremendously decreases the performance of the user and thus of the enterprise. Today many SAP hosting providers make use of virtualization techniques, but disregard the impact of such solutions. In this paper we focus on the impact of virtualization solutions on the performance of SAP systems and follow a quantitative approach to ascertain several benchmark results. We make four contributions: 1) On the basis of a quantitative investigation we give a recommendation how to configure a SAP system for heavy workload. The recommendation helps to avoid hardware resource shortage. 2) We show that the average performance of a SAP system increases up to +2% if a container-based virtualization solution is used. 3) We show that the performance of a SAP system is decreased up to -33% if a Xen-based virtualization solution is used. 4) On the basis of the quantitative results we give recommendations for a new sizing process in order to meet the requirements for virtualized SAP systems

OPTIMIZING SERVER CONSOLIDATION FOR ENTERPRISE APPLICATION SERVICE PROVIDERS

In enterprise application environments, hardware resources show averagely low utilization rates due to a provisioning practice that is based on peak demands. Therefore, the consolidation of orthogonal workloads can improve energy efficiency and reduce total cost of ownership. In this paper, we address existing workload consolidation potential by solving a bin packing problem, where the number of servers is to be minimized. Since dynamic workloads, gathered from historical traces, and priorities of running services are considered, we formulate the Dynamic Priority-based Workload Consolidation Problem (DPWCP) and develop solution algorithms using heuristics and metaheuristics. Relevance is pointed out by an analysis of service resource demands and server capacities across four studied cases from productively operating enterprise application service providers. After a classification of related work, seven algorithms were developed and evaluated regarding their exploited optimization potential and computing time. Best results were achieved by a best-fit approach that uses a genetic algorithm to optimize its input sequence (GA_BF). When applying the GA_BF onto the four studied cases, average utilization rates could be increased from 23 to 63 percent within an average computing time of 22.5 seconds. Therefore, the overall server capacity was reduced significantly by up to 83%

Storage Virtualization Promises Agility in the Data Center

Data storage and protection has moved to the forefront of Information Technology solutions because the business value of data has gained in rank and importance in the world of internet commerce. Modern business models are built around instant and continuous data availability and they would not be able to function without this quality. This level of data availability requires data storage technologies to be of increased flexibility and higher performance. However the more sophisticated technologies pose a greater challenge to the architects of data storage solutions who are required to evaluate products of much higher complexity and administrators who need to manage and monitor these installations. New tool sets are required to leverage the promise of the storage virtualization technologies and extract their full potential for an agile data center. New tool sets for storage virtualization will bring the IT organizations into the position of data service provider for the business groups

The Contemporary Affirmation of Taxonomy and Recent Literature on Workflow Scheduling and Management in Cloud Computing

The Cloud computing systemspreferred over the traditional forms of computing such as grid computing, utility computing, autonomic computing is attributed forits ease of access to computing, for its QoS preferences, SLA2019;s conformity, security and performance offered with minimal supervision. A cloud workflow schedule when designed efficiently achieves optimalre source sage, balance of workloads, deadline specific execution, cost control according to budget specifications, efficient consumption of energy etc. to meet the performance requirements of today2019; svast scientific and business requirements. The businesses requirements under recent technologies like pervasive computing are motivating the technology of cloud computing for further advancements. In this paper we discuss some of the important literature published on cloud workflow scheduling