Opportunities and Challenges for Self-Aware Virtualized Infrastructure Management
In the past decade, the information technology (IT) industry experienced a paradigm shift as computing resources became available to businesses and individuals as a utility through cloud based services. The wide adoption of server virtualization technologies has laid a foundation for both private and public cloud environments. The benefits of virtualized infrastructures are multifaceted, including easier deployment, elastic capacity, higher availability, higher resource utilization, and lower energy cost. At the same time, it brings new challenges to resource management and service level assurance as many applications share the same virtualized infrastructure. These challenges make it impossible for human administrators to carry out monitoring, anomaly detection, performance analysis, and problem remediation on a 24x7 basis. On the other hand, they present unique opportunities for applying feedback control and statistical learning based techniques to developing model-based, self-aware management frameworks and solutions. There has been a great deal of success in this area in the last several years, but many problems remain. In this talk, She'll highlight some of open research problems and related technical challenges, in hope to attract more innovative ideas and solutions from a larger community of researchers and practitioners.
Xiaoyun Zhu is a Staff Engineer in the VMware Cloud Resource Management group, focusing on developing automated resource and performance management solutions for virtualized data centers and cloud infrastructures. Her general interests are in applying control theory, optimization, algorithms, statistical analysis and simulation to IT systems and services management and automation. Prior to VMware, she worked as a Senior Research Scientist at Hewlett Packard Labs for 8 years. She has co-authored over 50 refereed papers in journals and conference proceeding, and holds 16 patents. She has been a program committee member for a number of technical conferences, including ICAC, IM, NOMS, CNSM, MASCOTS, and SIGMETRICS, and an associated editor for the Journal of Network & Systems Management. Xiaoyun received her dual B.S. in Automation and Applied Mathematics from Tsinghua University in 1994, and her Ph.D. in Electrical Engineering from California Institute of Technology in 2000..
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