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Giuliano Casale: Quality-aware DevOps for Cloud and Big data systems
CS101

Cloud computing has empowered software and system engineers with the ability to programmatically provision infrastructure resources and platform services upon demand. This feature has led in recent years to a progressive diffusion of novel architectural styles, such as microservices, and to looser boundaries between development and operations teams, fostering a widespread adoption of continuous delivery practices. In parallel to these trends, research on cloud quality-of-service management remains as intense as ever, ranging from auto-scaling controllers to system configuration auto-tuning. In this seminar, I will first review the above trends, discussing their progressive convergence into quality-aware DevOps toolchains. I will then present some of my recent and ongoing research work on open-source DevOps frameworks and underpinning modelling techniques to optimally design and operate Cloud and Big data systems.
Short bio: Giuliano Casale joined the Department of Computing at Imperial College London in 2010, where he is currently a Senior Lecturer in modeling and simulation. Previously, he worked as a research scientist at SAP Research UK and as a consultant in the capacity planning industry. He teaches and does research in performance engineering, cloud computing, and Big data, topics on which he has published more than 100 refereed papers. His recent research papers on cloud computing and performance modeling have received awards at ACM SIGMETRICS 2017, IEEE/IFIP IM 2017, and IEEE CLOUD 2015. He has been a technical program committee member for over 80 conferences and workshops, and a program co-chair for several conferences in the performance evaluation area, such as ACM SIGMETRICS/Performance. He presently serves on the editorial boards of IEEE TNSM and ACM TOMPECS and on the ACM SIGMETRICS board of directors.

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