Software Performance Analytics in the Cloud
Authors: 
Kingsum Chow, Wanyi ZhuAuthors Info & Claims
Kingsum Chow, Wanyi ZhuAuthors Info & ClaimsPages 419 - 421
Abstract
The emergence of large-scale software deployments in the cloud has led to several challenges: (1) measuring software performance in the data center, and (2) optimizing software for resource management. This tutorial addresses the two challenges by bringing the knowledge of software performance monitoring in the data center to the world of applying performance analytics. It introduces data transformations for software performance metrics. The transformations enable effective applications of analytics. This tutorial starts with software performance in the small and ends with applying analytics to software performance in the large. In software performance in the small, it summarizes performance tools, data collection and manual analysis. Then it describes monitoring tools that are helpful in performance analysis in the large. The tutorial will guide the audience in applying analytics to performance data obtained by common tools. This tutorial describes how to select analytical methods and what precautions should be taken to get effective results.
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Owen Vallis, Jordan Hochenbaum, Arun Kejariwal, A novel technique for long-term anomaly detection in the cloud, Proceedings of the 6th USENIX conference on Hot Topics in Cloud Computing, p.15--15, June 17--18, 2014, Philadelphia, PA
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Chengwei Wang, Krishnamurthy Viswanathan, Lakshminarayan Choudur, Vanish Talwar, Wade Satterfield, and Karsten Schwan. 2011. Statistical techniques for online anomaly detection in data centers. In Proceedings of the IFIP/IEEE International Symposium on Integrated Network Management (IM'11). IEEE, 385--392.
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Kingsum Chow, Pooja Jain and Khun Ban, "Tutorial: Java Application Performance in the Data Center, Data Collection and Analysis" CMG imPACt 2016 Conference. November 7--10, 2016 in La Jolla, California.
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Kingsum Chow, Li Chen and Colin Cunningham, "How We Coach Performance Engineers to Adopt Data Science in Reproducible Analytics", Intel Analytics Summit, March 22--24, 2016, Santa Clara, California.
[6]
Kingsum Chow and Pranita Maldikar "Applying Analytics to Workload Optimized Systems" {best paper award} presented at the FastPath workshop, held in conjunction with the IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), March 23-25, 2014.
[7]
Keerthi Palanivel, Kingsum Chow, Khun Ban and David Lilja, "A Stepwise Approach to Software-Hardware Performance Co-Optimization Using Design of Experiments", Computer Measurement Group Performance and Capacity 2013, Nov 5th to 7th, La Jolla, California, USA.
[8]
Shruthi Deshpande, Kingsum Chow, Peng-fei Chuang and Latifur Khan, "Big Data Analysis to Characterize Workload using Machine Learning Algorithms for High Dimensional Performance Data", Computer Measurement Group Performance and Capacity 2013, Nov 5th to 7th, La Jolla, California, USA.
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Index Terms
- Software Performance Analytics in the Cloud
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Information & Contributors
Information
Published In
April 2017
450 pages
ISBN:9781450344043
DOI:10.1145/3030207
- General Chairs:
- Walter Binder,
- Vittorio Cortellessa,
- Program Chairs:
- Anne Koziolek,
- Evgenia Smirni,
- Meikel Poess
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Association for Computing Machinery
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Published: 17 April 2017
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- Research-article
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ICPE '17
Sponsor:
ICPE '17: ACM/SPEC International Conference on Performance Engineering
April 22 - 26, 2017
L'Aquila, Italy
Acceptance Rates
ICPE '17 Paper Acceptance Rate 27 of 83 submissions, 33%;
Overall Acceptance Rate 252 of 851 submissions, 30%
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