"I keep coming back for the technical content and the personal networking opportunities. I attend for career development."
LISA '13 Attendee
"I use LISA to benchmark the SA activities in my company."
LISA '13 Attendee
"LISA is where professionals share what's hot in designing, building, and maintaining critical systems."
Tom Limoncelli, author, speaker, and system administrator
"LISA is where I find direction for evolving the my core professional skills."
LISA '13 Attendee
"LISA is the conference that I send my system administrators to so they can bring the latest tools and techniques back to the rest of the team. Much of our current environment can be traced directly back to LISA."
Cory Lueninghoener, Deputy Group Leader of Production High Performance Computing at Los Alamos National Laboratory
"LISA is the conference that I send my system administrators to so they can bring the latest tools and techniques back to the rest of the team. Much of our current environment can be traced directly back to LISA."
Cory Lueninghoener, Deputy Group Leader of Production High Performance Computing at Los Alamos National Laboratory
"LISA is where professionals share what's hot in designing, building, and maintaining critical systems."
Tom Limoncelli, author, speaker, and system administrator
"Information from LISA helps us push the envelope on automation and scaling, allowing a team of four to manage over 3000 Firefox build and test systems running 15 different operating systems."
Amy Rich, Manager of Release Engineering Operations at Mozilla
"LISA is the place where industry best practices and cutting-edge research come together to advance system administration."
Rukma Talwadker and Kaladhar Voruganti, NetApp Inc.
Abstract:
Historically, traces have been used by system designers for designing and testing their systems. However, traces are becoming very large and difficult to store and manage. Thus, the area of creating models based on traces is gaining traction. Prior art in trace modeling has primarily dealt with modeling block traces, and file/NAS traces collected from virtualized clients which are essentially block I/O’s to the storage server. No prior art exists in modeling file traces. Modeling file traces is difficult because of the presence of meta-data operations and the statefulness NFS operation semantics.
In this paper we present an algorithm and a unified framework that models and replays NFS as well SAN workloads. Typically, trace modeling is a resource intensive process where multiple passes are made over the entire trace. In this paper, in addition to being able to model the intricacies of the NFS protocol, we provide an algorithm that is efficient with respect to its resource consumption needs by using a Bloom Filter based sampling technique. We have verified our trace modeling algorithm on real customer traces and show that our modeling error is quite low.
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