There is a push in the enterprise towards facilitating processes from best practice frameworks (such as the IT Infrastructure Library (ITIL)) to make them more repeatable, efficient and cost-effective. Best practice processes provide descriptive, high level guidelines rather than prescriptive, precise process model definitions. They are meant to be followed by people and may be adapted and enacted differently in various realizations. Currently, ITIL processes are either supported by tools that hard code an interpretation of the process logic, or followed by people using productivity tools. This is inefficient because existing tools hardcode a rigid logic of the processes, and do not support collaborative and flexible realizations of processes. Moreover, there is a risk of information loss when people using rigid productivity tools, and are forced to collaborate outside of those tools. In this paper, we present a conversation-centered approach and a tool that enables dynamic and flexible definition and enactment of best practice processes in a collaborative and interactive manner. We address the issue of information loss by using the concept of a conversation as a container of information about the interactions among people in the context of a process. A conversation is backed with a semi-structured process model and process templates to support flexible and adaptive process realization. We showcase the approach using an illustrative use case in incident and problem management, based on best practice processes from ITIL.

Despite the importance of storage in enterprise computer systems, there are few adequate tools to design and configure a storage system to meet application data requirements efficiently. Storage system design involves choosing the disk arrays to use, setting the configuration options on those arrays, and determining an efficient mapping of application data onto the configured system. This is a complex process because of the multitude of disk array configuration options, and the need to take into account both capacity and potentially contending I/O performance demands when placing the data. Thus, both existing tools and administrators using rules of thumb often generate designs that are of poor quality.This article presents the Disk Array Designer (DAD), which is a tool that can be used both to guide administrators in their design decisions and to automate the design process. DAD uses a generalized best-fit bin packing heuristic with randomization and backtracking to search efficiently through the huge number of possible design choices. It makes decisions using device models that estimate storage system performance. We evaluate DAD's designs based on traces from a variety of database, filesystem, and e-mail workloads. We show that DAD can handle the difficult task of configuring midrange and high-end disk arrays, even with complex real-world workloads. We also show that DAD quickly generates near-optimal storage system designs, improving in both speed and quality over previous tools.

This paper describes the design, implementation, and evaluation of a Federated Array of Bricks (FAB), a distributed disk array that provides the reliability of traditional enterprise arrays with lower cost and better scalability. FAB is built from a collection of bricks, small storage appliances containing commodity disks, CPU, NVRAM, and network interface cards. FAB deploys a new majority-voting-based algorithm to replicate or erasure-code logical blocks across bricks and a reconfiguration algorithm to move data in the background when bricks are added or decommissioned. We argue that voting is practical and necessary for reliable, high-throughput storage systems such as FAB. We have implemented a FAB prototype on a 22-node Linux cluster. This prototype sustains 85MB/second of throughput for a database workload, and 270MB/second for a bulk-read workload. In addition, it can outperform traditional master-slave replication through performance decoupling and can handle brick failures and recoveries smoothly without disturbing client requests.

A federated array of bricks is a scalable distributed storage system composed from inexpensive storage bricks. It achieves high reliability with low cost by using erasure coding across the bricks to maintain data reliability in the face of brick failures. Erasure coding generates n encoded blocks from m data blocks (n > m) and permits the data blocks to be reconstructed from any m of these encoded blocks. We present a new fully decentralized erasure-coding algorithm for an asynchronous distributed system. Our algorithm provides fully linearizable read-write access to erasure-coded data and supports concurrent I/O controllers that may crash and recover. Our algorithm relies on a novel quorum construction where any two quorums intersect in m processes.