Name
Abstract | ||
|---|---|---|
Automated management is critical to the success of cloud computing, given its scale and complexity. But, most systems do not satisfy one of the key properties required for automation: predictability, which in turn relies upon low variance. Most automation tools are not effective when variance is consistently high. Using automated performance diagnosis as a concrete example, this position paper argues that for automation to become a reality, system builders must treat variance as an important metric and make conscious decisions about where to reduce it. To help with this task, we describe a framework for reasoning about sources of variance in distributed systems and describe an example tool for helping identify them. |
Year | Venue | Keywords |
|---|---|---|
2012 | HotCloud | key property,automated management,position paper,cloud computing,automated diagnosis,low variance,conscious decision,concrete example,automation tool,automated performance diagnosis,example tool |
Field | DocType | Citations |
Predictability,Software engineering,Simulation,Computer science,Position paper,Automation,Recipe,Cloud computing | Conference | 2 |
PageRank | References | Authors |
0.36 | 25 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Raja R. Sambasivan | 1 | 223 | 13.33 |
| Gregory R. Ganger | 2 | 4560 | 383.16 |