Speaker
Mr
Andrew Baranovski
(FNAL)
Description
In a shared computing environment, activities orchestrated by workflow management systems often need to span organizational and ownership domains. In such a setting, common tasks, such as the collection and display of metrics and debugging information, are challenged by the informational entropy inherent to independently maintained and owned software sub-components. Because such information pool is often disorganized, it becomes a difficult target for business intelligence analysis i.e. troubleshooting, incident investigation, and trend spotting.
The Metrics Correlation and Analysis Service (MCAS) provides an integral solution for system operators and users to uniformly access, transform, and represent disjoint metrics, generated by distributed middleware or user services. The proposed software infrastructure assists with indexing and navigation of existing metrics and it supplies tools and services to define and store other quantifiable data. The Project reuses existing monitoring and data collection software deployments, with the goal of presenting a unified view of metrics data.
This paper discusses the MCAS system and places special emphasis on applying integration technologies to assist with the process of formalizing the interaction of users with end applications.
| Presentation type (oral | poster) | oral |
|---|
Primary author
Mr
Andrew Baranovski
(FNAL)
Co-authors
Mrs
Eileen Berman
(FNAL)
Dr
Gabrielle Garzoglio
(FNAL)
Mr
Parag Mhashilkar
(FNAL)
Dr
Ted Hesselroth
(FNAL)
