Contextual linking between workflow provenance and system performance logs

When executing scientific workflows, anomalies of

the workflow behavior are often caused by different issues such

as resource failures at the underlying infrastructure. The provenance

information collected by workflow management systems

only captures the transformation of data at the workflow level.

Analyzing provenance information and apposite system metrics

requires expertise and manual effort. Moreover, it is often timeconsuming

to aggregate this information and correlate events

occurring at different levels of the infrastructure. In this paper,

we propose an architecture to automate the integration among

workflow provenance information and performance information

from the infrastructure level. Our architecture enables workflow

developers or domain scientists to effectively browse workflow

execution information together with the system metrics, and

analyze contextual information for possible anomalies.