Report Open Access

Machine Learning applications on OpenStack log data analysis

Ravi Charan Nudurupati

Dublin Core Export

<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Ravi Charan Nudurupati</dc:creator>
  <dc:description>A massive amount of data is generated by the Openstack cloud services in the format of service logs. Besides timestamps and log level fields, these logs contain additional information useful for pattern analysis. Unfortunately, this information is generally exposed in semi-structured text format, not allowing direct analysis without additional munging of the data. Traditional approaches to extract information from those fields are rule-based, mainly applying regular expressions upon knowledge of the text structure. These approaches require a pre-knowledge of all text patterns and are not scalable with the growth of the services. This report proposes a solution that is a mixture of the MinHash Locality Sensitive Hashing and the DB scan algorithm for data clustering. 
  <dc:subject>CERN openlab</dc:subject>
  <dc:subject>Summer Student Programme</dc:subject>
  <dc:title>Machine Learning applications on OpenStack log data analysis</dc:title>
All versions This version
Views 7777
Downloads 5858
Data volume 70.9 MB70.9 MB
Unique views 6464
Unique downloads 5050


Cite as