With Robotic Data Automation (RDA) Log Analytics Pack, you can get actionable insights and analytics from logs and alerts generated by your IT workloads and microservices running in any environment.
Example Use Cases
Splunk log analytics
If you microservices are running on Kubernetes/CloudFoundry/OpenShift etc. and their logs are sent to Splunk, you can get extended log retentio for ML model training, comprehensive log analytics to identify top chatty source, trends, related log clusters and optimization suggestions.
Jira Ticket Analysis
Ingest historical and live tickets from Jira to find IT blind spots, assess problem areas or gain new insights that help proactively identify problematic microservices and iteratively reduce overall ticket volume
Unsupervised Log Clustering to Identify and Forecast Top Problems
Logs are mostly unstructured or semi-structured at best. Using innovative ML pre-processing and unsupervised clustering techniques you can accurately identify groups of related logs and problem areas.