Automated Root Cause Analysis Neural Network Assisted
ARCANNA is a custom built Elastic plugin capable of identifying with increased accuracy the probable root cause of issues that arise within the entire infrastructure stack.
Making use of the Elastic Stack’s capabilities to ingest and store large quantities of data from anywhere within the infrastructure we developed a supervised machine learning algorithm to discern the false positives and connected events from the real issues.
ARCANNA was built to be efficient and adaptable to the environment in which it is running. Thus we gave users the ability to influence the results from ARCANNA and effectively enable it to adapt to each infrastructure and organization as is required.
Furthermore ARCANNA ties in with the Elastic Stack Common Schema which is a common set of fields and naming guidelines for data ingestion into Elastic giving users the ability to quickly and efficiently start analyzing their hybrid infrastructure.
ARCANNA will be showcased at this year’s Elasticon on 13th of November! Read more about the event and how you can register here.
Installation is done similar to other existing Elastic plugins from the command line.
Adaptable to any organization’s IT environment by enabling user feedback
A user friendly UI enables anyone to create jobs and give feedback.