The highly complex nature of today’s modern cloud-based distributed applications challenge monitoring approaches. To address this, your teams might be exploring algorithmic IT and artificial intelligence as the means to detect and predict problems faster while prescribing automated self-healing and recovery processes.
By adopting a unified data model dynamically built using a time-journaled directed graph of attributed objects, your teams can have the analytical foundation upon which to collect, group, correlate and visualize more complex performance conditions spanning applications, infrastructure and networks.
In this white paper, you’ll discover why CA’s unified data model enables teams to gain complete visibility across modern application environments. Open, extensible, ontology-agnostic and using time as a primary dimension, this dynamic model allows your teams to purposefully apply artificial intelligence (AI) and machine learning (ML) to drive substantive improvements in application performance without sacrificing speed.