AIOps! Finding Incidents in the Haystack of Alerts
The challenge of managing alerts and incidents looms large in the realm of AIOps (Artificial Intelligence for IT Operations). Surprisingly, traditional approaches often rely on rule-based engines, raising the question, "Where is AI?".
In today's complex IT landscape, organizations face an avalanche of alerts stemming from diverse sources like Kubernetes clusters, cloud providers, and third-party tools. These alerts often lack context, inundating teams with noise and making it arduous to discern crucial incidents from the noise. This deluge not only overwhelms IT teams but also hampers incident response and resolution times, ultimately impacting business continuity.
At Keep, we're spearheading a paradigm shift with our AI automated alert correlation engine. Unlike conventional rule-based systems, our approach leverages state-of-the-art LLM models trained on real-world incident data.
Our AI engine acts as a discerning needle, swiftly identifying and correlating incidents in real-time. By automating the correlation process, we alleviate the burden on IT teams, enabling them to focus their efforts on resolving critical issues promptly. Furthermore, our AI engine continuously learns and evolves, adapting to shifting patterns and emerging threats, thereby enhancing its efficacy over time.
