New InsightFinder innovations to reduce MTTR: Knowledge Base and Active Learning

TL; DR: InsightFinder Human Insight + Active Learning FTW

Knowledge Base 

InsightFinder makes it easy for users to access, analyze, and reference all incidents per system through their life cycle with the InsightFinder Knowledge Base. It aggregates failure pattern records into Knowledge Bases by system and organization. As a result, InsightFinder Knowledge Base records can be used by operators to train AI models and observe how specific incidents impact system health. 

To enhance the benefits of collective knowledge, InsightFinder users at a company can view incidents that have occurred within their systems.

Active Learning

InsightFinder users can now leverage active learning to enhance unsupervised machine learning with their human insights to make the most accurate incident predictions. For each Knowledge Base row, users can add “Confirmed”, “Ignored”, and modify thresholds to determine when InsightFinder does or does not use rules. By allowing users to combine human insight with active learning, InsightFinder provides the most accurate way to predict and prevent future incidents. 

Because human feedback combined with active learning helps models improve over time, InsightFinder Knowledge Bases are the most reliable and best source of truth for DevOps and AIOps tools. 

To see a demo of how these changes can help your team, request information here.