TrackMe for Splunk

Three dedicated components to monitor and track your data sources' availability, quality, and latency. Detect anomalies with Machine Learning Outliers and ensure data quality through format recognition.

Track scheduled search activity, SLA compliance, and execution metrics across your Splunk environment. Monitor run times, detect failures, and ensure your critical saved searches and reports run on schedule.

Intelligent incident lifecycle management with state-aware alerts that track opening, updating, and closing. Rich HTML email notifications with embedded charts and AI-generated status reports.

Replace hardcoded alert rules with a flexible scoring system. Combined with ML-driven anomaly detection that automatically learns seasonal patterns with confidence-based evaluation.

A comprehensive REST API with an interactive explorer interface for integration and automation. Interact with every TrackMe capability programmatically or directly in native SPL through the built-in trackme command.

Automated daily backups of all KVstore records and Knowledge Objects with flexible full or partial restore operations — per tenant, per collection, or per object. Export and import archives for migration with transparent Search Head Cluster support.

Pre-built SOAR monitoring use cases with bi-directional REST API integration. Monitor playbook execution, asset health, automation broker HA, and more — with active health checks and automated response capabilities.