Splunk IT Service Intelligence

Splunk ITSI helps you proactively prevent outages by applying machine learning to data, correlating and reducing alerts, monitoring service health, and streamlining incident management. Customers can detect, respond and resolve incidents all from one place for faster MTTD and MTTR.

A single, live view of business service performance gives visibility to relevant services and aligns ITOps and business leaders on the impact of service health. Real-time, predictive performance monitoring, AI-driven alerting and integrated IT management workflows can even help your team proactively prevent outages before they impact the business.

● Intelligent incident management to accelerate MTTR: Accelerate MTTR using real-time event correlation, automated incident prioritization and integrations with IT service management (ITSM) tools like ServiceNow.

○ Integrated event management, incident response and remediation: Create a ticket, run a script or contact a team from one dashboard. Resolve an incident without switching to another tool.

○ Reduce alert noise by 95% with real-time event clustering powered by machine learning.

○ Respond to the most urgent incidents first with Episode Review. Events are automatically grouped and prioritized by business impact and service health.

● Business and service level monitoring for end-to-end visibility: Monitor business and service performance, not just individual systems. Protect business service-level agreements with dashboards to monitor service health, troubleshoot alerts and perform root cause analysis.

○ Monitor the health score of a critical services and drill down into an incident to remediate, all from one dashboard

○ Entity integrations: Get started monitoring your environment quickly with OOTB workflows and content that auto-detect new data sources and relevant data to collect for operating systems, virtual infrastructures, containers, and cloud services

○ Analyze raw data at full-fidelity, and alert on true outliers, not averages of averages

● Machine Learning and Predictive Analytics to prevent issues before they impact customers: Use advanced analytics like anomaly detection, adaptive thresholding and predictive health scores to monitor KPI data and help prevent issues before they impact your business.

○ Predictive analytics: prevent service degradations in advance using machine learning algorithms and historical service health scores.

○ Real-time, automated event correlation triggers alerts as data enters the system, using out-of-the-box machine learning policies to reduce alert noise by over 90%. Adaptive thresholding: Set fixed or adaptive thresholds to enable alerts only when behavior strays from normal. Machine learning algorithms automatically update thresholds based on observed behavior so your alerts don’t become stale.