AIOps & Observability

Situation Fingerprinting uses historical data to identify similar incidents, accelerating problem resolution by learning from past experiences.

Intelligent event clustering cuts through alert noise, enabling IT teams to concentrate on the critical issues that matter most.

BMC Helix’s patented Best Action Recommendation (BAR) process automatically suggests optimal resolution steps, speeding up troubleshooting.

Service health trend analysis detects systemic issues early, triggering proactive alerts that help prevent outages before they occur.

Lightweight, agentless, scalable discovery unlocks full visibility into your dynamic environment.

Automated dependency identification highlights risks and relationships between infrastructure, applications, and software, providing context for effective management.

Predefined templates and service blueprints simplify and expedite service model creation and updating.

Automated topology reconciliation ensures accuracy and consistency across various topology sources, revolutionizing IT service management for the enterprise.

Ingest a wide range of observability data types, including metrics, events, logs, traces, incidents, changes, and topology.

Ingest from both native sources and third-party tools.

Automated data reconciliation aligns data from various sources, ensuring consistent and reliable information across your domain.

Intelligent automations syncs with existing automation tools, enabling proactive issue prevention.

What-If Business Planning and Simulation enables IT teams to simulate and analyze future business conditions, supporting proactive decision-making and strategic planning.

Resource optimization recommendations help to right-size capacity and reclaim unused resources.

Service health trend analysis identifies systemic issues, allowing for quick remediation and improved reliability.

High data ingestion throughput means you can handle vast amounts of data efficiently.

Ensures regulatory compliance for regulated industries and geographies with options for specific needs, including FedRAMP, GRC, and data residency.

Availability via hyper-scaler marketplaces, providing scalability and seamless integration into existing infrastructures.

A built-In AI safety layer incorporates a domain-specific large language model (LLM) for enhanced operational safety and efficiency.