BMC Helix AIOps 22.4


BMC Helix AIOps 22.4

BMC Helix AIOps is a multi-layered technology platform that leverages big data to automate and enhance IT operations through analytics, artificial intelligence (AI), and machine learning (ML). It uses predictive capabilities to proactively improve the performance and availability of IT services across multi-cloud and hybrid environments. BMC Helix AIOps uses monitoring, advanced anomaly detection, AI/ML-based event management and root cause isolation, open integrations, and intelligent automation to reduce the mean time to resolve (MTTR) issues and maximize service performance and availability.

Release notes and notices Updated 03 Apr 2025

Learn what’s new or changed for BMC Helix AIOps, including new features, urgent issues, documentation updates, and fixes or patches.

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Date

Summary

Reference

December 09, 2022

Enhancements included in this release:

  • View consolidated insights summary
  • View CIs of same kind as a group node in the topology map
  • Advanced filters for viewing Situations

November 14, 2022

Enhancements included in this release:

  • Discover insights for incidents from services
  • View child services associated with a parent service

October 10, 2022

Enhancements included in this release:

  • View Service Insights for events
  • Predict service outages proactively
  • View natural language-based Situation summary
  • View Situations in the Impacting Events panel
  • View metrics with their display names in the Performance View graph
  • Service health indicator improvements
  • Trigger automation from the event operations
  • View the automation history
  • View automation requests

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Related release notes

The following links provide updates about the integrated BMC Helix AIOps products:

Onboarding and implementing

Set up users and assign permissions, configure third-party integrations, and start monitoring key performance indicators, services, and situations.

Monitoring key performance indicators and entities

Get a consolidated health summary of key performance indicators and entities.

Monitoring service health and performing causal analysis

Monitor services to assess the service health and perform root cause isolation of impacted services.

Monitoring and investigating situations

Monitor and investigate ML-based situations for analysis and remediation.

Predicting and proactively resolving service outages

Predict service outages that helps in identifying and fixing issues before they happen.

Administering

Understand roles and permissions, enable AIOps features and notifications, model service blueprints and model services.

Remediating events for services and situations

Run automation actions to remediate open events for services and situations.

Troubleshooting

Resolve common issues or errors, review logs, or contact Support.
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