BMC Helix AIOps 23.2
BMC Helix AIOps reduces the mean time to resolve (MTTR) issues and maximizes service performance and availability by using tools that include monitoring, advanced anomaly detection, AI/ML-based event management and root cause isolation, open integrations, and intelligent automation.
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.
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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June 14, 2023 | Enhancements included in this release:
| 23.2.02 enhancements and patches |
May 08, 2023 | Enhancement included in this release: | 23.2.01 enhancements and patches |
April 07, 2023 | Enhancements included in this release:
| 23.2 enhancements and patches |
March 14, 2023 | Enhancements included in this release: Simplified user experience for the following areas:
| 23.1.02 enhancements and patches |
February 03, 2023 | Enhancement included in this release: Enable dark theme | 23.1.01 enhancements and patches |
January 12, 2023 | Enhancements included in this release:
| 23.1 enhancements and patches |
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Related release notes
The following links provide updates about the integrated BMC Helix AIOps products:
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BMC Helix Developer Tools and BMC Helix Intelligent Integrations release notes
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BMC Helix Operations Management release notes
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BMC Helix Portal release notes
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BMC TrueSight Operations Management release notes
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BMC Helix IT Service Management release notes
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BMC Helix Discovery release notes
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BMC Helix Intelligent Automation release notes
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. Assess the service health, do root cause analysis, and discover health insights. 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 happent. |
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. |
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