Gartner anticipates that, over the next five years, wide-scope AIOps platforms will become the de facto form-factor for the delivery of AIOps functionality as opposed to AIOps functionality embedded in a monitoring tool.
Early on, the emphasis has been on ways to:
- Reduce noise (for example, in the form of false alarms or redundant events)
- Provide better causality, which helps identify probable cause of incidents
- Capture anomalies that go beyond static thresholds to proactively detect abnormal conditions
- Extrapolate future events to prevent potential breakdowns
- Initiate action to resolve a problem (either directly or via integration)
But the ability to “act” is the future. AIOps analysis is expanding beyond its initial usage as a better solution for event correlation and analysis in IT operations, Gartner argues.
Gartner believes that AIOps will evolve into a bidirectional solution that not only ingests data for analysis, but also initiates actions based on its analysis, including:
- Alerting
- Problem triage
- CMDB population
- Run book automation
- Application release orchestration
Perhaps the fullest development of AIOps will come when pattern detection is used to detect and then alter organization behavior with respect to customer experience. In that sense, AIOps will expand to include:
- a pattern detection algorithm to improve the customer relationship process by detecting the patterns of behavior customers expressed in digital experience monitoring data. Use the machine learning algorithms in AIOps to perceive the patterns that relate user navigation with:
- Digital experience data from APM
- Order data pulled from payloads in business transactions
- Sentiment data from social media
- Service desk requests and statuses
- Account activity from the CRM system
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