AIOps platforms enhance IT operations by combining big data, machine learning and visualization to create actionable insights.
Compared to more traditional monitoring tools, AIOps seeks to reduce noise (false alarms or redundant events), capture anomalies on a dynamic basis, provide a better causality trail, to help identify incident causes, then extrapolate to future events and take actions to resolve problems, either automatically or with IT staff approval.
A sampling of AIOps platforms would include a large number of firms, ranging from Anodot to VuNet. These suppliers have the ability to ingest data from multiple sources, including historic and real-time streaming, and/or have different offerings that include proprietary, open source, free and commercialized versions, including deployment that cuts across on-premises and SaaS-based options.
AIOps platforms have historically focused on a single data source like logs or metrics. New data stores include digital experience data, order data, sentiment data from social media, service desk requests and statuses and account activity.
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