About This Architecture

AI-driven major incident management architecture integrating Datadog monitoring, Azure event ingestion, and Ivanti ITSM to automate detection, classification, and resolution of infrastructure incidents. Real-time metrics, logs, and traces flow from Windows/Linux servers, applications, and databases through Datadog agents into Azure Event Hub and Service Bus, where Stream Analytics and Azure ML detect anomalies and generate root-cause analysis via Azure OpenAI. Classified incidents automatically create tickets in Ivanti ITSM with P1/P2 priority, SLA tracking, and escalation rules, while Azure Automation triggers runbooks for auto-remediation, patching, and infrastructure scaling. Teams notifications, Power BI dashboards, and Azure Sentinel provide real-time visibility and post-incident review workflows. Fork this diagram on Diagrams.so to customize incident thresholds, add your CMDB integrations, or adapt runbook logic to your environment.

People also ask

How can I automate major incident detection, classification, and remediation across multi-cloud infrastructure using AI and ITSM?

This diagram shows a six-layer architecture where Datadog agents collect metrics, logs, and traces from servers and applications, Azure Stream Analytics and ML detect anomalies in real-time, Azure OpenAI generates root-cause analysis, and Ivanti ITSM auto-creates prioritized tickets with escalation rules. Azure Automation runbooks then trigger infrastructure fixes, patching, and scaling, while Tea