Monitor System Logs → AI Anomaly Detection → Auto-Create Incident Tickets

Configure Datadog agents on your Ubuntu servers to collect system logs, application logs, and performance metrics. Set up log parsing rules for common Linux log formats and create custom dashboards to visualize log patterns. Enable real-time log streaming and configure retention policies for historical analysis.

Configure Datadog webhooks to send log events to your analysis pipeline when specific conditions are met (error rate spikes, unusual patterns, or custom triggers). Set up filters to focus on critical logs and reduce noise, ensuring only relevant events trigger the AI analysis.

Use OpenAI's API to analyze incoming log data for patterns that indicate potential issues. Configure prompts that understand common Linux system problems, security concerns, and performance degradation patterns. The AI should classify severity levels, suggest potential root causes, and recommend initial troubleshooting steps.

Set up Zapier to receive AI analysis results and determine the appropriate response based on severity level and issue type. Configure routing logic that escalates critical issues immediately while grouping related minor issues to avoid alert fatigue.

Automatically create PagerDuty incidents with detailed information from the AI analysis, including log excerpts, suspected root causes, and recommended actions. Configure escalation policies and on-call rotations to ensure incidents reach the right team members. Include severity levels and tags for efficient incident management.