AI Operations
Investigate failures, interpret evidence and keep AI-powered applications reliable.
Open any lesson to see its learning objective. The lesson activities are being prepared.
Triage and Observability
Issue Intake and Severity
Turn a vague user complaint into a clear initial incident description.
Reproducing a Problem Safely
Prepare controlled steps with expected and actual results.
Reading Logs, Traces and Metrics
Recognize useful timestamps, request IDs and failure signals.
Model, Integration or Infrastructure?
Separate likely origins before choosing a fix.
Common Incident Scenarios
Client-Side 4xx Error Investigation
Identify mistakes involving inputs, authentication or permissions.
Rate-Limit Incidents and HTTP 429
Choose safe mitigation for bursts and exceeded limits.
Server Errors: 500, 502 and 503
Interpret internal failures, gateway issues and temporary outages.
Timeouts, Retries and Duplicate Work
Prevent retry loops and unintended repeated actions.
Operational Improvement
Monitoring, Alerts and Health Checks
Read basic service health indicators and meaningful alerts.
Billing and Unexpected Usage
Investigate abnormal consumption using example reports.
Bug Reports, Regression Checks and QA
Write evidence-based bug reports and confirm improvements.
Incident Review and Prevention
Create a concise post-incident review with actions and ownership.