Learn to explain failed requests, measure application health, observe alarms and identify resource changes. You will use CloudWatch Logs, CloudWatch metrics and CloudTrail to investigate small operational incidents.
Five guided labs introduce the signals before an independent alarm-repair challenge. Supplied application fixtures let you focus on observation and diagnosis.
What You Will Learn
- Find a failed request in logs using its request ID
- Publish request and error counts and measured handler latency
- Select metric dimensions that separate applications
- Observe an alarm trigger and recover from actual request results
- Trace a management action to its actor, resource and time
- Combine logs and metrics to diagnose an incident
- Repair an alarm that watches the wrong application
Who This Course Is For
This course is for AWS beginners, developers and aspiring operators who want a practical introduction to application observation and audit evidence.
Prerequisites: Start with Get Started with AWS on LabEx in AWS Foundations for Beginners. Use the Foundations lessons on caller identity and Parameter Store before the audit lab. The labs below identify their own log, metric and alarm prerequisites.
Learning environment: All activities run in a provided browser-based LabEx Linux environment. Use Terminal for AWS CLI commands and AWS View, next to Terminal, to inspect the same resource and application state. Tools and the connection are prepared; you do not need a personal AWS account or access keys. Each lab starts independently in a fresh VM.
Frequently Asked Questions
How are logs, metrics, alarms and audit history different?
Logs describe events; metrics summarize measured quantities over time; alarms evaluate a selected metric against a policy. Management history records the actor, action, resource and time of a control-plane operation. Combine the signals to explain an incident.
Does an OK alarm prove the application is healthy?
No. Missing-data treatment can produce OK. Check actual requests and the intended metric dimensions. Sum helps with counts; Average describes measured handler latency, not percentile latency. Earlier failures remain in window totals, so use a new request ID to confirm recovery.
Are the short alarm periods a production recommendation?
No. High-resolution 10-second periods make transitions observable in these exercises. Retention, resolution, periods and missing-data treatment affect behavior and cost. See CloudWatch concepts and alarm evaluation.
Does cleanup erase all historical evidence?
No. Deleting a resource does not erase its audit record, and existing metric datapoints have no individual delete API. Stop publication and remove exact owned resources, confirm inventory and then remove credentials.
Do I need the whole course before Lambda?
The first request-log lab provides the log foundation for Lambda. SNS delivery, X-Ray tracing and a full production observability stack are outside this course.
