Observability with AWS
summary
AWS shows how a production observability stack built on CloudWatch metrics, CloudWatch Logs and X‑Ray traces reduces Mean Time to Identification by letting teams correlate logs, metrics and traces without hopping tools. The demo uses ServiceLens and Metrics Explorer, X‑Ray sampling and Synthetics canaries (demoed running every 1 minute with screenshots and logs), ADOT/OpenTelemetry export to Amazon Managed Grafana and Elasticsearch, composite alarms and anomaly detection; data is immutable and can be KMS‑encrypted.
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chapters (10)
- 0:00Intro
- 0:21What is observability Observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs
- 1:12Typical troubleshooting workflow
- 3:13Observability maturity level
- 7:19AWS observability tools
- 11:10Why choose AWS observability services? Designed for enterprise scale and security
- 14:42Who can benefit from cloud-native observability?
- 15:49Customer experience
- 22:23Comparison
- 22:44Takeaways and call to action
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