October 2025 AWS outage: DNS failure in US-EAST-1 cascaded globally, impacting banking, AI workloads, and SaaS for 10 hours. Multicloud resilience and independent DNS were critical defenses.

On October 20, 2025, Amazon Web Services (AWS) experienced a significant global outage that disrupted thousands of websites and applications across multiple sectors. The incident, concentrated in the US-EAST-1 (Northern Virginia) region, caused widespread disruptions from early morning hours and was fully mitigated by mid-afternoon.
AWS confirmed the outage stemmed from a DNS resolution failure linked to DynamoDB’s endpoint in US-EAST-1. This caused cascading API request failures across globally reliant services (e.g., IAM and DynamoDB Global Tables). AWS engineers indicated it was not security-related, but rather an internal infrastructure misconfiguration affecting internal DNS propagation.
Beyond EC2 and S3, the disruption rippled through:
No evidence of cyberattack or data corruption was found. However, temporary IAM authorization mismatches and API Gateway rate throttling disrupted authentication services for some customers. Bedrock latency and Lambda backlogs triggered delayed automation pipelines across AI-driven workflows.
Industry analysts argue this outage underscores single-region dependency risks and the fragile coupling between DNS and modern distributed applications. Gartner analysts noted enterprises using multicloud redundancy or failover DNS like Cloudflare’s D1 or Azure Traffic Manager maintained higher uptime. CIOs and CTOs are advised to:
Overall Impact: Temporary but severe — approximately 20% of global internet traffic was degraded or interrupted for up to 8 hours. AWS has since stated it is implementing “enhanced DNS partitioning and inter-region failover automation” to prevent recurrence.
About the Author

Rejith Krishnan
Founder and CEO
Rejith Krishnan is the Founder and CEO of lowtouch.ai, a platform dedicated to empowering enterprises with private, no-code AI agents. With expertise in Site Reliability Engineering (SRE), Kubernetes, and AI systems architecture, he is passionate about simplifying the adoption of AI-driven automation to transform business operations.
Rejith specializes in deploying Large Language Models (LLMs) and building intelligent agents that automate workflows, enhance customer experiences, and optimize IT processes, all while ensuring data privacy and security. His mission is to help businesses unlock the full potential of enterprise AI with seamless, scalable, and secure solutions that fit their unique needs.