It is now well documented that the us-east-1 region experienced a significant outage on AWS on October 20th, 2025. While there is already much discussion around why such a vast number of systems were impacted and what design weaknesses were exposed, for me, the real story isn’t just that AWS went down (of course, us-east-1), but rather how many SaaS providers went down with it.
There is a growing push toward adopting SaaS platforms due to their obvious advantages — abstracting away infrastructure management and letting teams focus on solving business problems that matter. However, while SaaS is beneficial, it hides many resiliency weaknesses — until you get the shock of your life during a major cloud outage.
A Closer Look: Example E-commerce Architecture Affected
Let’s take one example: if you're running a large e-commerce platform, your architecture might rely on the following stack — and here's how each layer was affected.
Note: The SaaS dependency and impact details in this article are based on publicly available information, incident reports, and observed behavior during the AWS us-east-1 outage. Some examples are illustrative or inferential in nature and may not reflect the full internal architecture of each provider.
Frontend Hosting — Vercel
Vercel, a popular platform for Next.js applications, was reportedly impacted during the outage, likely due to its reliance on AWS infrastructure such as Lambda (for serverless functions), EC2 (for compute), and DynamoDB (for metadata storage).
During the outage, users experienced:
- Failed deployments
- Elevated error rates in serverless functions
- CDN rerouting issues
- Intermittent dashboard access
While Vercel's architecture spans multiple regions, users whose deployments were primarily in US-East-1 faced notable downtime, with some sites and APIs going offline temporarily.
Vercel CEO Guillermo Rauch acknowledged the issue on X:
Identity Management — Auth0
Auth0, an Okta company, is widely assumed to rely heavily on AWS infrastructure, which may have contributed to service disruptions during the US-East-1 outage. For customers in that region, failover mechanisms such as Geo-HA may have been triggered, though public information on their effectiveness is limited.
Observability — Datadog
Datadog was likely affected to some extent during the AWS US-East-1 outage, given its integration with AWS services such as DynamoDB, EC2, and Lambda for telemetry ingestion (metrics, logs, traces).
Possible effects for users included:
- Delayed data processing
- Gaps in historical logs
- Reduced visibility into workloads running on AWS
Datadog operates on a multi-cloud architecture (AWS, GCP, Azure), so the platform did not experience complete downtime. Nevertheless, users relying on AWS-specific integrations may have seen temporary cascading issues.
Payments — Stripe
Stripe may have experienced some service disruptions during the AWS US-East-1 outage. Much of Stripe’s infrastructure runs on AWS (EC2 for compute, S3 for storage), which could have contributed to temporary issues.
Possible effects reported by users included:
- Elevated API error rates
- Dashboard access issues
- Payment processing delays
While Stripe did not experience a full outage, dependencies on AWS services may have led to cascading issues affecting certain workflows.
Communication & Collaboration — Slack
Slack reportedly experienced some service disruptions during the AWS US-East-1 outage, possibly due to dependencies on AWS services such as EC2, S3, and Lambda.
Users may have noticed:
- Failed message deliveries
- Delayed notifications
- Intermittent workspace loading
These are just a few examples. The list goes on — and it reveals a critical point: SaaS platforms promise scalability, ease of use, and low maintenance, but their black-box nature hides several resiliency vulnerabilities — which the AWS outage brought into the spotlight.
What Went Wrong: Key Issues Exposed
Cascading Failures from Shared Infrastructure
Many SaaS providers run on AWS and default to the US-East-1 region due to its maturity and low latency.
But when it fails, it creates ripples across countless services, often in unexpected ways.
SaaS ≠ Always-On
Without transparency into a provider’s infrastructure, you can’t audit failover paths or validate high availability claims.
This creates a domino effect, where one outage stalls your entire workflow, and you're left completely blind.
Even Giants Weren’t Immune
Some large streaming platforms may experience disruptions during regional cloud outages. For example, high-traffic services like Disney+ Hotstar could be affected by dependencies on cloud infrastructure such as AWS EC2 or S3, though no confirmed reports are available for this specific outage.
The reality is that most of the issues discussed above are beyond our direct control. SaaS providers abstract away their backend infrastructure, which can leave you vulnerable to upstream failures. However, there are proactive steps you can take within your control to mitigate these risks and improve system resilience.
SaaS Resilience Improvement Plan
1. Map and document SaaS dependencies
Create and maintain an up-to-date inventory of all SaaS services your system relies on, both directly and indirectly. Include details such as the underlying cloud infrastructure (e.g., AWS, GCP), regional hosting, and the criticality of each service to your operations.
2. Implement client-side circuit breakers and retries
Add fault-tolerance mechanisms in your frontend and backend code, such as circuit breakers, timeouts, exponential backoff retries, and fallback UIs. This ensures that transient SaaS outages do not fully break your user experience.
3. Cache critical data locally
For high-availability features (e.g., product catalog, user settings), implement edge or client-side caching strategies. This allows your system to serve stale-but-usable data if upstream SaaS services are temporarily unavailable.
4. Set up independent monitoring and alerting
Do not rely solely on the provider’s status pages. Implement external health checks and synthetic monitoring to independently track the availability and performance of critical third-party services.
5. Enable redundant SaaS providers (where feasible)
For high-risk areas such as authentication, payments, or observability, consider integrating with secondary SaaS providers that can be switched to manually or programmatically during outages. Be mindful that this can increase complexity and may require handling differences between providers.
6. Configure multi-region deployment for services under your control
Where you manage infrastructure or use PaaS providers (e.g., Vercel, Firebase), ensure that deployments span multiple regions. Avoid over-reliance on a single cloud region, such as AWS us-east-1.
7. Use event-driven buffering for critical workflows
Decouple workflows using queues or message buffers (e.g., SQS, Kafka, Durable Queues) so that temporary upstream failures do not result in data loss or dropped transactions.
8. Test system resilience with chaos engineering
Regularly simulate SaaS outages (e.g., temporarily disabling a key API) to test how your system behaves under failure conditions and identify points of fragility before a real outage occurs.
9. Establish offline-friendly workloads
Where possible, allow users to continue working in a limited or offline mode—especially in mobile apps or agent consoles—and sync data back once the upstream SaaS service recovers.
10. Monitor and enforce SaaS SLAs
Track uptime, latency, and incident response of critical SaaS providers. Ensure they meet their SLA commitments, and escalate contractually or operationally if violations become frequent.
These strategies will not eliminate risk entirely, and that’s okay. But they can significantly reduce exposure so that when the unexpected happens, you’re not scrambling—you’re calmly sipping a cup of tea.
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