AWS Global Services: The Hidden Layer of Resilience
When cloud architects design for high availability, we usually focus on redundancy — multiple Regions, replicated data, automated failover. But as AWS environments scale, resilience becomes less about where your data lives and more about how your dependencies behave when things go wrong.
One of the most overlooked dependencies? AWS global services.
The Illusion of “Global”
AWS defines global services as those that operate beyond a single Region — often because their control plane is centralized or because their data plane spans the edge network.
That global reach enables massive scale, but it also introduces invisible coupling. A few examples:
IAM and Organizations — control planes anchored in one Region per partition (usually us-east-1).
CloudFront, Route 53, and Global Accelerator — globally distributed data planes with single-Region control planes.
S3 and STS — regional data, but certain operations depend on global endpoints.
On paper, that architecture looks elegant. In production, it means your “multi-Region” design might still have hidden single-Region dependencies.
Where Things Break
Imagine a control-plane disruption in us-east-1.
Your CloudFront distributions still serve cached content — great.
Your Route 53 DNS continues resolving — also good.
But try to create a new IAM role, rotate credentials, or deploy a new CloudFront distribution, and your automation stalls.
Your data plane may be healthy, but your control plane — the ability to change things — isn’t.
That’s the quiet irony of cloud resilience: a globally distributed system can still be operationally centralized.
A Shift in Perspective
The goal isn’t to eliminate global dependencies — that’s impossible.
It’s to understand them, design around them, and keep them out of your critical paths.
Here’s how I approach it:
Visibility before action.
Map every service your workload depends on. Identify which are regional, global, or hybrid.Pre-provision instead of react.
If your DR plan includes “create,” it’s already fragile. Pre-create IAM roles, S3 buckets, Route 53 records, CloudFront distributions.Design for static stability.
Ensure your workload can run — or failover — without new control-plane API calls. Test that deliberately.Cache what you can’t control.
If automation reads config from control-plane APIs, cache those values regionally (SSM Parameter Store or DynamoDB).Prefer regional endpoints.
Especially for STS. Usests.us-west-2.amazonaws.cominstead of the global endpoint. Small change, big impact.
Reflection: The October 20 AWS Incident
On October 20, AWS experienced a wide-reaching service disruption that underscored many of these themes.
Here’s the key timeline:
2:01 AM PDT – AWS identified a potential root cause impacting DynamoDB APIs in us-east-1, initially thought to be DNS resolution issues. Global services like IAM and DynamoDB Global Tables also showed symptoms due to their control-plane ties to us-east-1.
2:22 AM PDT – AWS reported early signs of recovery after applying mitigations, though with increased latency and processing backlogs as systems caught up.
8:43 AM PDT – The picture changed. AWS isolated the true root cause to an internal subsystem responsible for monitoring the health of network load balancers. To stabilize operations, they throttled new EC2 instance launches while working toward full recovery.
This wasn’t a typical outage where compute or storage failed — it was an internal control-plane health-monitoring issue that cascaded into the orchestration layer itself.
Even though it began as an internal subsystem failure, the impact spread outward through dependent services — a vivid example of how deeply intertwined AWS control-plane components really are.
And as always, the impact was magnified for workloads concentrated in us-east-1.
Customers running single-Region infrastructure there faced the brunt of it — delayed instance launches, stalled scaling operations, and inconsistent API responses.
For organizations with distributed or multi-Region architectures, the effect was mostly slower management operations, not workload outages.
In short: the smaller your blast radius, the smaller your pain.
Looking Ahead
AWS will almost certainly publish a post-mortem on this event — and it will be worth reading closely.
I’ll be particularly curious to see whether AWS acknowledges a deeper implication:
whether this “internal subsystem” was an isolated failure, or a systemic risk pattern that could exist elsewhere.
If this load-balancer health-monitoring layer underpins multiple regional control planes, it could represent a latent single point of failure — a kind of architectural ticking time bomb.
The real question is whether AWS will treat this as a one-off incident or as a prompt to regionalize and decouple more of its control-plane fabric.
Because that decision determines whether future events stay local — or ripple globally.
Cross-Cloud Perspective: Azure and GCP
AWS isn’t alone here — every major cloud provider faces the same challenge of balancing global coordination with regional isolation.
Azure
Microsoft’s architecture blends global management with regional data planes.
Global control planes: Azure Resource Manager (ARM), Entra ID (Azure AD), Front Door, and Policy.
These coordinate globally but can impact operations everywhere if they degrade.Regional data planes: Compute, Storage, SQL DB are region-bound and paired for DR.
Architect’s read: Azure’s data isolation is strong, but its management plane (ARM, Entra ID) behaves a lot like AWS’s us-east-1 — a centralized orchestrator that can ripple globally.
Google Cloud Platform (GCP)
GCP goes all in on global by default.
Global control + data planes: Cloud Storage, Load Balancing, IAM, Pub/Sub, and DNS.
It simplifies deployments but makes fault domains less visible.Regional services: Compute Engine, Cloud SQL, and GKE Regional Clusters reintroduce locality at the compute layer.
Architect’s read: GCP’s global model is elegant but opaque — control-plane slowdowns can affect everything at once.
Perspective:
AWS abstracts, Azure centralizes, and GCP globalizes.
Each model has trade-offs — and your resilience depends on how well you understand them.
Final Thoughts
Multi-Region architecture isn’t a checkbox — it’s a mindset.
Understanding where your cloud provider draws its fault boundaries is what separates “highly available” from genuinely resilient.
Global services aren’t flaws; they’re design constraints.
And great architects don’t ignore constraints — they exploit them to build systems that keep running when the unexpected happens.
Because resilience isn’t built through redundancy.
It’s built through awareness and independence.
Architect’s Note
Cache before chaos. Don’t depend on live control-plane APIs during an incident.
Never create during failover. If your DR plan says “create,” rewrite it.
Assume throttling, not outage. Most incidents degrade before they fail.
Spread your blast radius. If everything runs in us-east-1, you’re gambling.
Watch the post-mortem closely. If AWS acknowledges systemic risk, revisit your own dependency map.