Building resilient systems is no longer a best practice. It as an expectation. Whether you’re running a small internal app or handling millions of transactions a day, the assumption is the same: your service should stay online, even when things go wrong. That includes major failures such as a full region outage on your cloud provider. This is where geo-resilience comes in. Think of it as the modern approach to designing for the worst-case scenario. Your architecture will determine whether users feel the impact of an outage or whether they don’t even know it happened.
In this post, we will explore the two most common geo-resilience patterns: active-active and active-passive. We will break down what each model looks like in practice, what kinds of trade-offs you can expect, and how AWS and Azure support these designs through their native tools.
What Is Geo-Resilience?
The term geo-resilience refers to the ability of a system that maintains availability and consistency even when the infrastructure partially or entirely fails.
The geo element comes from mobilizing different geographical elements of cloud platforms. A geo-resilient system doesn’t treat availability zones or regions as backup plans. Instead, it incorporates them into the architecture from the start. The goal is simple: if a failure happens, it shouldn’t turn into downtime. And if recovery is needed, it should be fast, automated, and verifiable.
Public cloud providers like AWS and Azure offer regionally isolated infrastructure, but that is only part of the equation. You still need to design your system in a way that can use those isolated regions in meaningful, coordinated ways.
Two Geo-Resilience Patterns
Active-Active
In an active-active model, multiple regions are live and in action at the same time and both regions serve production requests in parallel. Traffic is routed to two but not randomly. It is often based on geography or latency. This approach requires careful planning, especially when it comes to data synchronization and conflict resolution. Databases, caches, and session state need to be either globally distributed or explicitly coordinated.
The benefits are immediate: faster response times for global users, high availability with no single point of failure, and immediate recovery if one region drops out. However, there is a complexity there. Now, you have to take care of the distributed consistency, increased network traffic between regions, and higher overall cost.
Active-Passive
In the active-passive setup, regions are not equally responsible. One region is the primary. It serves all traffic under normal conditions. Secondary regions remain on standby. Generally it is supported by replicating data and configuration continuously but not actively serving users. When the primary region becomes unavailable for any reason, routing shifts to the passive region either through DNS-level failover, application level load balancer configuration, or manual intervention.
This model looks more cost-effective, particularly for applications that don’t require millisecond-level failover or cross-region performance. However, failover introduces delay, and idle resources may still incur cost depending on how “warm” the passive region needs to be.
Architecture Overview
How you architect for geo-resilience depends heavily on whether you choose active-active or active-passive. Both models share some fundamental components like DNS routing, load balancers, replicated databases, and storage layers. But they differ in topology and behaviour under failure.
Active-Active Model Architecture
An active-active system typically consists of:
- Global level DNS routing (or load balancing), often based on latency or geography
- Application load balancers in each region, serving real-time traffic
- Application services deployed and scaled identically in both regions
- Globally synchronized databases, such as multi-master setups or eventually consistent models
- Cross-region object storage replication, to ensure shared assets are available everywhere
In this setup, both regions are live and can handle full production loads. If one region fails, the other can continue with little to no disruption, no cold start time. The only challenge could be scaling.
Active-Passive Model Architecture
In an active-passive model, the components shift slightly:
- DNS routing favours a primary region until a health check fails
- Only one region serves traffic; the passive region is on standby
- Data is continuously replicated, usually in an async or near-sync mode
- Storage and infrastructure are pre-provisioned or spun up as needed (cold, warm, or hot standby)
Here, the secondary region is not actively serving users but is prepared to take over if the primary fails. It’s a design that minimizes operational complexity while still protecting against regional outages.
You don’t need identical tooling across clouds, but the basics are the same. Below is a breakdown of how their offerings compare in practice:
| Component | AWS Active-Active | Azure Active-Active | AWS Active-Passive | Azure Active-Passive |
|---|---|---|---|---|
| DNS Routing | Route 53 (Latency or Geolocation Routing) | Traffic Manager (Performance Mode) | Route 53 (Failover Policy) | Traffic Manager (Priority Mode) |
| Load Balancing | Application Load Balancer + Global Accelerator | Azure Front Door | Classic ELB or ALB with health checks | Azure Load Balancer + ASR |
| App Hosting | EC2/EKS/ECS in both regions | AKS / App Services deployed to multiple regions | EC2/ASG with AMI replication | VM Scale Sets + Site Recovery |
| Databases | Aurora Global / DynamoDB Global Tables | Cosmos DB (Multi-region write mode) | RDS with Cross-Region Read Replicas | Cosmos DB (Manual Failover Mode) |
| Storage | S3 with Cross-Region Replication (CRR) | Azure Blob Storage with RA-GRS | S3 with periodic backup to secondary region | Azure Blob with GRS or LRS + Recovery Vault |
Cost, Complexity & Operational Trade-offs
Every resilience model has a cost and it is not just in dollars. Choosing between active-active and active-passive means balancing budget, operational effort, and risk tolerance.
Cost
Active-active architectures are expensive by nature. You’re running at least two fully sufficient copy of the infrastructure in multiple regions, and you have to keep them in sync. You pay for compute, data transfer between regions, replication, and the engineering time it takes to keep everything coordinated.
Active-passive setups can reduce that cost, but only to a point. Passive regions still require provisioning. If you’re running warm or hot standby systems, you’re paying for resources that might never see production traffic. Furthermore, cold standbys take longer to recover.
Complexity and Maintenance
Active-active systems are more complex. You have to solve distributed state management, plan for consistency models (strong, eventual, conflict-free), and handle failovers that don’t feel like failovers to the user. You’ll likely need chaos testing and careful release strategies.
Active-passive is simpler. But failovers are more fragile if they aren’t exercised regularly, or automated. They also tend to become outdated faster if deployments aren’t automated across all regions. And observability and 1st line support needs to be in action.
When to use which?
No doubt, there’s no definite answer for this question. However,
you may prefer to use active-active when:
- Your users are globally distributed and latency matters
- You can’t afford downtime, even in the event of a full region failure
- Your application architecture supports multi-region consistency or is naturally stateless
- You’re willing to invest in the operational maturity needed to maintain it
you may prefer to use active-passive when:
- Cost is a concern and fully duplicating the infrastructure isn’t justifiable against people holding the tap of the budget
- Your “Recovery Time Objective” allows for a little bit of delay during failover
- Your system has a clear primary region and you serve only for people in that region
- You want to simplify state management and consistency guarantees
Conclusion
Knowing your system can absorb failure without falling apart is an expectation. It changes how you operate, deploy, and how your users experience your product. Both active-active and active-passive architectures can deliver geo-resilience. However they serve for different purposes and come with different costs, expectations, and engineering requirements.
Suleyman Cabir Ataman, PhD