To keep an AI application working when a model provider, endpoint, or cloud region fails, build and test a recovery path before an outage. That usually means routing requests among suitable, independent back ends, using bounded retries and health-based circuit breaking, and planning for the data, traffic, capacity, identity, and safety systems the application also depends on. A second endpoint is not a complete failover plan if it shares the same failure or cannot handle the load.
Start by deciding what has to fail over
“The provider is down” can describe very different problems: one model instance is unavailable, a deployment is throttled, a provider-wide service is disrupted, a gateway has failed, or a whole region cannot serve traffic. The right fallback depends on the failure boundary. Multiple deployments in one region can help with an instance-level disruption, quota event, or networking misconfiguration; they do not address every provider-wide or regional failure. For wider protection, the alternate back end needs to be independent of the failed component and reachable by the application. Microsoft’s gateway guidance describes routing across multiple model back ends and retrying against another available back end.
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Before choosing a design, list the dependencies in the request path: client or global ingress, gateway or routing logic, model endpoint, orchestration or agent service, data store, identity and permissions, monitoring, and content-safety controls. A model in another region does not preserve the application if a required database, orchestration service, or safety control is still unavailable. Microsoft’s baseline conversational reference architecture explicitly lacks multiregion capabilities, so regional continuity requires additional design work.
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| Pattern | What it is suited to | Main trade-off or constraint |
|---|---|---|
| Retry another back end | An individual deployment or endpoint is unavailable or throttled, while another usable back end is reachable. | The alternate must support the task and have capacity; a retry cannot fix a shared provider, gateway, or regional failure. Microsoft gateway guidance |
| Active-active distribution | Multiple locations serve traffic so the application can continue when a location is impaired. | Deployments and global traffic distribution must be configured across locations, with enough capacity to handle shifted demand. Google Cloud reliability guidance |
| Active-passive failover | A designated standby region or back end takes traffic after the primary is unavailable. | The standby must be ready, authorized, and provisioned for the traffic it may receive; keeping every region at peak capacity may not be appropriate. Microsoft gateway guidance |
| Cold recovery | Recovery can take longer and a standby need not serve traffic continuously. | Recovery depends on bringing the required services and routing back into operation; establish acceptable recovery-time and recovery-point objectives for the workload. Microsoft reference architecture |
These patterns are not interchangeable guarantees. Google recommends deploying models in multiple locations and using global load balancing for availability and fault tolerance. Whichever pattern you choose, verify that the alternate model behaves acceptably for the actual application; the cited architecture guidance does not establish that different models are equivalent.
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Put health-aware routing and bounded retries in the request path
A gateway or equivalent routing layer can centralize back-end selection and health logic instead of duplicating provider-specific decisions in every client. Configure it to consider availability and throttling signals, retry only within a bounded policy, and select a healthy alternative when one exists. Circuit breaking stops repeated requests from being sent to a back end that is failing; recovery logic should allow it back into service only when it is safe. Health checks should also expose when no usable back ends remain rather than reporting the gateway as healthy merely because it is responding. Microsoft’s gateway guidance covers multi-back-end routing, retries, and the gateway’s own availability considerations.
Retries need limits and timeouts. If every request keeps retrying an overloaded service, retries can add demand at the moment capacity is already constrained. Decide how many attempts are permitted, how long the request may wait, and what the application should return when no healthy back end is available. The response may be a controlled error or a reduced-capability mode, depending on the application; do not imply that a fallback exists if it has not been implemented.
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Make regional recovery cover the whole application
A regional plan needs to account for how users reach the surviving region, not just where a model is hosted. Specify the behavior of global ingress or DNS, gateway instances, orchestration, data, identity, monitoring, and safety controls. Decide whether data is replicated or kept regionally isolated, and confirm the target region’s services can access what they need without violating the application’s policy. Set recovery-time and recovery-point objectives according to how long the workload can be unavailable and how much data it can afford to lose.
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Capacity and access are part of recovery. If one region stops serving, the remaining region may receive the combined demand. Provision for that possibility or use an active-passive design with a clear capacity plan; ensure credentials and least-privilege permissions work for the alternate back ends. Do not route across geopolitical boundaries without checking data-residency and sovereignty requirements. Microsoft’s gateway guidance calls out capacity planning and data-sovereignty constraints.
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Test the failure path, not just the normal request
A configured fallback is only useful if the application can actually use it under stress. Test the workflow with the failure boundary you intend to survive, and verify each dependent layer:
- Make a primary endpoint unavailable or throttled and confirm the router detects the condition and stops sending it requests as intended.
- Check that timeouts and retry limits are bounded, and that retries do not keep adding load to an unhealthy service.
- Confirm the alternate endpoint is reachable, authorized, suitable for the task, and able to accept the shifted traffic.
- Exercise regional ingress, orchestration, data access, monitoring, and safety controls rather than testing model invocation alone.
- Restore the primary and verify that recovery does not send traffic back prematurely or bypass safety and policy controls.
This testing checklist follows from the architecture dependencies and documented failover risks; it is not a claim that any particular application has been tested. OpenAI’s August 2026 incident write-up, “Elevated errors affecting ChatGPT”, described a concrete limitation: “Existing failover behavior did not automatically redirect enough traffic away from the affected region, so protective controls began rejecting requests to prevent further overload.” The lesson is that a failover setting alone does not demonstrate that traffic will shift successfully or that the surviving service can absorb it.
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