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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteA provider fallback system needs a shared failure taxonomy so retries, failover, circuit breakers, and user-facing errors respond consistently to the same evidence. A timeout, a rate limit, an invalid request, and an open circuit are not interchangeable: each points to a different likely cause and may warrant a different action.
Why classification must come before policy
Retrying, switching providers, opening a circuit, and returning an error are separate decisions. A common classifier gives those decisions the same account of what happened. Without it, one layer may retry an error another layer treats as permanent, or a breaker may fail to count a provider-side problem that routing already treats as a reason to fall back.
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A concrete example appears in TYPO3 LLM Extension ADR-095, dated July 20, 2026. The project records that its retry, fallback, and circuit-breaker call sites had drifted; in particular, a 5xx response was neither retried nor counted by the breaker. Its proposed shared classification is an implementation decision for that project, not proof that every 5xx from every provider should always trigger cross-provider fallback.
The practical principle is to keep meaning and action distinct: first classify the observed failure, then apply explicit policy for each mechanism. The same class can, for example, permit a bounded retry while disallowing fallback if no alternate provider can safely serve the request.
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What should the failure taxonomy include?
ADR-095 uses these categories: connection, rateLimit, auth, configuration, clientError, serverError, circuitOpen, and unknown. It uses the classifier to answer consistently whether an error is retryable and whether it should count toward opening the circuit. Those categories are a useful starting point, not a universal standard.
A classification should preserve the evidence that produced it. Normalize provider exceptions into an internal record that can include provider and operation, HTTP status when present, provider error code or type, transport or timeout evidence, retry timing metadata, and safe request context. Keep the original status and structured provider details available for diagnostics; ADR-095, for example, preserves a 429 status in context while mapping it to a quota-specific exception.
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Here is a policy-oriented starting point. The responses are design options, not rules that fit every provider or workload.
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|---|---|---|
| Connection failure or timeout | Potentially transient; the request may or may not have reached the provider. | Retry within a bound and with delay. Consider another provider only if request semantics make that safe. Azure transient-fault guidance and AWS circuit-breaker guidance discuss transient failures and repeated-call protection. |
| HTTP 429 or explicit quota signal | Throttling or a quota limit, which does not necessarily mean the provider is generally unhealthy. | Honor Retry-After or reset timing when supplied. Use alternate capacity only if policy, quota, and request compatibility allow it. Azure and Salesforce reliability guidance provide retry-related guidance. |
| HTTP 5xx or explicit provider overload | Often a provider-side transient-failure candidate, but the precise meaning varies. | Consider bounded retry and circuit accounting; consider fallback only if another target is eligible. Confirm the provider-specific error meaning. ADR-095 treats server errors as retryable and circuit-tripping within its own design. |
| Authentication, configuration, or ordinary client error | Often a credential, setup, or request problem unlikely to be repaired by repeating the same call. | Usually fail fast with useful diagnostics rather than retrying or counting it as provider-health failure. Correct the request or configuration before trying again. ADR-095 makes this distinction in its project policy. |
| Circuit already open | The breaker has already classified the dependency as unhealthy. | Skip the upstream call or follow configured fallback; do not count the open-circuit result as another upstream failure. ADR-095 documents this behavior in that implementation. |
| Unrecognized or contradictory evidence | The cause is not established. | Keep an unknown class, retain diagnostic context, and use an explicit conservative policy rather than silently treating every unfamiliar error as transient. The Bifrost documentation describes provider-specific error semantics and distinguishes retry from fallback: Retries & Fallbacks. |
Why a status code alone is not enough
Providers do not always encode the same underlying problem in the same way. Rejected credentials, exhausted quota, unavailable models, and retired models can appear under different status codes or provider-specific error types. Bifrost’s Retries & Fallbacks documentation gives examples of these differing semantics; it is development-branch documentation, so its behavior may change.
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Use structured provider error types and context when available, while retaining the HTTP status and an unknown path when evidence is insufficient. Avoid rules such as “all 400s are permanent” or “all 429s mean switch providers” unless the specific provider contract supports them. OpenClaw’s model-failover documentation likewise lists distinct failure conditions such as authentication, rate limits, overload, timeouts, billing disables, and missing models; that is an implementation example, not a general policy to copy wholesale.
Retry, fallback, and circuit breaking make different decisions
Retry the same provider
A retry repeats an operation, often against the same target. Use it only when the failure may recover and repeating the operation is safe. Bound attempts, add backoff, and use provider-supplied retry timing where applicable. Retries can amplify load when many callers respond to the same incident, so Azure also recommends an aggregate retry budget to limit retry work across requests: Transient Fault Handling.
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Fail over to another provider
Fallback asks whether a different provider or alternate strategy can serve the request. It is not a repair for malformed input, bad local configuration, or invalid credentials that are shared across providers. Before switching, check that the alternate accepts the same model, parameters, data handling requirements, and operation semantics. A request that can be safely retried against one provider may not be safe to replay elsewhere; streaming requests also need a defined policy for partial output.
Open a circuit
A circuit breaker protects a dependency by stopping repeated calls after a configured failure condition and allowing recovery checks according to its state-transition behavior. Its thresholds, observation windows, recovery probes, and interaction with fallback are implementation-specific; a single brief failure need not have the same effect as persistent failure. AWS describes the pattern as a way to limit repeated calls and reduce cascading effects: Circuit breaker pattern. VIDAI documents one implementation with provider/model-scoped health and fallback chains: Fallback.
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How to implement a consistent decision path
- Normalize the evidence. Convert provider exceptions into a stable internal representation while preserving raw status, structured error type, retry metadata, and safe context for troubleshooting.
- Classify once. Use a shared classifier or one authoritative classification layer rather than separate error ladders in retry middleware, routing, and breaker code. Keep a meaningful
unknownresult for cases the evidence cannot resolve. - Define each policy separately. For each class, specify whether same-provider retry is allowed, whether another provider is eligible, whether the event counts toward a circuit, and what error to return if no safe action remains. These answers need not be identical.
- Bound the work. Configure a maximum retry count and backoff, honor retry timing supplied by the provider when present, and consider a system-wide retry budget when concurrent retries could magnify load. See Azure’s transient-fault guidance and Salesforce’s reliability guidance.
- Make decisions observable. Record structured reasons for retrying, skipping a target, failing over, opening a circuit, or returning an error. Separate the upstream failure from a local
circuitOpenresult so operational data does not mistake a skipped call for a new provider failure. AWS guidance discusses logging and identifying calls affected by an open circuit: Circuit breaker pattern. - Test classification and policy independently. Test provider-specific mappings as pure classification cases, then test integration behavior: retries stop at their bound, fallback occurs only for eligible targets, breaker counts match policy, and open circuits avoid upstream calls. ADR-095 describes direct classifier tests and middleware tests for its changed behavior: ADR-095.
Streaming and replay need explicit treatment
A connection drop during streaming can leave the caller with partial output. Automatically restarting on another provider may duplicate content, repeat side effects, or produce a response whose beginning came from one provider and ending from another. VIDAI notes that a dropped streaming connection can leave a partial stream and require client-side retry: Fallback. Decide whether to stop with an error, restart from the beginning, or support a provider-specific resume mechanism; document the consequences and tell clients whether partial output may have been delivered.
For non-streaming calls too, establish idempotency and replay assumptions before enabling cross-provider fallback. A taxonomy can identify likely causes, but it cannot by itself prove that replay is safe or that two providers interpret a request equivalently.
What the taxonomy cannot decide for you
There is no universal mapping from status code to action, no single correct breaker threshold, and no source-backed retry count that fits every API. Provider contracts, quota accounting, whether a request reached the upstream service, operation idempotency, streaming state, and the cost of degraded output all matter. Document those assumptions alongside the class-to-policy mapping, and revisit provider-specific mappings when their APIs change.
For an essential operation with a safe alternate result, fallback may be preferable to immediate failure. If an alternate cannot preserve the request’s meaning or safety, returning a clear error is better than silently serving a misleading substitute. Salesforce describes fallback as an alternative approach in reliability design, while the criticality decision remains system-dependent: Reliability.
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