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Diagnose a GPT-6 failure in Amazon Bedrock from the API error type, not the HTTP status alone. First capture the response, Region, endpoint, model or inference-profile identifier, invocation API, request ID and UTC time. Then follow the matching branch: fix identity and policy issues for AccessDeniedException, correct the model, Region or request shape for ResourceNotFound and ValidationError, reduce or request quota for ThrottlingException, and retry transient capacity failures reported as ServiceUnavailable or overloaded_error. GPT-6 model IDs, supported APIs and Regions must be confirmed in the live Bedrock catalog; do not copy an identifier from an old example.
Start with the error returned by Bedrock
A 400, 403, 404, 429, 503 or 529 narrows the search, but the Bedrock exception name and message are more useful than the status code by itself. Log the structured error before changing permissions, model settings or traffic. Two requests can return the same status while requiring completely different fixes, and a proxy or SDK can hide the original Bedrock detail if you only record its generic message.
| Signal | Most likely branch | First checks |
|---|---|---|
AccessDeniedException (403) |
Caller or policy authorization | Active principal, Bedrock action permission, temporary credentials and policy restrictions |
ValidationError (400) |
Invalid request | Required fields, value formats and ranges, and the request schema for the selected API |
ResourceNotFound (404) |
Wrong or unavailable resource | Model, endpoint or inference-profile identifier, Region and current catalog entry |
ThrottlingException (429) |
Account quota or rate limit | Endpoint-specific model quotas, token and request rates, concurrency and max_tokens where applicable |
ServiceUnavailable (503) |
Temporary service capacity | Backoff, jitter, lower concurrency and a check for a continuing regional incident |
overloaded_error (529) |
Temporary model-serving load | Honor Retry-After, avoid synchronized retries and use supported alternate routing if needed |
Treat the table as a routing aid, not proof of root cause. Read the complete response body, including nested error details, and preserve the request ID.
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A clean record lets you compare attempts and gives AWS Support enough context to trace a request. For every failure, save:
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- HTTP status, exact Bedrock exception name and complete message
- UTC timestamp and AWS Region
- Endpoint (
bedrock-runtimeorbedrock-mantle) - Model ID or inference-profile ID exactly as sent
- Invocation API and SDK or client version
- Request ID from response headers or the SDK exception
- Whether the caller uses long-lived keys, an assumed role, a workload identity or another temporary credential
For repeated throughput failures, also record input and output token rates, requests per minute, maximum concurrency, max_tokens, batch or streaming mode, and the time and slope of the traffic ramp. A single failed request cannot show whether the limit was a burst, a sustained quota breach or a service-capacity event.
Fix access and authorization failures
Check the identity that actually made the call
With AccessDeniedException, verify the principal at runtime rather than the user or role you expected the application to use. A local profile, container task role, instance profile, Lambda execution role and CI role can all resolve to different identities. Confirm the account and role in the same Region and environment where the failure occurred.
For an assumed role, check both sides of the arrangement: the role trust policy must allow the intended caller to assume it, and the role’s permissions policy must allow the Bedrock action used by the application. A permission added to a human administrator’s identity does not grant it to a workload role.
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Inspect identity policies, permission boundaries, session policies, service-control policies and resource or endpoint conditions that apply to the principal. Look for explicit denies and conditions on Region, source VPC, source account, tags or requested model. Grant only the actions the chosen invocation API requires; do not treat a broad administrator policy as the diagnostic default.
Validate temporary credentials
Expired or not-yet-valid temporary credentials can surface as an authorization failure. Check the credential expiration time, the machine clock and the role session duration. Refresh the session and retry with the same request after confirming the new principal. If the first attempt came from a long-running worker, ensure its credential provider refreshes before expiration instead of retaining a cached token indefinitely.
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Separate IAM denial from model-account conditions
Some model-access or marketplace-related conditions have their own error names and messages. A 403 does not prove that adding an IAM action will solve the problem. Match the exact exception to the current Bedrock error guide and check whether the account must accept an agreement, enable access or satisfy a model-specific condition. Do not mask such a response by repeatedly broadening permissions.
Resolve 404 and 400 configuration errors
ResourceNotFound: verify every part of the resource address
A 404 commonly means the identifier is wrong for the endpoint or Region, not that the model is universally unavailable. Check all of these values together:
- Model ID, including punctuation and version suffix
- Inference-profile ID, if the request uses a profile rather than a base model
- Endpoint name and API operation
- AWS Region selected by the SDK, environment variable or client constructor
- Whether the resource is available to the account in that Region
Refresh the model list from the current Bedrock catalog in the target account and Region. Remove stale IDs from configuration files, notebooks and deployment secrets. A model can exist in a catalog view yet still require a different invocation route or profile for the request you are making.
ValidationError: compare the request to the selected API
A 400 indicates that Bedrock received the request but rejected its shape or values. Compare every field with the reference for that specific operation and model: required fields, content type, message structure, token limits, stop sequences, sampling ranges, tool definitions and streaming options. Check data types as well as names; a numeric limit serialized as a string can fail validation.
Make one minimal request with the smallest valid prompt and conservative generation settings. Add optional fields one at a time until the failing field is identified. Keep the original failing payload (with secrets and personal data removed) so you can explain the difference between a working and failing call.
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Do not infer compatibility from the model name
Model support differs by endpoint and API. A model may be listed for one invocation surface but not another, or may require an inference profile. Confirm that the chosen model supports the operation, request format and streaming mode you are using before changing quotas.
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Confirm GPT-6 availability without guessing an identifier
The current AWS General Reference includes quota entries for GPT-6 Luna and GPT-6 Sol. Those entries do not, by themselves, establish an invoke-ready model ID, supported API, account access or Region availability. The exact identifiers and compatibility matrix must be checked in the live Bedrock model catalog and the Service Quotas view for your account.
- Open the Bedrock model catalog while the console is set to the Region where the application runs.
- Find the GPT-6 model entry and record the exact model or inference-profile identifier shown for invocation.
- Review the entry’s supported APIs, endpoint, input and output format, streaming support and cross-Region options.
- Check that the account has access in that Region and that the identifier is valid for the API your client calls.
- Copy the identifier into a controlled configuration value and test a minimal request before enabling production traffic.
Do not publish or deploy an ID copied from an old blog post, another Region or a different endpoint. A correct-looking name can still produce ResourceNotFound or ValidationError.
Diagnose 429 throttling with the correct quota system
ThrottlingException generally means the account exceeded a quota or rate limit. Quotas are scoped by model, Region and endpoint, so first identify the exact route used by the failing client. Runtime and Mantle have separate quota accounting even when they invoke the same underlying model.
| Endpoint | Quota characteristics | Operational implication |
|---|---|---|
bedrock-runtime |
Per-model token rates and, for some models, request rates. Multiple supported inference APIs on this endpoint can share the model quota. | Switching APIs while staying on Runtime may not increase capacity. Shape total token and request traffic for that model and Region. |
bedrock-mantle |
Scaling guidance emphasizes input and output tokens per minute and the request’s max_tokens. The endpoint does not enforce RPM quotas. |
Control token budgets and concurrency using Mantle’s limits; do not apply Runtime RPM assumptions. |
Measure the traffic that consumes quota
Estimate both requested and generated tokens, not just prompt count. A low request rate can still exceed a token-per-minute limit when prompts or max_tokens are large. Record peak and sustained rates, concurrent in-flight calls, retries and whether streaming requests remain open for a long time. Retries consume quota too and can turn a brief spike into a continuing throttle.
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Reduce demand before requesting more quota
- Lower concurrency with a bounded worker pool or semaphore.
- Cap
max_tokensto the largest useful response rather than a generous default. - Queue work and smooth bursts instead of releasing a large batch simultaneously.
- Set client timeouts and stop abandoned requests so they do not occupy capacity.
- Prevent automatic retries from multiplying traffic; use one centralized retry policy.
After the workload fits the documented limit, watch the same metrics during a gradual ramp. If sustained demand still exceeds the account allocation, request an increase through Service Quotas or AWS Support when that model and Region permit adjustment. Capacity offerings and adjustability vary, and a model nearing lifecycle transition may not be a good candidate for an increase; check lifecycle status first.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Handle 503 and 529 as transient capacity conditions
A 503 ServiceUnavailable means the service is temporarily unable to handle a request because of high demand or a capacity constraint. A model API can report similar temporary serving load as 529 overloaded_error. These are different from a 429 account quota breach: immediately requesting more quota will not cure a short-lived capacity event.
Use bounded exponential backoff with jitter
Retry only operations that are safe to repeat, and place a cap on attempts and total elapsed time. Honor a server-supplied Retry-After value when present. Otherwise, use exponential delays with random jitter so many workers do not retry on the same second.
delay = min(base_delay * 2**attempt, maximum_delay)
sleep(random_between(0, delay))
Keep the retry budget outside individual helper functions so nested SDK and application retries do not multiply one another. Log each retry with the original request ID, attempt number and reason.
Control concurrency during an overload
Reduce the number of simultaneous calls when 503 or 529 responses persist. A retry storm can prolong the outage even after the service begins recovering. Use a circuit breaker or queue that pauses new work after a threshold, then probes with a small number of requests. Restore concurrency gradually rather than returning to the previous burst immediately.
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Consider another route only when it is supported
Another Region or cross-Region inference can help with a capacity constraint only if the model, account, data-handling requirements and workload support that route. Confirm availability in the live catalog before changing routing. Do not move traffic across Regions merely because a model name appears in a global list.
Compare invocation routes before changing architecture
When a model is available through more than one route, compare the routes on facts that affect both correctness and throughput:
| Decision point | Questions to answer |
|---|---|
| Model and Region | Is the exact model or profile available to this account in the target Region? |
| API surface | Does the route support the required request format, streaming, tools and response shape? |
| Quota system | Will calls consume Runtime or Mantle allocations, and are quotas shared across APIs on that endpoint? |
| Limit type | Are limits expressed as tokens per minute, requests per minute, concurrency or a combination? |
| Routing options | Does the route support cross-Region inference or a capacity option required by the workload? |
Establish availability first. It is not useful to compare theoretical throughput for a route that cannot invoke the model in your account or does not accept your request schema.
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Use CloudWatch Bedrock metrics where your monitoring role has the required permissions. Correlate metric spikes with application logs rather than relying on aggregate request counts. Track status and exception type separately: a rising 429 rate points to quota pressure, while 503 or 529 spikes point to capacity conditions.
Include the following in a support case or internal incident record:
- Account, Region, endpoint and exact model or inference-profile ID
- Invocation API, SDK and client versions
- UTC start and end times, including the first and last request IDs
- HTTP status, exception name and complete sanitized message
- Input and output token rates, request rates, concurrency and
max_tokens - Traffic ramp timeline, retry policy and any Region or endpoint changes
- A minimal request that reproduces the problem, with credentials and sensitive content removed
This evidence distinguishes an authorization defect from an invalid resource, a quota ceiling and a transient service event.
An end-to-end troubleshooting runbook
- Freeze the evidence. Save the complete error, request ID, Region, endpoint, identifier, API and UTC time.
- Classify the exception. Route to access, validation/resource, quota or capacity handling; do not classify from status alone.
- Verify identity. Confirm the runtime principal, credential validity, trust relationship and effective denies.
- Verify the address. Check the current catalog entry, model or profile ID, endpoint, API and Region.
- Minimize the request. Send the smallest valid payload, then add optional fields incrementally.
- Measure load. For 429, compare token and request rates, concurrency and
max_tokenswith the quota for that endpoint. - Shape or request capacity. Smooth traffic and lower concurrency first; seek a quota increase only when the model and Region support it.
- Retry transient failures safely. For 503 or 529, honor
Retry-After, use bounded exponential backoff with jitter and prevent retry storms. - Re-test in a controlled ramp. Start with one request, then increase concurrency while watching exception-specific metrics.
- Escalate with evidence. Send the complete timeline and measurements when the corrected request, identity and quota still do not explain the failure.
Common mistakes that prolong an outage
- Using only the HTTP code: the exception name and message identify the branch more accurately.
- Changing IAM for every 403: model-access or agreement conditions can require a different remedy.
- Reusing a model ID across Regions: availability and identifiers are Region- and endpoint-specific.
- Switching APIs to evade Runtime throttling: supported Runtime APIs can share the same per-model quota.
- Applying RPM assumptions to Mantle: Mantle guidance centers on token throughput and
max_tokens, not enforced RPM. - Requesting quota for a 503: 503 and 529 are usually temporary capacity signals, not account quota errors.
- Retrying all errors: retries cannot repair a malformed payload, missing permission or nonexistent resource.
- Retrying in lockstep: synchronized workers create a retry surge; add random jitter and a concurrency limit.
- Publishing an unverified GPT-6 ID: current quota listings for GPT-6 Luna and GPT-6 Sol do not prove invoke-ready identifiers or Region support.
Final decision rule
Keep the diagnostic path tied to the actual endpoint and response. Authorization errors require the effective identity and policy; 404 and 400 errors require a current model/API/Region check and a valid request shape; 429 requires endpoint-specific quota measurement; and 503 or 529 requires controlled retries and reduced concurrency. Only after those checks should you change routing, request additional quota or open a support case.
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