When Amazon Bedrock returns an error during a model invocation request, start by analyzing the error code and message to identify the root cause. Bedrock uses standard HTTP status codes and service-specific error codes (e.g., ThrottlingException, ValidationException) to indicate issues. For example, a 400 Bad Request with a ValidationException often points to invalid input parameters, such as a malformed request body or unsupported model configuration. Check your API request for syntax errors, missing required fields, or parameter values that exceed model limits (e.g., maxTokens set too high). Use AWS CloudWatch Logs or enable Bedrock’s logging feature to review detailed error traces. If the error is unclear, cross-reference the Bedrock documentation for the specific model you’re using to confirm input format and constraints.
Next, address rate limits and retry strategies. Bedrock enforces service quotas (e.g., transactions per second) per model and AWS account. If you receive a ThrottlingException, your application may be exceeding these limits. Check your service quotas in the AWS Service Quotas console and consider requesting an increase if needed. Implement retry logic with exponential backoff in your code to handle transient errors. For example, use the AWS SDK’s built-in retry mechanisms or a library like retry in Python to pause and retry failed requests. Ensure retries are applied only to idempotent operations and avoid aggressive retry loops that could worsen throttling. If the issue persists, verify that your application isn’t sending redundant requests or that multiple clients aren’t inadvertently overloading the service.
Finally, validate permissions and model access. A 403 AccessDeniedException often indicates missing IAM permissions or lack of explicit access to the model. Confirm that your IAM role or user has the bedrock:InvokeModel permission for the target model and that the model’s access policy grants your account or role permission. For example, some Bedrock models require you to request access via the AWS Management Console before they can be used. Check the Bedrock model access settings in the console to ensure the model is listed as “Access granted.” If the error relates to regional availability (e.g., ModelNotAccessibleException), verify that the model is supported in the AWS region you’re using. For complex permissions issues, use AWS IAM policy simulators or temporary credential debugging tools like AWS CloudTrail to trace authorization failures.