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A Braket task marked QUEUED is waiting for a device; one marked FAILED was attempted and did not complete successfully. Check the remote task state before changing settings or submitting a duplicate. For a queued task, inspect the target device and live queue. For a failed task, use its error details to investigate access, S3, SDK compatibility, quotas, or request limits.
First, tell a queue delay from a task failure
Record the task ARN, device ARN, AWS Region, creation time, status, and configured output S3 location. In the Amazon Braket console, open Quantum Tasks in the same Region where the task was submitted; the task list is Region-specific. In the SDK, inspect the task with task.state() and its metadata.
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| State | What it means | Next step |
|---|---|---|
CREATED |
Braket received the task. | Check whether it advances to the queue or returns an error. |
QUEUED |
The task is waiting to run on its target device. | Inspect device availability, queue depth, and queue position. |
RUNNING |
The task is executing. | Check its remote state and avoid resubmitting it just because it is taking time. |
COMPLETED |
The task finished. | Retrieve its result from the configured output location. |
FAILED |
The task was attempted and failed. | Use the task’s error information to choose the relevant failure branch below. |
CANCELLED |
The task was cancelled before execution. | Confirm why it was cancelled before deciding whether to submit another task. |
A queue delay and an execution failure need different diagnoses. For a Hybrid Job, inspect both the job and its quantum tasks: Hybrid Job tasks appear in the priority task queue, so ordinary task queue depth alone may not show the full picture.
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- Open the target device in the Braket console. Check its online/offline status and current or upcoming availability windows. A device may be offline despite an availability window—for example, because of maintenance, upgrades, or operational issues.
- Read the queue counts and the task’s position. Braket exposes queue depth and queue position in the console and SDK. AWS’s guide shows calls including
device.queue_depth().quantum_tasks,device.queue_depth().jobs, andtask.queue_position().queue_position. Check these against the syntax supported by your installed SDK version. - Record when you checked. Note the Region, device status, queue counts, task position, and observation time. These values describe a live snapshot, not a promised completion time.
Braket distinguishes normal task, priority task, and Hybrid Job queue counts; quantum tasks associated with Hybrid Jobs receive priority over standalone tasks. A position is the number of tasks ahead, not an estimate of minutes or hours. Queue length, shared QPU capacity, device availability, and the complexity of other customers’ tasks all affect how long work takes. AWS documentation does not provide a universal wait-time estimate, and a device with fewer visible queued tasks is not necessarily faster if it is unavailable or handling different work.
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If submission or execution failed, follow the error
AccessDeniedException
Check that Braket is enabled and permitted for the principal in the Region where you are submitting. AWS advises checking with your internal administrator about Region restrictions and whether the role is allowed to use Braket.
CreateQuantumTask validation errors involving S3
- Confirm that the output S3 bucket and prefix already exist. Braket does not create them automatically.
- If calling the API directly, provide the bucket path without an
s3://prefix in the bucket-path field. - Verify that the principal can access the intended output location, and keep that location with the task’s diagnostic record.
SDK feature or schema compatibility problems
A feature failure may reflect the Python runtime or package/schema versions rather than the task or device. AWS’s documentation, accessed October 4, 2026, says Python 3.10 or newer is required and recommends Python 3.12 for Hybrid Jobs. First check the runtime and installed package versions, especially in a managed notebook or a deployment that pins dependencies. The documented upgrade commands are:
pip install amazon-braket-sdk --upgrade --upgrade-strategy eagerpip install amazon-braket-schemas --upgrade
Apply upgrades in the environment that actually submits or runs the workload, and account for any dependency pinning before changing a managed or production environment.
ServiceQuotaExceededException on a simulator in a Hybrid Job
One documented cause is exceeding the concurrent quantum-task limit for the selected simulator. Multiple Hybrid Jobs in an account can submit against the same simulator and contribute to that limit. Search task states for the device—CREATED, QUEUED, RUNNING, or CANCELLING—or inspect CloudWatch Braket metrics by device. Then check the current Region-specific quota in Service Quotas. AWS’s troubleshooting guidance identifies a quota increase as applicable to SV1; do not assume the same remedy applies to every simulator or quota row. If handling the exception in code, use a deliberate retry strategy rather than a tight loop that continues submitting while capacity is exhausted.
Other quota or provisioning errors
If the message concerns Hybrid Job ML instance capacity, check whether the requested instance type is listed and available and whether its Service Quotas limit can be increased. If the requested ML compute capacity cannot be provisioned, AWS’s quota guidance suggests trying another Region. Confirm the instance type and Region before changing the job configuration.
Check API request rates as well as device capacity
Throttling caused by a burst of API calls is not the same as waiting in a device queue. Amazon Web Services’ live Amazon Braket Quotas documentation, accessed in 2026, lists these default request rates per account and Region:
| API rate | Documented default | Qualification |
|---|---|---|
| General API requests | 140 requests per second | Per account and Region; the quotas page also specifies separate burst limits. |
CreateQuantumTask |
20 requests per second | Per account and Region; separate burst limits apply. |
SearchQuantumTasks |
5 requests per second | Per account and Region; separate burst limits apply. |
Compare both the sustained rate and burst pattern of your submitter or diagnostic tooling with the current quota and account behavior. The AWS quotas page says adjustable request rates can be increased only up to twice the stated default; burst rates cannot be increased.
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Concurrent task quotas are also Region-specific, and the live quotas documentation distinguishes quota rows that should not be collapsed into one universal limit. Its current table lists concurrent SV1/DM1 task maxima of 100 in us-east-1, 50 in us-west-1, 100 in us-west-2, and 50 in eu-west-2; it also identifies an adjustable SV1 (DM1) quota maximum of 60 per Region. Because these entries depend on the particular quota row and Region, verify the applicable live Service Quotas entry for your account rather than treating any one of these figures as universal.
Check task-specific limits before changing the workload
Some failures or long runs can be explained by the selected device’s task limits rather than a queue. Amazon Web Services’ current Braket quotas documentation, accessed in 2026, lists a 5 MB maximum quantum-task action size. It lists SV1 maximum running durations of 3 hours for circuits up to 31 qubits and 11 hours for circuits above 31 qubits. These are simulator-specific limits, not general QPU time estimates.
The same documentation lists a maximum of 50,000 shots per task for SV1, DM1, and Rigetti devices. Other listed limits differ by provider and device—for example, AQT IBEX-Q1 is listed at 2,000 shots and QuEra Aquila at 1,000; IonQ has an on-demand minimum of 100 shots and gate limits. Check the current limit for the exact device and task mode before altering shots or circuit size.
Do not mistake a local polling timeout for remote failure
The SDK’s task.result() polls for completion. AWS documents a default poll_timeout_seconds of 432,000 seconds (five days), recommends allowing a few days for QPUs such as Rigetti and IonQ, and warns that a shorter client timeout can occur while a QPU is unavailable. A local timeout does not prove that the remote task failed. Look up the task’s remote state by ARN before resubmitting, so a still-active task is not duplicated.
Monitor recurring incidents and state changes
- Use the console’s Quantum Tasks search to filter by task ARN, status, device, and creation time; task details show a dynamic queue position.
- Use CloudWatch Braket device metrics to monitor activity and concurrency by device.
- Use SDK state tracking and retrieve results from the task’s S3 output location after completion.
- For automated notifications, route task state-change events through EventBridge to SNS, Lambda, or Step Functions.
Amazon Braket documentation says these events are delivered at least once and may arrive out of order. Make event consumers tolerant of duplicates; when ordering matters, use event timestamps and terminal status together with a fresh task lookup rather than treating the event stream as exactly once or strictly ordered.
Quick Recap
A practical decision path
- If the remote state is
QUEUED, inspect device availability, queue counts, and task position; save a timestamped snapshot and wait or investigate device status. - If the state is
FAILED, use the error to check access, the S3 output path, SDK compatibility, quotas, request rates, or task-specific limits. - If only
task.result()timed out, query the task ARN for its remote state before retrying. - If the incident recurs, retain task and device identifiers, Region, timestamps, error details, queue observations, and output location, then monitor by device and state-change events.
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