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Amazon ECS GPU auto-repair monitors NVIDIA GPU health on GPU-enabled Amazon ECS Managed Instances. When NVIDIA Data Center GPU Manager (DCGM) reports one of the critical failures ECS watches, ECS marks the managed instance impaired and replaces the instance. The process drains tasks, starts replacement capacity, lets running tasks stop within their configured stop timeout, and then terminates the impaired instance.
That is infrastructure replacement, not an in-place GPU repair or a general fix for application, container, driver, capacity, or workload problems. Understanding that boundary is essential when deciding whether to enable the feature and how to respond to an impaired instance.
What ECS GPU auto-repair actually is
GPU auto-repair is an automated response for a specific class of hardware-health failures on Amazon ECS Managed Instances that use NVIDIA GPU hardware. ECS relies on NVIDIA Data Center GPU Manager (DCGM) to monitor the accelerator. If DCGM reports a critical GPU failure that ECS recognizes, the container instance is marked IMPAIRED.
With repair actions enabled, ECS does not attempt to replace a component inside the server. Instead, it replaces the entire managed instance. The replacement workflow is designed to protect scheduling and give tasks an orderly shutdown rather than abruptly deleting the host.
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The practical definition is therefore:
- Detect: DCGM reports a monitored critical GPU event.
- Mark: ECS changes the instance health state to impaired.
- Drain: ECS sets the instance to
DRAINING, preventing new task placement there. - Replace: ECS provisions replacement managed capacity.
- Finish: Existing tasks receive their normal graceful-stop window, then ECS terminates the impaired instance.
The feature is not a promise that every GPU symptom will be detected, that tasks will continue without interruption, or that a replacement host will cure a software defect.
How ECS decides that a GPU is critically unhealthy
DCGM emits NVIDIA Xid error codes for low-level GPU faults. ECS monitors a defined list of Xid codes for GPU auto-repair. The code identifies the hardware-health condition that caused the impairment; it is not an application exception or a diagnosis of your model, kernel, or container code.
| Xid | Condition reported by NVIDIA |
|---|---|
| 46 | GPU stopped processing |
| 48 | Double-bit ECC error |
| 54 | Auxiliary power connector not connected |
| 62 | Internal micro-controller halt |
| 64 | GPU memory remapping failure |
| 74 | NVLink error |
| 79 | GPU fell off the bus |
| 95 | Uncontained memory error |
| 109 | Context-switch timeout |
| 110 | GPU disappeared from the bus |
| 136 | GPU memory page-retirement limit exceeded |
| 140 | Unrecoverable ECC error |
| 142 | GPU memory page retired because of an uncorrectable error |
| 143 | GPU memory page retired after a correctable-error threshold was reached |
| 151 | GPU-to-CPU interconnect error |
| 155 | GPU NVLink flit CRC error |
| 156 | GPU NVLink lane error |
| 158 | GPU InfoROM corrupted |
Only these documented signals are the trigger described for GPU auto-repair. A GPU that is slow, heavily utilized, thermally constrained, misconfigured, or producing application-level errors is not automatically equivalent to an impaired GPU under this mechanism.
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The sequence is intentionally start-before-stop: ECS begins bringing up replacement capacity before it removes the impaired host. That reduces the period during which the capacity provider has fewer usable instances, but it does not make the event invisible to workloads.
- ECS records the GPU failure. The accelerated-compute health check reports the impairment and includes the Xid identifier in its status reason.
- The instance enters
DRAINING. ECS stops placing new tasks on the impaired instance. Tasks already running there are allowed to stop according to ECS draining behavior. - Replacement capacity is provisioned. ECS Managed Instances obtains a replacement instance through the capacity provider.
- Tasks receive their configured stop window. Your task stop timeout determines how long a running task can shut down gracefully while the old host drains. Applications should handle termination signals and persist any state that must survive host replacement.
- The impaired instance is terminated. After draining, ECS removes the old host. Replacement tasks can then be scheduled on healthy capacity, subject to the capacity provider’s available resources and placement rules.
Because tasks stop and restart as part of host replacement, auto-repair should not be described as guaranteed task continuity. Services with multiple task replicas, durable state, and appropriate deployment settings can tolerate the event better than a single long-running task with state held only in local GPU or host storage.
Why repairs are rate-limited
ECS limits concurrent draining so one GPU incident does not trigger a cascading capacity event. No more than 20% of the instances in a capacity provider can be draining at one time. If the capacity provider has fewer than nine instances, ECS drains at most one instance at a time.
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| Capacity-provider size | Maximum instances draining concurrently | Operational meaning |
|---|---|---|
| Fewer than 9 instances | 1 | A second impaired instance waits until the first drain progresses. |
| 9 or more instances | Up to 20% | The limit scales with provider size; it is a concurrency cap, not a completion-time guarantee. |
These limits describe how many replacements may be in progress, not how quickly an individual repair finishes. Provisioning time, task stop timeouts, placement constraints, and available capacity can all affect the elapsed incident time.
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What GPU auto-repair does not fix
The most important operational mistake is treating instance replacement as a universal GPU troubleshooting system. The documented action is replacement after a monitored DCGM failure. Problems outside that boundary remain your responsibility.
Application and model defects
A CUDA kernel bug, invalid tensor operation, out-of-memory condition, deadlock, bad model checkpoint, or incorrect application parameter can crash a task without producing one of the monitored Xid conditions. Replacing the host does not change the application image or its inputs, so the same failure can recur on the replacement.
Container, driver, and runtime configuration
Incorrect GPU resource requests, incompatible CUDA and driver versions, missing device permissions, an invalid container runtime configuration, or an image that cannot initialize the accelerator are workload or environment configuration problems. Auto-repair does not rewrite task definitions, rebuild images, install a different driver, or correct placement requirements.
Non-monitored hardware symptoms
The feature is tied to the listed critical Xid codes. A temperature concern, performance regression, intermittent application timeout, or hardware symptom that DCGM does not report through a monitored code may not mark the instance impaired. Use normal ECS and operating-environment diagnostics for those cases.
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Capacity shortages and placement failures
Replacement is useful only if ECS can obtain and place new capacity. A lack of available GPU instances, restrictive placement constraints, insufficient quotas, or a capacity-provider configuration problem can prevent replacement tasks from starting. Auto-repair does not increase quotas or override placement rules.
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State and data loss
Draining stops tasks; it does not migrate process memory or ephemeral host data to the replacement instance. Persist important state outside the host and make shutdown handling part of the task design. A longer stop timeout gives a task more time to flush state, but it cannot make non-graceful software safe.
How to see the health reason in ECS
You can inspect the state through the ECS container-instance health APIs and events rather than relying only on task symptoms.
DescribeContainerInstances
Use the ECS DescribeContainerInstances operation for the affected cluster and container instance. ECS aggregates individual health checks into the overall container-instance health status. On a GPU-enabled managed instance, the relevant check type is ACCELERATED_COMPUTE.
When that check is impaired because of a monitored GPU event, its status reason contains the NVIDIA code in the form XID_<number>, such as XID_79. Record that value before termination if you need to correlate the infrastructure event with application logs or an incident timeline.
Container-instance health-change events
ECS health-change events provide an event-driven way to detect a transition instead of polling. Use them to notify an on-call system, annotate a deployment or training run, and begin checking whether replacement capacity is registering. The event identifies the health change; it does not by itself prove that an application is healthy after the replacement.
Separate host health from task health
A healthy replacement instance does not imply that every task restarted successfully. Check service deployment events, task stopped reasons, placement failures, and application logs separately. The accelerated-compute check answers whether ECS observed a monitored GPU health failure on the host; task-level diagnostics answer why a workload did or did not recover.
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Is auto-repair enabled by default?
The current ECS GPU auto-repair guide states that the feature is enabled by default for Amazon ECS Managed Instances. The setting belongs to the capacity provider’s autoRepairConfiguration.
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|---|---|---|
| Enabled | Automatically replaces instances reported IMPAIRED because of the monitored GPU health condition. |
Continues monitoring health and applies the drain, replacement, graceful-stop, and termination sequence. |
actionsStatus: DISABLED |
Does not automatically replace an impaired instance. | Continues monitoring and reporting instance health. |
To disable replacement, set actionsStatus to DISABLED in autoRepairConfiguration when creating or updating the capacity provider. Disabling actions changes the response, not the detection: ECS continues to monitor the instance and expose its health state.
The daemon auto-repair interaction
A consequential side effect is that disabling GPU auto-repair also disables Amazon ECS Managed Daemons auto-repair. Managed Daemons auto-repair can drain and replace an instance when a critical daemon task stops or becomes unhealthy. Daemon health checks are optional; without a health check, ECS can detect a daemon failure only when the task stops.
Therefore, disabling GPU replacement to perform manual investigation can also remove automatic recovery for critical managed daemon tasks. Include that dependency in change reviews and runbooks.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.GPU metrics: basic versus enhanced Container Insights
Health state and Xid reasons tell you that ECS considers an instance impaired. They do not provide the same detail as time-series GPU metrics. For supported GPU-enabled ECS Managed Instances, Container Insights with enhanced observability collects DCGM GPU metrics at container, task, and instance levels.
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|---|---|---|---|
| Basic Container Insights | Does not collect GPU metrics. | General ECS monitoring without DCGM GPU metric detail. | No GPU-metric collection through this option. |
| Enhanced Container Insights | Collects DCGM GPU metrics for supported GPU-enabled managed instances at container, task, and instance levels. | Trend analysis, utilization visibility, and correlating workload behavior with GPU telemetry. | AWS states that enhanced Container Insights incurs additional cost. |
Enhanced metrics complement, rather than replace, health-change events and DescribeContainerInstances. Metrics may show a developing utilization or error pattern, while the accelerated-compute check and Xid reason identify the monitored critical event that caused impairment.
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A practical incident runbook
Before an incident
- Confirm whether GPU auto-repair is enabled on each relevant capacity provider.
- Document the task stop timeout and verify that applications handle termination signals.
- Use more than one service task where the workload permits, so draining one host does not remove all service capacity.
- Keep important state in durable external storage rather than on the managed instance’s local filesystem.
- Decide how health-change events will reach the on-call team.
- If GPU-level trends matter, enable enhanced Container Insights and account for its additional cost.
- Record the daemon auto-repair dependency before changing
actionsStatus.
When ECS reports an impaired GPU instance
- Identify the affected cluster, capacity provider, and container instance from the health-change event.
- Call
DescribeContainerInstancesand inspect theACCELERATED_COMPUTEcheck and itsXID_<number>reason. - Confirm that the instance is draining and that replacement capacity is being provisioned.
- Review running tasks’ stop behavior and service deployment events. Distinguish expected draining from an application crash.
- Watch for placement failures on the replacement. If tasks remain pending, investigate capacity availability, quotas, resource requests, and placement constraints.
- After replacement tasks start, verify application readiness and GPU initialization independently of the host health state.
After recovery
Correlate the Xid code, task stop reasons, deployment events, and enhanced GPU metrics if available. If the same application fails on a healthy replacement, focus on the image, runtime, model, inputs, and task definition rather than assuming another hardware repair is needed.
When should you leave auto-repair enabled?
For most production GPU capacity providers, leaving the default enabled behavior in place provides the fastest automated response to the specific critical failures ECS monitors. It removes an impaired host from placement and starts replacement without waiting for an operator to perform the first action.
There are legitimate reasons to disable replacement temporarily: collecting forensic data, coordinating a maintenance window, validating a suspected driver or image problem, or preventing an automated replacement while a broader capacity incident is being contained. If you disable it, continue watching health events because detection remains active, and remember that Managed Daemons auto-repair is disabled at the same time.
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|---|---|---|
| Production service needs automatic removal of failed GPU hosts | Keep actions enabled | ECS can drain and replace an impaired instance without manual initiation. |
| Investigating a suspected software or configuration failure | Consider temporary disablement | Replacement may reproduce the same workload defect and could remove evidence from the original host. |
| Critical managed daemon relies on automatic recovery | Keep actions enabled unless you have a compensating plan | Disabling GPU auto-repair also disables Managed Daemons auto-repair. |
| Need GPU trend and utilization detail | Use enhanced Container Insights in addition to health APIs | Basic Container Insights does not collect GPU metrics. |
The boundary to remember
ECS GPU auto-repair is best understood as a narrowly scoped availability mechanism: DCGM detects selected critical NVIDIA GPU failures, ECS marks the managed instance impaired, and ECS replaces that instance through draining and graceful task shutdown. It does not repair a GPU in place, debug application code, correct a container image, guarantee uninterrupted tasks, or solve a lack of replacement capacity.
Design around that boundary. Use health APIs and events to identify the Xid reason, use enhanced Container Insights when metric history is needed, make tasks restart-safe, and treat software failures and placement problems as separate investigations.
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