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Amazon ECS can detect a failed NVIDIA GPU and replace the affected container instance automatically, but the documented GPU health and repair workflow applies to Amazon ECS Managed Instances. It is not a general feature of every ECS cluster backed by ordinary EC2 container instances or an Auto Scaling group.

For a Managed Instances capacity provider, enable autoRepairConfiguration.actionsStatus as ENABLED, select GPU-capable instance requirements, and verify health with DescribeContainerInstances. ECS uses NVIDIA Data Center GPU Manager (DCGM) checks; when a critical failure marks an instance IMPAIRED, ECS drains it, starts a replacement, allows tasks to stop within their configured timeouts, and then terminates the impaired host.

What ECS GPU instance health checks actually cover

Amazon Web Services describes the boundary directly: “Amazon ECS monitors NVIDIA GPU health on Amazon ECS Managed Instances that use GPU hardware.” The signal is an instance-level health result, not a command executed inside an application container.

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Managed Instances combine ECS capacity management with a provider configuration that specifies the cluster, networking, infrastructure permissions, and instance requirements. When those requirements include an accelerator type and count, ECS can run accelerated-compute checks in addition to its other container-instance checks. NVIDIA DCGM supplies the GPU health signal.

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A critical GPU fault can change the container instance’s overall health to IMPAIRED. The instance’s statusReason may contain an NVIDIA XID identifier in the form XID_<number>. The XID is a diagnostic clue to preserve in incident records; it is not, by itself, a promise that every XID has the same root cause or recovery procedure.

Feature boundary: Managed Instances versus ordinary EC2 capacity

The automatic GPU-repair procedure documented by ECS is for a capacity provider whose compute type is Amazon ECS Managed Instances. A capacity provider backed by an EC2 Auto Scaling group is a different operating model. The material here does not establish that the Managed Instances DCGM repair action is available there, so do not assume that setting an Auto Scaling group health check creates an equivalent ECS GPU repair workflow. For EC2-backed capacity, use the health, replacement, and scaling controls belonging to that provider and validate their GPU behavior separately.

How the health signal differs from a task health check

There are two separate layers. Confusing them can produce a healthy service on a failed host or an unnecessarily replaced task.

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Layer What it evaluates Typical response Use this wording
ECS container or task health A health-check command from the task definition, executed inside the container For an unhealthy task in an ECS service, the service scheduler stops that task and launches a replacement according to service deployment rules Application or container health
ECS Managed Instances container-instance health Host and runtime checks, ECS agent connectivity, accelerated-compute checks such as NVIDIA DCGM, and supported managed-daemon checks If the instance is IMPAIRED and automatic repair is enabled, ECS drains and replaces the instance Instance or GPU hardware health

A container health command can prove that a process responds to an endpoint while the GPU on the host is unusable. Conversely, a GPU host can be healthy while one model-serving process is wedged. Configure and monitor both layers when the application depends on GPU availability.

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Prerequisites before creating the provider

Prepare these items before attempting to enable repair:

  • An ECS cluster that will use an Amazon ECS Managed Instances capacity provider.
  • The infrastructure role and instance profile required by Managed Instances, with permissions as described in the ECS Managed Instances capacity-provider documentation.
  • VPC, subnet, and security-group choices that let the instance reach ECS control-plane endpoints, pull images, and send logs and metrics.
  • Instance requirements that select GPU hardware, either by accelerator type and count or by appropriate GPU instance types. A requirement that selects only CPU and memory cannot satisfy a GPU workload.
  • A task definition and service or run-task configuration that uses the Managed Instances capacity provider strategy.
  • ECS agent version 1.57.0 or later for the automated container-instance checks documented by ECS.

Capacity-provider configuration is the control plane for repair. A task definition’s healthCheck property does not turn on host replacement.

Create a GPU-capable Managed Instances capacity provider

Choose the provider in the ECS console

  1. Open the Amazon ECS console and select the target cluster.
  2. Open the cluster’s capacity-provider configuration and choose the option to create or associate an Amazon ECS Managed Instances capacity provider. Do not select an Auto Scaling group provider if your goal is this specific managed GPU repair workflow.
  3. Enter the required infrastructure role and instance-profile settings.
  4. Configure the network: VPC, subnets, security groups, and any required connectivity settings.
  5. Set instance requirements that include the accelerator type and the number of GPUs required by the workload, or select GPU instance types supported by the Managed Instances configuration.
  6. In automatic repair settings, set the actions status to ENABLED.
  7. Create the provider, associate it with the cluster, and use its capacity-provider strategy when deploying services or running tasks.

Console labels can vary as the ECS console evolves. The important values are the Managed Instances compute model, GPU-inclusive instance requirements, and the provider’s automatic-repair action status.

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Create or update the provider through the API

The API field is managedInstancesProvider.autoRepairConfiguration.actionsStatus. The following fragment shows the relevant shape; replace surrounding fields with the required cluster, role, network, and instance-requirement values for your account. It is an illustrative configuration fragment, not a tested, copy-and-paste command.

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{
  "managedInstancesProvider": {
    "autoRepairConfiguration": {
      "actionsStatus": "ENABLED"
    }
  }
}

Use ENABLED to permit automatic replacement after ECS declares an instance impaired. Use DISABLED when you want monitoring without an automatic repair action—for example, during a controlled investigation. AWS states that GPU auto repair is enabled by default for Managed Instances, but inspect the actual provider rather than relying on that default.

For an existing provider, use the capacity-provider update operation to change the Managed Instances configuration, then read the resulting provider configuration and confirm the stored value. A successful API request is not sufficient evidence that the provider is using the intended GPU requirements or that the setting was applied to the provider associated with your production cluster.

Verify that ECS is collecting instance health

Query health with the ECS API or CLI

Call DescribeContainerInstances with the CONTAINER_INSTANCE_HEALTH include value. Supply the cluster and one or more container-instance identifiers:

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aws ecs describe-container-instances 
  --cluster <cluster-name> 
  --container-instances <container-instance-arn-or-id> 
  --include CONTAINER_INSTANCE_HEALTH

Inspect healthStatus.overallStatus and each entry in healthStatus.details. ECS documents these overall states:

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  • OK: the evaluated checks are healthy.
  • IMPAIRED: at least one critical check has failed and the instance is considered impaired.
  • INSUFFICIENT_DATA: ECS cannot yet make a reliable health determination.
  • INITIALIZING: checks are still starting.

The most severe check status determines the overall status. During a GPU incident, also inspect the container instance’s statusReason for an XID_<number> value and record the individual detail entries. An INITIALIZING or INSUFFICIENT_DATA result is not the same as a confirmed GPU failure and should not be treated as one.

Check the agent and event stream

Automated container-instance checks require ECS agent version 1.57.0 or later. Confirm the agent version on the instances and watch ECS container-instance health change events. Correlate the event time with task placement, the transition to DRAINING, service deployment activity, and CloudWatch metrics. This separates a DCGM failure from an agent-connectivity problem, a networking interruption, or an application-level task failure.

What happens after a GPU instance becomes impaired

With automatic repair enabled, ECS uses a start-before-stop sequence rather than simply rebooting the same host. The documented order is:

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  1. Drain the impaired instance. ECS sets the container instance to DRAINING, preventing new tasks from being placed there.
  2. Provision a replacement. Managed Instances obtains replacement capacity that satisfies the provider’s requirements, including its GPU requirements.
  3. Stop existing tasks gracefully. Tasks on the draining instance are allowed to stop according to their task stop-timeout settings. Services can then place replacement tasks on available capacity.
  4. Terminate the impaired instance. After draining, ECS removes the failed host.

Tasks do not continue uninterrupted on the same physical host. Applications should therefore tolerate task termination, restart, and model or cache initialization on a new instance. Set task stop timeouts long enough for the application to flush state, but do not assume that a long timeout makes the host usable while its GPU is failing.

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Repair rate limits

Repair is deliberately capacity-aware. ECS limits draining to no more than 20% of a capacity provider’s instances at one time. For a provider with fewer than nine instances, at most one instance drains at a time. A small GPU fleet can therefore recover serially, and a second impairment may wait until the first repair has progressed. Design service desired counts and spare capacity with this limit in mind.

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Observability for GPU incidents

Container-instance health details

Use DescribeContainerInstances --include CONTAINER_INSTANCE_HEALTH as the authoritative ECS view of the health decision. Capture the overall status, detail names and statuses, status reason, instance identifier, and timestamps from your surrounding event and logging systems. Preserve the XID code when present; it helps correlate the ECS decision with NVIDIA and operating-system diagnostics.

Container Insights GPU metrics

A health status tells you that ECS considers a check healthy or impaired; it is not a time series of utilization, memory use, or per-container GPU activity. AWS documents enhanced observability in Container Insights for NVIDIA DCGM metrics on GPU-enabled Managed Instances. With enhanced observability, GPU telemetry can be collected at container, task, and instance levels. Basic Container Insights does not collect those GPU metrics. Enable the enhanced mode when you need utilization and workload-level context, and keep the ECS health events for replacement decisions.

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Useful correlations during an incident

  • Compare the first IMPAIRED event with DCGM and CloudWatch metric timestamps.
  • Check whether the service scheduler placed replacement tasks after the instance entered DRAINING.
  • Look at task stop reasons and stop-timeout behavior to identify slow shutdowns.
  • Verify that the replacement instance registered with the cluster and passed its initial health state before expecting GPU tasks to start.
  • Review whether the provider had enough healthy capacity for the 20% drain limit and the service’s desired count.

Application health checks still matter

Define a task-level health check for the failure modes your application can detect: for example, a local inference endpoint that verifies model readiness or a worker process that must answer a diagnostic command. ECS runs that command inside the container and can replace an unhealthy service task. Keep the command focused on application readiness rather than trying to reproduce DCGM’s host-level checks in shell code.

Use instance health for host and GPU failures, task health for process and application failures, and service deployment settings for how replacements are rolled out. None of these layers guarantees that a stateful job can resume from the same point; checkpoint long-running GPU work to durable storage when interruption is unacceptable.

Troubleshooting decision tree

The instance is healthy, but the GPU workload is failing

  • Inspect the task health result, container logs, and application-level GPU initialization errors.
  • Check enhanced Container Insights DCGM metrics for abnormal utilization, memory, or error patterns.
  • Confirm that the task landed on a GPU-capable Managed Instances provider and received the expected GPU allocation.
  • If only the application is unhealthy, let the service scheduler replace the task rather than forcing host repair.

The instance is IMPAIRED

  • Read healthStatus.details and statusReason from DescribeContainerInstances.
  • Record any XID_<number> identifier and correlate it with the health-change event and DCGM telemetry.
  • Confirm the provider’s actionsStatus. If it is DISABLED, ECS will continue monitoring but will not perform automatic repair.
  • Check whether the instance is already DRAINING and whether the repair-rate limit is delaying another drain.

The status remains INITIALIZING or INSUFFICIENT_DATA

  • Verify the ECS agent is version 1.57.0 or later.
  • Check agent connectivity, instance networking, and registration state.
  • Allow the checks to initialize before declaring a hardware failure.
  • Look for health-change events and detail-level results rather than relying only on the overall state.

No replacement appears

  • Confirm that the compute provider is Amazon ECS Managed Instances, not an EC2 Auto Scaling group capacity provider.
  • Read the provider configuration and verify autoRepairConfiguration.actionsStatus is ENABLED.
  • Check that the provider can launch an instance satisfying its GPU accelerator requirements in the selected subnets and availability zones.
  • Review the 20% or one-instance drain limit, desired service capacity, and any task stop timeouts that keep the impaired host in the draining phase.

Operational checklist

  • Use Amazon ECS Managed Instances for the documented GPU auto-repair flow.
  • Select accelerator type and count, or GPU instance types, in the provider’s instance requirements.
  • Install or verify ECS agent version 1.57.0 or later.
  • Set and verify managedInstancesProvider.autoRepairConfiguration.actionsStatus as ENABLED.
  • Query DescribeContainerInstances with CONTAINER_INSTANCE_HEALTH.
  • Alert on IMPAIRED, health-change events, and GPU-related statusReason values.
  • Enable enhanced Container Insights when container-, task-, and instance-level NVIDIA DCGM metrics are required.
  • Test service behavior when a task is stopped and relaunched on replacement capacity.
  • Plan for graceful shutdown, checkpointing, and startup time on a newly provisioned GPU host.
  • Document a separate recovery procedure if the cluster uses ordinary EC2 instances or an Auto Scaling group.

Configuration example in context

A practical rollout is to create a Managed Instances provider with GPU-inclusive requirements and automatic repair enabled, associate it with the cluster, and deploy a small canary service using that provider strategy. Query the registered container instance until its health state is OK, then verify that the service receives GPU-capable placement. During normal operation, retain health-change events and DCGM metrics. During an impairment, let ECS perform the documented drain-and-replace sequence while the service scheduler restores task count on the replacement capacity.

Do not interpret a successful canary deployment as proof that every GPU failure mode is repaired instantly. Replacement is capacity- and timeout-dependent, and the documented drain limits are especially significant for small providers.

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