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No. Amazon ECS GPU auto-repair for Managed Instances replaces an impaired GPU host; it does not live-migrate a running task or copy the host’s local files. ECS detects a critical GPU fault with NVIDIA Data Center GPU Manager (DCGM), marks the instance impaired, drains it, gives tasks their configured shutdown window, starts replacement capacity, and then terminates the original instance. Service tasks can be started again by the service scheduler, but a task’s in-memory state and host-only data are not transparently preserved.
What ECS GPU auto-repair actually does
This feature applies to Amazon ECS Managed Instances configured for GPU workloads. GPU health is monitored by NVIDIA DCGM. Critical conditions, including classes of Xid errors such as an uncorrectable ECC failure, a GPU falling off the bus, or a GPU stopping processing, can mark an instance unhealthy. The complete trigger list is maintained in the AWS GPU auto-repair documentation.
The repair is host replacement, not migration. The normal sequence is:
- ECS detects a critical GPU health condition and marks the managed instance impaired.
- The instance is placed in
DRAINING, so the scheduler can move service work away from it. - ECS provisions replacement capacity through the capacity provider.
- Tasks on the impaired host receive their configured stop signal and task stop timeout.
- The original instance is terminated after draining and replacement processing.
The stop window is intended to reduce abrupt termination. It does not keep a process running while ECS moves it to another host, and it does not transfer RAM, GPU state, open connections, or an unfinished in-memory computation.
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How much repair can happen at once?
AWS limits concurrent draining to protect the capacity provider: “No more than 20% of the instances belonging to the capacity provider can be drained at a time. If there are fewer than 9 instances in the capacity provider, at most one instance is drained at a time.” See the GPU auto-repair guidance for the current rule. This is a repair-rate limit, not an uptime guarantee. A replacement can still take time to launch, register, pass health checks, and obtain a usable GPU.
What happens to running tasks?
Tasks managed by an ECS service
Service tasks are governed by the service deployment settings while the instance drains. minimumHealthyPercent determines how far the service may fall below its desired count during replacement. maximumPercent determines whether ECS may start replacement tasks before stopping old ones. If the cluster has enough registered GPU capacity, ECS may overlap new and old tasks. With restrictive percentages or insufficient capacity, it may have to stop an old task before a replacement can start. Therefore, auto-repair can result in interruption even when the service eventually returns to its desired count.
| Service setting or condition | Effect during GPU-instance draining |
|---|---|
minimumHealthyPercent |
Sets the lower bound for healthy running tasks ECS tries to maintain while replacing tasks. |
maximumPercent |
Sets the upper deployment capacity, allowing overlap of replacement and old tasks when resources are available. |
| Available GPU capacity | Determines whether replacements can be placed before old tasks stop; a percentage alone cannot create missing GPUs. |
| Task health checks and startup time | Control when a replacement is considered healthy and able to serve traffic. |
Read the API behavior for draining in UpdateContainerInstancesState. It describes scheduler behavior, but it does not promise zero downtime or state transfer.
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Standalone tasks
A standalone task is not continuously reconciled to a desired service count. A manually drained instance does not automatically cause ECS to launch a replacement for that task; it normally runs until it finishes or an operator stops it. GPU auto-repair is different because the impaired host is ultimately terminated. A standalone task on that host can therefore be stopped by host replacement without an automatic re-run. Use an external job controller, an ECS service, or another retry mechanism when the work must be resubmitted after failure.
How shutdown is delivered
For Linux containers, ECS sends the configured stop signal, which is SIGTERM by default. If the process remains alive after the task’s configured StopTimeout, ECS sends SIGKILL; this lifecycle is documented in Amazon ECS task lifecycle. Install signal handling in the application, stop accepting new work, checkpoint progress, flush logs, and close files within that interval. A graceful signal only provides an opportunity to save state; it cannot guarantee that every workload finishes its checkpoint before the timeout.
Does local data survive replacement?
Bind mounts and an EC2 sourcePath
A bind mount exposes a directory from the host inside the container. An explicit EC2 sourcePath can remain on that particular host while the host exists, as described in Specify a bind mount in an Amazon ECS task definition. It is not replicated to another instance. When auto-repair terminates the impaired host, a replacement instance has a different filesystem and does not contain those files. ECS explicitly states that it does not synchronize storage across Amazon EC2 instances.
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Instance-store data is tied to the physical host. AWS states that “Instance store volumes are ephemeral. Data on instance store volumes is lost when the instance is stopped, terminated, or when hardware fails. Do not use instance store for data that must persist.” Because GPU auto-repair terminates the old instance, checkpoints, model artifacts, caches, and logs stored only there should be treated as lost.
EBS, EFS, and independent storage
Storage must be evaluated by lifecycle and attachment behavior, not by the label “volume.” The ECS storage options guide and EBS volume configuration guide describe supported modes and settings.
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| Storage | Outlives the task? | Outlives the original host? | Available to a replacement task? | Critical qualification |
|---|---|---|---|---|
| Container writable layer | No; it disappears with the task. | No. | No. | Use only for disposable runtime data. |
| Bind mount without durable external storage | Often only while the host and path remain. | No guarantee. | Not automatically. | sourcePath is host-specific; ECS does not copy it. |
| Instance store | Not reliably. | No. | No. | Lost on termination, stop, or hardware failure. |
| EBS | Depends on attachment and task lifecycle. | Potentially, depending on configuration. | Only when ECS can attach it under the supported mode. | Persistence and deletion-on-termination settings must be checked for the deployment. |
| EFS or another network-backed durable service | Yes, subject to that service’s own durability and access controls. | Designed to be independent of one host. | Generally usable by a replacement task when networking and permissions are correct. | Validate mount targets, security groups, identity permissions, and performance needs. |
Do not assume every EBS volume survives simply because EBS is persistent. Verify whether the volume is task-attached or instance-attached, whether it is retained or deleted when the task or instance ends, and whether a replacement task can attach it in the target placement. For shared files that must be available on another GPU host, a service such as EFS may be more appropriate. The correct choice depends on throughput, latency, concurrency, and recovery requirements.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to configure and verify auto-repair
GPU auto-repair is enabled by default for Amazon ECS Managed Instances. The autoRepairConfiguration setting exposes actionsStatus. Setting it to DISABLED stops automatic replacement while ECS continues monitoring GPU health; the field and allowed values are documented in the AutoRepairConfiguration API reference.
Disabling GPU auto-repair has a side effect: AWS documents that it also disables managed-daemon auto-repair. That can be useful during a controlled investigation, but it leaves an impaired host in service until you remediate it yourself. Treat the setting as an operational choice, not as a data-protection feature. Turning repair off does not make local files portable or preserve a running process.
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Designing GPU workloads for host loss
Persist checkpoints outside the instance
Write model checkpoints, job offsets, and other restartable state to storage independent of the GPU host. Keep only caches and reconstructable scratch data on bind mounts or instance store. A checkpoint should be complete and versioned before the application acknowledges the associated unit of work.
Make replacement safe
- Handle
SIGTERMand stop accepting new work immediately. - Flush or checkpoint within the configured
StopTimeout, then exit cleanly. - Make jobs idempotent so a retry cannot corrupt results or duplicate an external side effect.
- Store task progress separately from container-local files.
- Ensure the image, model dependencies, and GPU runtime can initialize on a newly provisioned instance.
Leave placement headroom
Test the service with enough spare GPU capacity for replacement tasks to overlap old tasks when that behavior is required. Review deployment percentages together with actual capacity-provider size; increasing maximumPercent cannot help if no compatible GPU is available. Capacity planning should also account for the repair concurrency limit and the time needed for a new instance to become healthy.
Observe the whole recovery path
Alert on DCGM health failures, ECS instance state changes, task stops, replacement-task launch failures, and storage-attachment errors. Record the task stop reason and application checkpoint location. A service that returns to its desired count can still have dropped requests or incomplete jobs, so monitor business-level completion as well as ECS task count.
Recovery runbook for an impaired GPU instance
- Confirm the scope: verify that the affected capacity is an ECS Managed Instance and identify the GPU health event.
- Check service desired count,
minimumHealthyPercent,maximumPercent, and available compatible GPU capacity. - Inspect stopped-task reasons and application logs to determine whether the process checkpointed before termination.
- Verify that required data is in independent storage and that the replacement task has the required network, IAM, and volume permissions.
- For standalone work, resubmit the job through its scheduler or operator-controlled retry path; do not wait for ECS service reconciliation.
- After recovery, remove stale host-local assumptions, review the stop timeout, and test restart from the latest durable checkpoint.
Common assumptions that cause data loss
- “Draining means the process keeps running elsewhere.” Draining controls placement and shutdown; it is not live migration.
- “A bind mount is persistent.” It can persist on one EC2 host but does not follow that host’s replacement.
- “EBS always survives.” Attachment mode and deletion settings determine the result.
- “A standalone task will restart.” Standalone tasks have no service desired-count controller.
- “The 20% limit guarantees availability.” It limits simultaneous drains but says nothing about application readiness, capacity shortages, or state durability.
For the authoritative behavior and current limits, consult AWS documentation for GPU auto-repair, task storage, and the task lifecycle.
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