Dynamic Endpoint Transfer
Servers change.
Files still reach the right place.
In GPU, Cloud, Kubernetes and Edge environments the server that runs the work keeps changing. INNORIX delivers the datasets and files to the endpoint your existing infrastructure selected, so the transfer target never has to be set up again.
Dataset StorageObject Storage (S3) · training-dataset
- training-data1.2 TB
- pretrained-model480 GB
- image-dataset820 GB
- auxiliary-data120 GB
4 datasets2.62 TB
Target ConditionThe target is named by condition.
- GPU
- Training
- Ready
Endpoint Selected
Available EndpointsThe endpoints your infrastructure holds
- GPU-01Seoul | NVIDIA H100Busy
- GPU-07Seoul | NVIDIA H100Released
- GPU-12US West | NVIDIA A100Offline
- GPU-24Tokyo | NVIDIA L40SSelected
Selected1Ready0Unavailable3
Endpoint Selection
The destination is not fixed.
It is chosen by condition.
Instead of pinning a transfer to one server’s IP address or name, the endpoint can be named by condition: role, region, workload and status.
Your infrastructure picks the endpoint that matches, and INNORIX delivers the data to it. The machine differs from run to run; the transfer setup does not change.
Target ConditionThe conditions that name the target.
- RoleGPU Compute
- RegionSeoul
- WorkloadTraining
- StatusReady
Available EndpointsSelected by your infrastructure
- GPU-03Seoul | NVIDIA H100Available
- GPU-07Seoul | NVIDIA H100Selected
- GPU-12Tokyo | NVIDIA A100Available
Dynamic Infrastructure
Servers come and go.
The transfer stays the same.
A Cloud VM, a GPU compute node or a Kubernetes Pod is created when the work starts and released when it ends. A transfer built on a fixed server cannot follow that.
INNORIX delivers the dataset once the endpoint is ready, and collects the result data into the storage you named when the job is done. Creating and releasing the server stays with your own infrastructure.
Endpoint lifecycleThe transfer follows the endpoint from creation to release.
- 1. CreatedThe endpoint is created.Created
- 2. ReadyThe environment for the job is ready.Ready
- 3. Data DeliveryThe required data is delivered.Delivered
- 4. Job RunThe job runs on the delivered data.Finished
- 5. CollectionThe result data is collected back.Collected
- 6. ReleasedThe endpoint is released when the job ends.Released
Infrastructure Integration
Your systems decide where the work runs.
INNORIX delivers the files.
A Kubernetes scheduler, a GPU scheduler, a cloud orchestrator or an edge manager keeps deciding what runs where. File transfer is connected to it without changing any of that.
Once your system has chosen a Pod, a GPU server or an edge device, INNORIX transfers the files to the endpoint it was handed and returns the progress and the result for the next step.
Transfer integrationThe transfer goes to the endpoint your system selected.
Existing Infrastructure
- Kubernetes SchedulerSelects the target Pod
- GPU SchedulerSelects the target GPU node
- Cloud OrchestratorSelects the compute instance
- Edge ManagementSelects the target edge device
Selected Endpoint
Transfer Continuity
The target differs every run.
The result is never lost.
The same transfer condition picks a different endpoint on every run. INNORIX records the endpoint each run used, the files it carried, the progress and the result.
When a transfer breaks off, resume and retry pick it up instead of sending everything again, and the failure and its recovery stay visible. Runs spread over many GPU servers and temporary resources are followed in one place.
Training Data DeliveryTarget Condition | GPU · Training · Ready
Every one of these capabilities,on a single platform.
The capability on this page is one of the many file transfer features INNORIX Platform provides. From file transfer to automation and unified operations, try every feature free.
Start FreeConsidering transfer to changing Endpoints?
We'll help you review the Dynamic Transfer setup you need across Cloud, Kubernetes, and distributed environments.
- Review of your Dynamic Infrastructure environment
- Proposal for an Endpoint and Group connection method
- Guidance on integrating with your existing Orchestrator