Validate Compose GPU reservation fields before deployment

Bottom line: Review the reservation object before treating a rejected deployment as a driver or application problem. Check the required fields and conflicting selectors in the managed Compose definition, then leave actual accelerator suitability to its separate acceptance procedure.

Source fact: documented behavior

The Run Docker Compose services with GPU access documentation is the primary reference.

The Compose GPU guide requires capabilities in the reservation; omitting it produces a service-deployment error. The count and device_ids fields are mutually exclusive and must not be defined together. The guide also documents errors for an invalid device ID or a requested count larger than the available GPU population.

What the source does not establish

This article covers the Compose reservation validation contract. It does not repeat generic Engine GPU-selection commands, certify a GPU model or prove CUDA or graphics suitability. Obtain the exact supported host, driver, toolkit and application requirements independently. Keep resource assignment, workload isolation and measured acceleration separate from a definition passing deployment validation.

Applicability questions

• Does the managed reservation contain the required capability declaration?
• Does it use one selector form rather than both?
• Do the proposed identifiers or count agree with the actual host?
• Which separate application check will establish useful accelerator behavior?

DSE recommendation: review the reservation as one configuration object

DSE recommends validating the complete Compose GPU reservation object before diagnosing application acceleration.

Locate the actual service definition used by the managed deployment and identify the exact reservation object. Have the application and platform owners state the intended device allocation separately. Preserve the original definition and keep reusable examples out of the operational configuration until their fields have been reviewed for the target host.

Inspect the capability declaration and selector fields together. Resolve an omitted required field or a combination of both selector forms before changing unrelated driver settings. Keep the selected count or identifiers matched to a current permitted host inventory, and mark any mismatch as a configuration issue to resolve rather than substituting numbers until deployment succeeds.

Use the installed Compose version’s supported model-inspection and deployment workflow in an approved test environment. Preserve the actual stage and error when a definition is rejected. Do not claim that static inspection exercised every runtime validation path; distinguish an inspected object from an attempted service deployment and an application observation.

After the reservation is accepted, have the application owner perform its independently approved functional check. Retain the exact accelerator assignment with that result. A valid reservation should advance the investigation without becoming a compatibility or performance statement about the workload.

Verification and evidence

Proposed verification, not performed: prepare harmless reservation desk cases with a missing capability declaration, both selector fields present, an unknown fixture identifier and a count beyond the fixture inventory. Require a reviewer to identify the documented configuration problem in each before any deployment.

Exercise only approved cases on an appropriately configured disposable host, preserving whether the tool rejected model handling or service deployment. Compare a corrected object with the current host inventory, then run the separate harmless application check if authorized. Retain definitions, inventory references, tool outcomes and actual assignment without interpreting a successful configuration as measured GPU acceleration.

Official references

• Run Docker Compose services with GPU access — Docker Docs.

Source review completed October 29, 2026. Recheck the official documentation and deployment-specific applicability before a production change.