Disposable Vast.ai GPU CI

Overview

Use ordinary CPU CI for deterministic tests and reserve Vast.ai for a small GPU acceptance slice. The cloud step must publish its resource ID immediately and make cleanup independent of test success.

Prerequisites

• GPU-only acceptance command and expected machine-readable result
• Scoped CI key, dedicated SSH public key, immutable image digest, and masked logs
• Offer constraints, maximum price, readiness deadline, job timeout, and cleanup escalation

Instructions

Step 1: Gate before provisioning

Run lint, unit, CPU, and image tests first. Skip the GPU job when those fail or when the change does not require hardware acceptance.

Step 2: Create a scoped run manifest

Record commit, image digest, test command, GPU policy, maximum spend, external artifact target, and unique CI run label.

Step 3: Provision one resource

Search compliant verified offers and create exactly one instance. Write the returned instance ID to CI state before any polling or test step.

Step 4: Wait and test

Use structured status, bounded polling, terminal failure branches, and a non-interactive GPU test. Keep command output and logs free of secrets.

Step 5: Publish evidence

Copy the test result, relevant redacted logs, image identity, timings, and cost estimate to durable CI artifacts.

Step 6: Destroy unconditionally

Run destruction in the CI finalizer for success, failure, cancellation, and timeout; confirm removal and alert on cleanup failure.

Authentication

Inject VAST_API_KEY from the CI secret store into the control step only. Use a scoped key without billing-write or team-write and prevent forked or untrusted PRs from receiving it.

Tool Discipline

Use Read and Grep to inspect manifests, configuration, provider output, and existing tests before proposing a mutation. Use Write or Edit only for the approved plan, implementation, test, or redacted receipt; do not create, update, destroy, or fund Vast.ai resources without explicit operator approval.

Output

• CI run and immutable workload manifest
• Provisioning, state, GPU assertion, timing, and cost artifacts
• Unconditional cleanup result and escalation receipt

Return CI run, commit, image digest, offer/instance IDs, test result, elapsed time, estimate, and confirmed destruction.

Examples

A protected-branch workflow runs CPU tests first, rents one verified GPU under a fixed ceiling, executes a five-minute CUDA acceptance test, uploads JSON evidence, and destroys the instance in always() cleanup.

Error Handling

Resources

• First-party source notes
• CLI authentication for CI
• CLI hello world
• Official CLI skill