page:recipes:rest api:starlette:artifact storage

Host rest api with Starlette: stored input and output artifacts

Deploy a rest api built with Starlette on Ample using the generated downloads pattern. Compute runs the app in an isolated microVM behind a public HTTPS URL, a managed PostgreSQL 16 database is auto-provisioned and injected as DATABASE_URL, a private S3-compatible bucket holds objects with credentials delivered as encrypted environment variables. Verified on Starlette: an export query rendered to a CSV artifact stored with metadata in a private bucket and returned only to an authorized caller (401 without token, export=ok rows=3). Not separately tested: your export formats, retention policy and entitlement model; treat the rest api-specific behavior as your application code.

Representative Queries

Resource Requirements

Infrastructure Requirements

  1. Compute
    Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.
  2. Postgres
    Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.
  3. S3-compatible object storage
    Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.

Prerequisites

Workflow Steps

  1. Build and start
    pip install into .ample/python from requirements.txt, then uvicorn from run.py reading PORT on the python-3.12 template. The server must bind 0.0.0.0 on PORT.
  2. Implement the pattern on PostgreSQL
    The fixture's module implements generated downloads: an export query rendered to a CSV artifact stored with metadata in a private bucket and returned only to an authorized caller (401 without token, export=ok rows=3). Keep migrations idempotent and run them with --release-command.
  3. Wire object storage
    Create the bucket(s), then pass endpoint, region, bucket and keys as --env values. Use path-style addressing. Keep private data in an unpublished bucket.
  4. Deploy
    Run the synchronous deploy once and read the result (exit 0 live, 1 failed, 2 blocked). Re-running with no change is a no-op.
    ample deploy . --name  --public --start "python3 run.py" --env S3_ENDPOINT=... --env S3_REGION=... --env S3_BUCKET=... --env S3_ACCESS_KEY_ID=... --env S3_SECRET_ACCESS_KEY=..."
    
  5. Verify
    Fetch the live URL and the pattern self-test route(s) (/p/generated-downloads) from the example; then run your own checks.
    ample logs  --kind build
    

Examples

Success Checks

  1. App responds on its public URL
    HTTP GET /
    Expect: ample canary starlette patterns
  2. Generated-downloads self-test
    HTTP GET /p/generated-downloads
    Expect: export=ok rows=3 (with ?token=...; 401 without)

Limitations

Cost Estimate

Evidence Summary

  1. Canary Run
    Starlette pattern fixture deployed on Ample; checks passed for generated-downloads and configuration-secrets.
  2. Canary Run
    The same Starlette app deployed with a --release-command migration; the marker it created was readable after activation.

Last Verified At

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