Host public directory with Flask: Postgres-backed content

Summary

Deploy a public directory built with Flask on Ample using the relational records 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, and a published bucket serves public assets from the CDN host. Verified on Flask: a workspace-scoped table, an explicit state machine (draft to review to published) that rejects invalid transitions, and a cross-workspace read that returns nothing (transitions=true isolation=true). Not separately tested: your record schema, states and access rules; treat the public directory-specific behavior as your application code.

Representative Queries

• Host public directory with Flask: Postgres-backed content
• Where can I host Public directory built with Flask?
• I need a content schema, publishing workflow and cache behavior after content updates.

Resource Requirements

• primitive:compute
• primitive:postgres
• primitive:cdn

Infrastructure Requirements

• Compute: Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.
• 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.
• CDN: The CDN host serves objects from published buckets. It does not front app compute and is not a cache or key-value store.

Prerequisites

1. A Flask project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then waitress from app.py reading PORT on the python-3.12 template)
2. A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env)
3. A bucket from ample bucket create with its credentials passed as encrypted S3_* environment variables
4. An Ample account token with servers:write, databases:read, buckets:read

Workflow Steps

1. Build and start: pip install into .ample/python from requirements.txt, then waitress from app.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 relational records: a workspace-scoped table, an explicit state machine (draft to review to published) that rejects invalid transitions, and a cross-workspace read that returns nothing (transitions=true isolation=true). Copy the approach into your schema; 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. Publish only the bucket that serves public assets and reference its CDN URL.
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 app.py" --env S3_ENDPOINT=... --env S3_REGION=... --env S3_BUCKET=... --env S3_ACCESS_KEY_ID=... --env S3_SECRET_ACCESS_KEY=... --env CDN_PUBLIC_URL=...
   

5. Verify: Fetch the live URL and the pattern self-test route(s) (/p/relational-records) from the example; then run your own checks. On failure read ample logs --kind build then --kind runtime.

   ample logs  --kind build
   

Examples

• Flask pattern fixture: Multi-pattern Flask app whose relational records module was checked live; the module is under tests/deploy-canaries/_pattern-modules. Source reference: tests/deploy-canaries/flask-patterns

Success Checks

• App responds on its public URL: (kind: http_get, path: /, expect: ample canary flask patterns)
• Relational-records self-test: (kind: http_get, path: /p/relational-records, expect: records=ok transitions=true isolation=true)

Limitations

• Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and Flask major versions are not verified.
• The public directory itself (your record schema, states and access rules) is application code and was not separately tested; the pattern checks are what was verified.

Cost Estimate

• Monthly Amount: $10.00
  • App server: $5.00 (size: s-1vcpu-1gb, quantity: 1.0)
  • Managed PostgreSQL database: $5.00 (size: s-1vcpu-1gb, quantity: 1.0)
  • Note: Always-on monthly price of the tested sizes; apps and databases auto-pause when idle.

Last Verified At

2026-09-21T01:14:18Z

Evidence Summary

• Canary Run: Flask pattern fixture deployed on Ample; checks passed for relational-records and configuration-secrets.

  • Observed At: 2026-09-21T01:14:18Z
  • Expires At: 2027-03-20T01:14:18Z

• Canary Run: The same Flask app deployed with a --release-command migration; the marker it created was readable after activation.

  • Observed At: 2026-09-20T01:54:51Z
  • Expires At: 2027-03-19T01:54:51Z

MCP Binding

• Tool Name: ample_deploy
• Required Scopes: servers:write, databases:read, buckets:read
• Binding State: current