Host blog with Flask: Postgres-backed content

Deploy a blog 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 blog-specific behavior as your application code.

Prerequisites

• 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)
• A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env)
• A bucket from ample bucket create with its credentials passed as encrypted S3_* environment variables
• An Ample account token with servers:write, databases:read, buckets:read

Resource 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.

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. 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 Keep private data in an unpublished bucket.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).
5. Verify: Fetch the live URL and the pattern self-test route(s) from the example; then run your own checks.

Cost Estimate

• Monthly Amount: 10.0 USD
  • App server: s-1vcpu-1gb - 5.0 USD
  • Managed PostgreSQL database: s-1vcpu-1gb - 5.0 USD

Limitations

• Verified on the python-3.12 template at s-1vcpu-1gb; other sizes and Flask versions are not verified.
• The blog behavior (your record schema, states and access rules) is application code and was not separately tested.
• Region availability and compliance attestations are unknown.

Examples

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

Success Checks

• App responds on its public URL: Check / with expected response: "ample canary flask patterns".
• Relational-records self-test: Check /p/relational-records with expected response: "records=ok transitions=true isolation=true".