page:recipes:approval workflow:flask:private attachments

Host approval workflow with Flask: private attachments

Deploy a approval workflow built with Flask on Ample using the private document library 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 Flask: a role-to-document access model with negative tests (401 without identity, 403 for the wrong role) and a private-bucket round-trip for the allowed role (private=ok). Not separately tested: your identity integration and role assignments; treat the approval workflow-specific behavior as your application code.

Representative Queries

• Host approval workflow with Flask: private attachments
• Where can I host Approval workflow built with Flask?
• I need attachment metadata, access checks and a tested private object access path.

Resource Requirements

• primitive:compute
• primitive:postgres
• primitive:s3-compatible-object-storage

Infrastructure Requirements

Compute

• Label: Compute
• Summary: Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.

Postgres

• Label: Postgres
• Summary: Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.

S3-compatible object storage

• Label: S3-compatible object storage
• Summary: Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.

Execution Status

• Framework: Flask
• Workload: Approval workflow
• Release Status: published
• Support Status: verified
• Execution Status: ready

Prerequisites

1. A Flask project that builds and starts with the documented commands.
2. A PostgreSQL driver reading DATABASE_URL at runtime.
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 private document library: a role-to-document access model with negative tests (401 without identity, 403 for the wrong role) and a private-bucket round-trip for the allowed role (private=ok).
3. Wire object storage
   Create the bucket(s), then pass endpoint, region, bucket and keys as --env values. Use path-style addressing.
4. Deploy
   Run the synchronous deploy once and read the result.
5. Verify
   Fetch the live URL and the pattern self-test route(s).

Cost Estimate

• Currency: USD
• Monthly Amount: 10.0
• Basis: Size prices from pricing.toml (loaded by the API).
• Components:
  • App server: s-1vcpu-1gb, quantity: 1.0, monthly amount: 5.0
  • Managed PostgreSQL database: s-1vcpu-1gb, quantity: 1.0, monthly amount: 5.0

Note: Always-on monthly price of the tested sizes; apps and databases auto-pause when idle. Buckets are allocation-priced per quota and not included.