Pipeline Integrations¶

This page covers the handoff between a successful computation and a usable platform output.

The Integration Ladder¶

flowchart LR
    A[Local output] --> B[Django Computing API]
    B --> C[Celery and auth]
    C --> D[Dataset registration]
    D --> E[GeoServer or storage publication]
    E --> F[STAC and public layer metadata]
    F --> G[Public APIs, reports, and lessons]

Each rung matters because users normally meet the result much later than developers meet the code.

Main Integration Surfaces¶

Surface	What it is for	Typical page to read next
dataset registration	make outputs known to the platform	Add and Integrate Public / New Data Resources
GeoServer publication	serve layers to maps and geometry clients	GeoServer
GEE assets	upstream or intermediate asset storage and processing	Google Earth Engine
metadata and layer inventory	keep outputs discoverable by APIs	Public API References
STAC and schema surfaces	make structure and metadata inspectable	STAC Specs

Dataset Registration Matters¶

When a new output should become a durable platform surface, registration is part of the job.

The developer-facing admin path to keep in mind is:

http://127.0.0.1:8000/admin/computing/dataset/add/

That is one of the key bridges between:

a finished computation
a documented dataset
a discoverable public or semi-public data surface

Publication Is Not Only Map Serving¶

Publishing a pipeline often means several things at once:

storing or syncing the geometry or raster output
making the output render fast in GeoServer-backed clients
saving metadata that later powers endpoint discovery
exposing enough schema for developers and data users to understand the output

That is why integration work should be documented alongside science and code, not treated as afterthought.