Pipeline DAG

Pipeline DAG
               _
 .─────.      ╱ ╲      .─────.
(|||||||)═══▶▕   ▏═══▶(|||||||)══════╗
 `─────'      ╲ ╱      `─────'       ║
               ▔                     ║
                                     ▼
               _                     _
 .─────.      ╱ ╲      .─────.      ╱ ╲      .─────.
(|||||||)═══▶▕   ▏═══▶(|||||||)═══▶▕   ▏═══▶(|||||||)
 `─────'      ╲ ╱      `─────'      ╲ ╱      `─────'
               ▔                     ▔

A Pipeline DAG is simply a series of chained processes that in turn produce datasets. The chaining is by subscribing to a source dataset and listening for new arrivals.

DAG of Projects
                             ┌ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ┐
                              Project A
┌ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ┐│      _                │
 Ingress Project                   ╱ ╲      .─────.
│                           ││ ╔═▶▕   ▏═══▶(|||||||)═╬══════╗
   ════▶╔ ═ ═ ╗                ║   ╲ ╱      `─────'         ║
│          _                │└ ╬ ─ ─▔─ ─ ─ ─ ─ ─ ─ ─ ┘      ║
        ║ ╱#╲ ║      .─────.   ║                            ║
│  ════▶ ▕###▏ ════▶(|||||||│══╣                       ┌ ─ ─║─ ─ ─ ─ ─ ─ ─ ─
        ║ ╲#╱ ║      `─────' ┌ ╬ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ┐      ▼               │
│          ▔                │  ║    _                  │    _
   ════▶╚ ═ ═ ╝              │ ║   ╱ ╲      .─────.  │     ╱ ╲      .─────. │
│                           │  ╚═▶▕   ▏═══▶(|||||||)═══╬═▶▕   ▏═══▶(|||||||)
 ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │     ╲ ╱      `─────'  │     ╲ ╱      `─────' │
                                    ▔                  │    ▔
                             │Project B              │  Project C           │
                              ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─  └ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─

A pipeline DAG is not static and declared up front.

It is dynamic and organic. It grows and changes over time with only limited coordination between stakeholders.

Clusterless enabled developers and stakeholder to build and maintain complex pipelines, not because complexity is a goal but the result of multiple stakeholder requirements and expectations.

By leveraging project and dataset versioning, and support for multiple concurrent scoped (staging) environments, risks of complexity can be mitigated and managed.