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Deployment Manager

The Deployment Manager is the control plane that turns a published workflow into concrete jobs running on workers.

Mental model: workflow → deployment → workloads

Think of Deployments as a compilation pipeline:

Published workflow version
→ deployment record (desired state + history)
→ per-worker job deployments (rendered artifacts)
→ workloads (what is actually running)

This is why the Deployment Manager is separate from the workflow editor: workflows describe intent; deployments produce concrete runnable artifacts.

The three verbs: plan, apply, reconcile

Plan

Planning is where the system compiles the workflow into deployable concrete artifacts:

  • expands blueprints and imported workflow modules,
  • resolves transports (and may insert required adapter jobs),
  • validates bindings (channels, imports, required parameters),
  • and produces a diff preview (“what will change, and where”).

Apply

Applying executes the plan:

  • stages the concrete jobs,
  • renders per-worker deployment artifacts,
  • deploys them to the selected worker group(s),
  • and records history so you can audit and roll back by deploying an older workflow version.

Reconcile

Reconcile converges “what is running” back toward “what you asked for”:

  • detects drift (workers out of sync, missing replicas, changed placement),
  • and re-applies the desired state when needed.

Managed artifacts (what to edit vs what to regenerate)

When you apply a deployment, the system generates managed job artifacts from your workflow. In general:

  • Change behavior by editing the workflow (or selected blueprints) and applying a new workflow version.
  • Avoid “hot-editing” the generated jobs directly; those changes will look like drift and can be overwritten by reconcile. If you need a bespoke job outside the deployment manager, clone it into an unmanaged copy and manage it through Pipelines.

Placement and scaling (worker groups + replicas)

Workflows are designed to run across worker groups:

  • Placement chooses where each step runs (which worker group).
  • Replicas control horizontal scale per step (and isolate noisy stages).

This lets you isolate heavy ingest from sensitive delivery, or scale routing independently from collection.

Common reasons planning fails

  • Missing producers/consumers: workflows must have a complete channel graph (every channel has a producer and a consumer).
  • Missing worker group / no workers available: planning requires at least one eligible worker.
  • Missing secrets/config required by a selected blueprint (credentials, endpoints, storage paths).
  • Incompatible artifacts: license or runtime feature requirements are not met (for example, external workers unavailable in Community Edition).

Next: follow Tutorial: Quickstart File Store Roundtrip for an end-to-end walkthrough.