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Deployments Overview

Deployments is the part of LyftData that turns workflows (graphs) into running systems across one or more workers.

If Jobs teaches you how to author a single job (one input → actions → one output), Deployments teaches you how to:

  • compose many jobs into a system,
  • choose how data moves between steps (transports),
  • decide where each step runs (placement),
  • and safely plan + apply changes with a clear diff (“no surprises”).

When to use Deployments

Use Deployments when you need any of the following:

  • A pipeline that is naturally multi-stage (ingest → route/transform → deliver).
  • Fan-out (send the same events to multiple consumers) or fan-in (combine multiple sources).
  • A durable hop between stages (spooling/landing before downstream processing).
  • Placement and scaling: run different parts of the pipeline on different worker groups and scale them independently.
  • A repeatable rollout flow with plan → apply → reconcile and an audit trail.

If you just need a single job running on one worker, you can stay in Jobs.

The Deployments lifecycle (high level)

  1. Pick a starting point from the Catalog (a workflow, perspective, or blueprint).
  2. If you chose a perspective, clone/start from it, complete bindings in Workflows, and publish a deployable workflow version.
  3. Click Plan & register to open the “create deployment” flow.
  4. Choose a name, a worker group, and fill in wizard fields when present.
  5. Plan: preview what will be created/updated and where it will run.
  6. Apply: stage and deploy the concrete jobs onto workers.
  7. Operate: watch health/status, and use reconcile to converge drift back to desired state.

Where this lives in the UI

  • Catalog: discover workflows, perspectives, blueprints, and library jobs (local or portal).
  • Workflows: author drafts and publish versions.
  • Deployment Manager: plan/apply/reconcile deployments.
  • Workloads / Workers: see what is actually running and where.

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