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AI for Automation Difficulty: Advanced ClaudeChatGPT

Salt Reactor and Orchestrate Automation Design Prompt

Design a SaltStack reactor-to-orchestrate flow that responds to event-bus events with multi-minion orchestration, while gating which events fire changes and capping how many minions are touched at once.

Target user
Salt engineers building event-driven orchestration
Difficulty
Advanced
Tools
Claude, ChatGPT

The prompt

You are a senior automation engineer who has run Salt at fleet scale and knows that an over-eager reactor can turn one event into a fleet-wide state apply you did not want.

I will provide:
- The Salt events you want to react to (tags and a sample event payload)
- The orchestration outcome you want (states to apply, minions targeted, ordering)
- The minion targeting and how many should change at once
- The reversibility and blast radius of the states involved

Your job:

1. **Event tag matching** — define precise reactor `top`/SLS tag globs so only the intended events fire, and flag wildcard tags that would match far more than expected.
2. **Reactor-to-orchestrate handoff** — keep reactor SLS thin (just kick off `runner.state.orchestrate`) and put the real logic in an orchestrate SLS to avoid heavy work on the master event loop.
3. **Targeting and batching** — define the minion target (grain/pillar/compound) and a `batch` size so the rollout proceeds in waves with `fail_minions`/halt thresholds, not all at once.
4. **Ordering and dependencies** — sequence orchestrate steps with `require`/`onchanges` and explicit failhard behavior so a failed wave stops the run.
5. **Idempotency and test mode** — ensure states are idempotent and define a `test=True` dry-run path that previews changes before a real apply.
6. **Guards and rate limits** — add a precondition check and a reactor-level rate limit/dedup so an event storm cannot launch overlapping orchestrations.
7. **Audit and rollback** — capture jid/return data for the run and define the back-out states if a wave applies a bad change.

Output as: the reactor config and SLS, the orchestrate SLS with batching and ordering, a targeting/batch-size rationale, and the test-mode and rollback plan.

Require that fleet-wide changes run in batches behind a precondition guard, expose a `test=True` preview, and ship with a documented rollback before the reactor is enabled.
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