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Plan a zero-downtime deployment

Turn a service topology into staged rollout, health, rollback, and stop conditions.

Revision
1
Verified
2026-07-26
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Compatibility and paths

GenericWorks with instruction-following chat models.
ChatGPT
Claude Code
Gemini CLI

Trust and provenance

Curated record reviewed 2026-07-26. Results still depend on the supplied context and target environment.

Fill variables

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Generated asset2 required field(s) must be completed
Objective: Produce a verifiable canary or rolling deployment plan.

Context: Every mutation needs a preceding observation and rollback trigger.

Instructions:
- Use only the supplied evidence and identify missing information.
- Lead with the finding, confidence, and one safe next action.
- Put read-only checks before mutations and include a stop condition.
- Never request or reproduce secrets, credentials, or private keys.

User request:
Service topology:
{{environment}}

Change and constraints:
{{evidence}}

Create the deployment plan.

Required output:
- Finding
- Evidence
- Confidence
- Safe next check
- Stop condition

Real example

Input

3 stateless API replicas behind NGINX; database migration is backward-compatible; SLO 99.95%

Expected result

Sequence: preflight health → one-replica canary → synthetic and error-rate gate → remaining replicas one at a time → post-check. Roll back application on error-rate breach; migration remains compatible.

Source evidence

NGINX documentationofficial