Gate a production release on policy and a human approval

The challenge

Release rules such as passing tests, a clean secret scan, an SBOM and sign-off for production are written down but enforced inconsistently, and proof is scattered across tools.

The scenario

An engineering team deploys to production from a release branch. Their policy requires tests, secret scanning, dependency analysis and an SBOM on every release, and a named approval for production.

What goes in

Stage requirements

The checks each stage must pass and which environments need an approval.

Check results

The real outcome of each check, reported by the pipeline.

What you can ask

Illustrative prompts. Results depend on your own data and are not deterministic.

• “Can this release deploy to production?”Copy
• “Which approvals are blocking today's deploys?”Copy

How Clearception approaches it

How the work is structured. Each step shows what its output is grounded in.

1. 1

   The pipeline reports

   Source

   The gate step sends the stage, branch, environment and each check's outcome.

2. 2

   Requirements are checked

   Observed

   A required check that failed or was not reported blocks the stage.

3. 3

   A person approves

   Human-verified

   Production waits for an approver other than the requester; the approval is bound to this deploy only.

4. 4

   The gate re-runs

   Observed

   With the approval reference the stage is allowed, and the decision joins the evidence chain.

What you get

The shape of what comes back — not a promised result.

• Gate result

  Observed

  Pass or fail, with each missing or failed requirement listed.

• Release evidence

  Source

  The checks, the approver and the policy version behind each production deploy.

Why it matters

One rule set for every pipeline

GitHub Actions and Azure Pipelines ask the same policy, so releases are governed the same way.

Audit-ready releases

The proof that a deploy met policy is recorded when it happens, not reconstructed later.