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Release Readiness Guide

The release readiness analyzer evaluates milestones and deployments to highlight risks before you ship. It powers the release.refresh_readiness command palette entry, the analytics dashboard widgets, and notifications in the project sidebar.

Data Sources

  • Issues & milestones – Reads open work, blockers, and story points from the active milestone.
  • Deployments – Captures the latest production deployments (status, timestamp, environment).
  • Incidents & SLA events – Flags any unresolved incidents or SLA breaches for the release scope.
  • Changelog evaluations – If changelog drafts exist, their evaluation metrics are merged into the readiness report.

Running the Analyzer

  1. Navigate to a milestone and choose Refresh Readiness from the sidebar or the command palette (Cmd/Ctrl + K → release.refresh_readiness).
  2. The job runs asynchronously; progress appears in the activity panel.
  3. Once complete, the milestone shows readiness status (On Track, At Risk, Blocked) plus callouts for scope creep, test gaps, or dependency issues.

Configuration

  • Definition file: .kiket/analytics/release_readiness.yml 
    weights:
  blockers: 0.4
  overdue: 0.3
  incidents: 0.2
  test_coverage: 0.1
thresholds:
  caution: 0.6
  danger: 0.8
notifications:
  roles:
    - sre_lead
    - release_manager
  channels:
    - command_palette
    - email
  • Update weights to rebalance each signal.
  • thresholds decide when a release is flagged.
  • notifications controls who is pinged when readiness drops.

Surfacing Results

  • Analytics dashboards – Add the “Release Readiness” widget to any dashboard to visualize trends.
  • Command palette – release.refresh_readiness reruns the analyzer and surfaces the most recent summary inline.
  • CLI – kiket analytics readiness run <project_key> triggers the job from scripts.
  • API – Use /api/v1/projects/:project_id/release_readiness (see REST docs) to fetch the latest score for automations.

Best Practices

  • Refresh readiness at least once per day during a release window.
  • Pair readiness alerts with automation recipes (e.g., raise workflow approvals when a release is At Risk).
  • Track historical scores to learn which signals predict late releases in your organization.

With readiness data centralized, teams can ship confidently and catch blockers before they derail a launch.