Pre-Go-Live Readiness Assessment
Use Case
Author:
Fluent Commerce
Changed on:
31 Mar 2026
Problem
Potential Problems:- Unknown risks at go-live: Teams often don't have a clear, consolidated view of what's broken or misconfigured until something fails in production, by which point it's too late.
- Missing or misconfigured settings: Settings gaps are one of the most common causes of silent failures, and manually cross-referencing every rule parameter against deployed values is impractical at scale.
- Undetected workflow gaps: Orphaned rulesets, uncovered triggers, and missing workflow paths are easy to miss in review but can cause orders to get stuck the moment real traffic hits.
- No visibility into event health: Without monitoring event failure rates and unmatched events ahead of go-live, runaway loops or workflow blind spots only surface under production load.
- False confidence from static testing: A workflow can look correct on paper but behave differently at runtime. Without comparing expected paths against real order behaviour, gaps stay hidden until they cause incidents.
- Fragmented pre-launch checklists: Readiness checks are typically manual, inconsistent across team members, and lack the scoring or prioritisation needed to make clear go/no-go decisions.
Example
Pre-production readiness check before go-live.
Solution Overview
Together, these four steps replace scattered, subjective pre-launch reviews with a repeatable, evidence-based readiness process that makes the go/no-go decision straightforward.- Preparing for go-live starts with a broad, scored assessment of the entire implementation. Rather than relying on gut feel or a manual checklist, the tool analyses every layer of the system, including workflows, custom rules, settings, integrations, and entity relationships, and produces a structured report with health scores and risk ratings for each area. This gives the team a clear, prioritised picture of what needs attention before launch day, and what can be accepted as low risk.
- From there, the process drills into specific areas of concern. Settings are audited by cross-referencing what each workflow rule actually expects against what has been deployed, catching missing keys, incorrectly formatted values, and scope mismatches that could cause rules to behave unpredictably in production.
- Next, the health of the event system is checked by looking at real activity over the past day, measuring failure rates, identifying events that didn't match any workflow rule, spotting queues that are building up, and flagging any patterns that suggest a runaway loop. Any unmatched events are treated as critical findings, since they represent gaps in the workflow that real orders could fall into.
- Finally, the tool compares what the workflow was designed to do against what actually happened when real orders moved through the system. This side-by-side view surfaces rulesets that have never fired in production, unexpected events that shouldn't be occurring, and timing irregularities, giving the team confidence that the implementation behaves in practice the way it was designed to on paper.
