Cloud management software
Quality and reliability work inside a live cloud management product
A software quality and testing strategy for an existing web application portal, the kind of groundwork that makes later AI work safe.
Proof at a glance
- Delivery freeze required
- None. Coverage added alongside feature work
- Scope
- Critical paths across a multi-year codebase
- Effect
- Regression coverage that makes AI-assisted change safe
- Engagement length
- 2023 to present
01 · Existing product
A file and cloud management product, desktop application and web portal, already in use by customers across multiple cloud services.
02 · Problem
Critical paths built up over years had uneven coverage, so every change carried risk in a product customers depended on.
03 · Constraints
Changes had to improve reliability without disrupting an application customers depended on.
04 · Why it was hard
Critical paths were spread across an application built over years, so coverage had to be earned rather than assumed.
05 · AI capability added
A structured quality assurance and testing strategy covering the portal's critical paths.
06 · How we shipped it
Introduced alongside ongoing product work, with no freeze on delivery.
07 · Datics role
Quality engineering: test strategy, automated regression coverage on critical paths and release confidence, delivered without pausing the roadmap.
08 · Outcome
A more predictable product and a codebase that can absorb change with less risk.
09 · What came next
Reliable regression coverage is what makes later agent-driven behaviour safe to ship.
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