Introduction
A large retail client has used ignio, the AIOps platform from TCS subsidiary Digitate, for two years. ignio auto-resolved about 38% of eligible IT incidents, such as restarting hung services, clearing disk space and re-running failed batch jobs. Over the last quarter the client moved a large share of its workloads, including its e-commerce platform and parts of its supply chain systems, from on-premise data centres to a public cloud. Since then, ignio's auto-resolved incident share has fallen to 24%. The client's head of IT operations is questioning the renewal. I'll find the root cause using a structured approach, distinguishing between a product gap, a configuration gap and a change in the incident mix.
When a ratio metric falls, always check both numerator and denominator. Here, auto-resolved incidents could fall, or total incidents could rise with a different mix. Many candidates jump to "ignio broke" without checking the denominator.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Definitions often change during migrations. Expected answer: Incidents closed by ignio without human action ÷ all incidents eligible for automation in the ITSM tool. Impact on approach: We need to check whether eligibility rules changed.
Why it matters: It tells us how much of the estate ignio may no longer "see" properly. Expected answer: About 45% of applications, including e-commerce and warehouse management, moved to managed Kubernetes and cloud databases. Impact on approach: Focus on these applications first.
Why it matters: Steps aligned with migration waves would point to coverage gaps. Expected answer: Three step drops matching three migration waves. Impact on approach: Strong signal that migration is linked.
Why it matters: Rules out product regressions. Expected answer: A minor ignio update was applied, but no automation logic changed. Impact on approach: Lower priority hypothesis.
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