"Matthew Liu, an architect in Michelin's China IT operations team, describes how their implementation began with personal conviction rather than an executive mandate. Monitoring, telemetry, incident management, and mature cloud hosting were already in place; yet, the volume of incidents and manual checks continued to rise despite process optimisation efforts. This discrepency meant that motivation for change was straightforward - the time was "now"."
"Their approach used Dify, a low-code platform for building AI applications, deployed on AliCloud and integrated with other tools using Anthropic's Model Context Protocol. Liu built working demonstrations before seeking formal approval. One chatbot he built helped database administrators with health checks and slow query analysis. Another helped Kubernetes administrators with routine tasks. These prototypes used MCP servers to query ServiceNow tickets directly from within Dify agents."
Michelin's China IT operations initiated an AIOps implementation driven by practitioner conviction rather than an executive mandate. Existing monitoring, telemetry, incident management, and mature cloud hosting did not stop incident volume and manual checks from rising. The team used Dify, a low-code AI platform, on AliCloud and integrated tools through Anthropic's Model Context Protocol. Working prototypes included chatbots for database health checks, slow query analysis, and Kubernetes routine tasks. Prototypes were built and demonstrated before formal approval. Early demonstrations gained interest but revealed organisational reluctance to share metrics due to fears of headcount reduction and premature performance targets.
Read at InfoQ
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