aiqbench analysis
This article details using an AI assistant to consolidate disparate VMware and Nutanix management APIs into a single Go binary, solving practical challenges of latency and data fragmentation in hybrid infrastructure environments. While the tool is built on general-purpose coding assistance rather than novel machine learning models, its primary value lies in automating complex IT operations within the AI/quantum hardware ecosystem by streamlining inventory for migration planning.
Three languages, one binary: Building a VMware Nutanix inventory with Claude
Two UIs, two CSV shapes, and a spreadsheet I kept rebuilding. Claude helped turn throwaway scripts into one Go binary that inventories VMware and Nutanix in a single run.
Someone asked me how many servers we run, and I couldn’t tell them. Not in 30 seconds, anyway. I had a vCenter tab, a Prism tab, two CSV exports in two different shapes, and a spreadsheet I’ve rebuilt more times than I’d like to admit. What I didn’t have was a VMware + Nutanix inventory I could export, hand to someone, and check against reality. I look after a sandbox data center on both stacks: VMware vCenter across seven clusters, Nutanix Prism Central across three, Cisco UCS and HyperFlex underneath. Both platforms have a perfectly good UI. Neither has the faintest idea the other exists. Four months later, one Go binary inventories 104 servers and 2,139 VMs across both platforms in a single run. Claude wrote a lot of it. Getting there took three languages, two throwaway versions, and three bugs that hid in plain sight for months. Even one platform’s answer was thin. The vCenter host export didn’t easily include the server model, so “what hardware are we running?” meant cross-referencing UCS Manager by hand. Once the…
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