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What Running Kafka on VMs Taught Us About Systems Thinking

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Most infrastructure stories get written after something breaks. This one is different. Nobody paged Celestina Amadi's team at 3 AM about Kafka. The VMs were working, yet she made the call to rebuild anyway because she could see where things were headed before they became a problem.

Celestina Amadi leads the Cloud Engineering team behind the infrastructure that powers Moniepoint's payment and savings products, building systems that move transaction and savings data reliably for millions of customers every day. She's also a Grafana Champion, a HashiCorp Ambassador, and an IBM Champion 2026.

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Why We Moved to Strimzi

It Wasn't a Crisis. It Was a Decision.

We moved to Strimzi because we looked honestly at how we were running Kafka and made a deliberate call: this does not scale, and we can do better.

That kind of decision is actually harder than reacting to a crisis. Incidents are obvious — something breaks, and you fix it. Proactive architectural change requires you to see clearly enough to act on discomfort before it becomes a disaster. It requires you to say "this is working, but not well enough" and mean it.

This is the story of what we saw, what we built, and what it taught us about thinking in systems.

How We Were Running Kafka Before

Our Kafka setup started the way most things do in a fast-moving engineering team: pragmatically.

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