There’s a specific kind of exhaustion that comes from running Apache Kafka in production for long enough. It’s not about outages. Those you can deal with. It’s about the slow accumulation of operational rituals that start to define your engineering life. The constant JVM tuning, watching GC pauses creep in at the worst possible time, monitoring controller elections like a weather forecast, waking up to rebalances that feel like they’ve been going on since the Roman Empire. Kafka works, but it rarely feels effortless.
For years, we lived in that reality. Our event-driven platform was stable, respected, and battle-tested. But it was also heavy. Maintaining it required an almost emotional relationship with the cluster. You learned to sense when a broker was “not feeling well.” You built instincts for how long a restart would take. You knew the exact type of lag graph that meant: everyone cancel your plans.
And then Redpanda appeared in our orbit — a Kafka-compatible engine without ZooKeeper or JVM. A drop-in replacement that promised the same API but fewer moving parts. We didn’t believe the marketing. No one should. Instead, we deployed a small shadow cluster and tried very hard to break it.
That’s when our migration began, long before we admitted it.
The first thing we noticed was the silence. No GC logs screaming at us. No brokers freezing during a load spike. No ancient tuning notes written by engineers who left the company years ago. Redpanda didn’t feel alive the way Kafka does. It felt engineered. You start it, it runs, and you return to doing your actual job instead of feeding the cluster like a temperamental animal.
The emotional part of migration hit next. Kafka is familiar. You know its failure modes, even the ugly ones. Switching to something that claims to be simpler feels reckless, like trading a well-understood tank for a lightweight electric bike and hoping it holds up in battle. Every team has at least one engineer who says: “What if this thing dies in six months and Kafka would’ve survived?”
We asked that question too.
So we produced events to both systems in parallel. We consumed from both. We compared lag curves, tail latencies, and recoveries from forced failures. One of the earliest shocks came from broker restarts. Kafka restarts were measured in minutes—even on good days—mostly because JVM and state restoration took their time. Redpanda restarted in under a second. At first, it felt like a bug. Someone on the team actually said: “Is it allowed to be this fast?”
The real turning point came during a production traffic spike — the kind you never plan for, the kind that turns your graphs into cliff shapes. Kafka took the hit as expected, but its lag expanded wildly. Redpanda, running shadow traffic at the same volume, absorbed the spike without drama. When the load dropped, Redpanda drained its backlog far faster. It didn’t just survive. It recovered with elegance.
That’s when the internal debate shifted from “Is Redpanda safe?” to “Why are we still paying the Kafka tax?”
But migrations are never perfect. Some older internal clients depended on ancient Kafka protocol versions. A few of our monitoring dashboards simply didn’t map to Redpanda’s metrics. Some tooling had assumptions baked in that no longer applied. And there was always that lingering fear that we were giving up Kafka’s enormous ecosystem for something much more streamlined.
Yet every obstacle led back to the same question: were we engineers, or were we reluctant caregivers of a distributed system that demanded constant emotional support?
Kafka is powerful. But the cost of running it grows with the size of your team, traffic, and impatience for JVM-based surprises. Redpanda, by contrast, removed entire layers of operational work. No JVM. No ZooKeeper. No rebalances that take half an afternoon. No GC pauses randomly dictating your on-call schedule.
The cutover itself was anticlimactic in a way we didn’t expect. No fanfare. No urgent rollback discussions. One week Kafka was handling everything. The next week Redpanda was. The cluster behaved like it had been there all along. In infrastructure, “boring” is the highest compliment imaginable.
Months later, we noticed the real payoff. On-call rotations got quieter. Engineers finally focused on product work instead of infrastructure therapy sessions. Maintenance became a daytime activity instead of something you planned a weekend around. The team didn’t get smarter — the system simply stopped fighting us.
So what actually happened during our Kafka to Redpanda migration? Nothing dramatic. And that’s the point. Migration gave us back something Kafka had slowly consumed over the years: mental space. Room to build. Time to think. A foundation we didn’t have to babysit.
If you’re considering the same move, ignore the marketing slides and synthetic benchmarks. Run both systems side by side. Stress them. Break them. Watch how they behave when the world is burning around them. The truth reveals itself quickly.
That’s our story. And it changed everything for us.
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