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Kafka at Scale: Five Critical Challenges and How to Solve Them

Data quality, hidden costs, operational silos—five pitfalls that derail Kafka projects and how to avoid them.

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Kafka at Scale: Five Critical Challenges and How to Solve Them

Kafka powers everything from AI to real-time analytics. But without the right tools, teams hit the same walls again and again.

The Five Challenges

  1. Data Quality: Bad data breaks apps, analytics, and AI
  2. Developer Overhead: Too much friction between teams
  3. Operational Silos: Analytics and operations don't talk
  4. Hidden Costs: Infrastructure you forgot about
  5. Legacy Integration: Bridging old and new systems

What You'll Learn

Each challenge comes with real customer stories, clear diagnosis, and actionable solutions.

Who This Is For

Platform engineers scaling past 100 topics, data architects designing real-time platforms, and DevOps teams optimizing Kafka costs.

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