Great Stack to Doesn't Work #2 — Kafka: "Where Did My Messages Go?"
The article discusses common issues faced by engineers using Kafka, particularly regarding message visibility and consumer lag. It emphasizes the importance of monitoring lag per partition to avoid stale data and highlights the problem of rebalance storms that can disrupt processing. Solutions such as dead letter queues and adjusting timeout settings are suggested to mitigate these challenges.
- ▪Kafka does not lose messages but can hide them due to configuration issues.
- ▪Consumer lag should be monitored per partition to identify stuck consumers or problematic messages.
- ▪Rebalance storms can occur when Kafka mistakenly declares a consumer dead, leading to repeated disruptions in processing.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 2891163) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Mehmet TURAÇ Posted on May 30 Great Stack to Doesn't Work #2 — Kafka: "Where Did My Messages Go?" #kafka #backend #devops #discuss Great Stack to Doesn't Work (4 Part Series) 1 Great Stack to Doesn't Work #1 — PostgreSQL: "I Added an Index and It Got Slower" 2 Great Stack to Doesn't Work #2 — Kafka: "Where Did My Messages Go?" 3 Great Stack to Doesn't Work Bonus: SQL vs NoSQL: Which One in 2026? 4 Great Stack to Doesn't Work #3 — Redis: "99% Cache Hit Ratio, System Down" A survival…
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