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With Halloween just a few days away and temperatures dropping (in most parts of the world!), it’s safe to say that we’re right in the middle of “spooky season.” And while ghosts and ghouls may bring delight to those who enjoy a scary movie or two, there’s one nightmarish creature that we know strikes real fear into the hearts of those who are unwittingly trapped in its mandibles of misfortune: the Apache Kafka® Bug.
It strikes when you least expect it, and it can take many forms. Whether it’s reduced message throughput, increased request response time, surplus connections bogging down brokers, consumer rebalancing woes, or any other unexpected Kafka performance anomaly, one thing’s certain: you’ll know it when it emerges from the shadows.
But thankfully, according to our trusty Compendium of Open Source Creatures, the Kafka Bug has several weaknesses that its would-be victims can exploit. And with the right bug-slaying strategy, you’ll send this unsavory insect skittering back to the crypts in time to enjoy the rest of spooky season without worrying about what’s lurking in your Kafka clusters.
Ready to start squashing? Check out these six popular resources below for the best tips on how to debug a variety of common Kafka issues. We promise these tricks will feel more like treats!
1. Diagnose and Debug Apache Kafka Issues (blog series) In this four-part blog series, you’ll level up your Kafka debugging game and gain a better understanding of common problems that can arise in your environment. You’ll learn how to properly diagnose the issues causing you grief so you can find a cure instead of treating individual symptoms. In the series, you’ll learn how to address:
2. Unknown Magic Byte! How to Address Magic Byte Errors in Apache Kafka (blog post)
Ever come across this error while working with Kafka Streams or Schema Registry?
Caused by: org.apache.kafka.common.errors.SerializationException: Unknown magic byte!
This blog post covers how to address the “unknown magic byte” error and includes a tutorial on the core concepts of magic bytes so you’ll never feel spellbound by these file signatures again.
3. Debugging of a Stream-Table Join: Failing to Cross the Streams (blog post and recorded talk) This blog post and corresponding Kafka Summit talk discuss the challenges that can arise when joining two Apache Kafka topics. You’ll learn:
How to debug co-partitioning with kcat (formerly kafkacat)
How to avoid the number one pitfall of using kcat
What stream-table join semantics look like in action
4. Key Metrics to Uncover the Root Cause of Kafka Performance Anomalies (recorded talk)
In this recorded talk, you’ll get a walkthrough on how to diagnose common Kafka performance anomalies by identifying patterns in the metrics for various components. You’ll also see a demonstration of how to set up an open source observability pipeline to collect and process Kafka metrics at scale.
5. What’s Slowing Down Your Kafka Pipeline (recorded demo) In this recorded demo, you’ll discover an eBPF-based (Extended Berkeley Packet Filter) always-on CPU profiler for visualizing what your Kafka applications are spending time on. You’ll learn how to detect issues in your Kafka pipeline and remove performance bottlenecks instantly.
6. The Importance of Standardized Hashing Across Producers (blog post) When developing streaming applications, the default partitioning behavior of Java and non-Java producers often goes unnoticed. This can result in data mismatches and inconsistencies, which means headaches for developers! Dive into this blog post to learn what causes these challenges, and explore options for overcoming them so you can restore unity to your data.
Looking to learn more about the latest developments, tips, and trends in the world of Apache Kafka and data streaming? Check out the recorded sessions from Current 2023 | The Next Generation of Kafka Summit, and hear from subject matter experts across a variety of industries. Happy learning!
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