Hi, I'm Dennis Lattka, the Chief Storage Solutions Engineer at Micron Technology. My role is all about figuring out how to leverage flash storage to boost the performance and efficiency of workload applications. To explore this, I decided to evaluate Apache Kafka, one of the most widely used distributed messaging systems in the big data ecosystem. The goal was to understand how best to integrate Micron's solid-state storage into Kafka and what kind of performance improvements it could bring.
Introduction to Apache Kafka
During my evaluation, I closely monitored key system resources such as CPU, memory, disk activity, and network usage. I quickly identified that the main performance bottlenecks were disk I/O and network throughput.
Everything depends on throughput
One of the key takeaways from working with Apache Kafka was that throughput is everything. The Kafka team has done an excellent job of writing data directly to the kernel page cache, which minimizes I/O overhead. However, no matter how optimized the software is, eventually, the data will be written to disk in the form of continuous writes to Kafka partitions (log files). This means that the higher the disk throughput, the better the overall performance of Kafka.
After determining the best way to test Kafka and identifying the optimal parameters, I ran a simple test using its built-in generator script. Three generators sent a total of 600 million 100-byte messages to a single Kafka broker.
The test setup included:
- 600 topics generated in total.
- Each generator was assigned 200 unique topics.
- Each generator produced 1 million messages per topic.
- Each message was 100 bytes in size.
Hardware Configuration:
- Each server had one Kafka agent and three generators, all with the same configuration.
- Two Intel® Xeon® CPUs E5-2690 v3 @ 2.60GHz.
- 384GB of RAM.
- Two 10Gb NICs configured in ALB mode.
For comparison, we tested three different storage options: a 6TB 7.2k RPM HDD, a 1920GB Micron 5100 ECO SSD, and a 3.2TB Micron 9100 Pro NVMe SSD.
In each test, the Kafka agent partition was placed on the storage device being evaluated.
The results were clear:
As shown in the table above, the higher the disk throughput, the higher the IOPS (Input/Output Operations Per Second). This translates to more messages being processed per second by Kafka, measured in MB/s.
In conclusion
Using high-performance storage devices like the Micron 5100 Series SSD or the Micron 9100 Pro NVMe SSD in Apache Kafka configurations can significantly enhance Kafka's performance. These drives offer faster sequential write speeds and better I/O handling, which are crucial for high-throughput data pipelines. Whether you're running real-time analytics, log aggregation, or event streaming, optimizing your storage layer can make a huge difference in both speed and scalability.
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