Mastering Kafka Producer Configs: A Guide to Optimizing Performance

Apr 2, 20240 likes314 views

"In this talk, we will dive into the world of Kafka producer configs and explore how to understand and optimize them for better performance. We will cover the different types of configs, their impact on performance, and how to tune them to achieve the best results. Whether you're new to Kafka or a seasoned pro, this session will provide valuable insights and practical tips for improving your Kafka producer performance. - Introduction to Kafka producer internal and workflow - Understanding the producer configs like linger.ms, batch.size, buffer.memory and their impact on performance - Learning about producer configs like max.block.ms, delivery.timeout.ms, request.timeout.ms and retries to make producer more resilient. - Discuss configs like enable.idempotence, max.in.flight.requests.per.connection and transaction related configs to achieve delivery guarantees. - Q&A session with attendees to address specific questions and concerns."

Mastering Kafka Producer Conﬁgs
A Guide to Optimizing Performance

Agenda
2
01
Introduction
An overview on Kafka Producer API
02
Configs walkthrough
Understanding different kafka producer configs
and test results
Best Practices
Learnings
03
01
03
02

Introduction
3
● Producers are one of the core components of the Kafka ecosystem, responsible for publishing data to
Kafka topics.
● Producer configurations are a set of properties that allow developers to customize the behavior of their
Kafka producers.
● Understanding producer configurations is important for optimizing performance, ensuring reliability, and
achieving specific use cases.
● Explore the most common Kafka producer configurations and how they can be used to fine-tune your
Kafka applications.

MyTopic-1
Producer
Apache Kafka Cluster
Follower Replica
Record
Accumulator
Metadata Cache
Leader Replica
Follower Replica
● batch.size
● linger.ms
● max.request.size

Performance Test Results
● With default configs: Throughput 66.83 MB/sec
● With batch.size=128000 and linger.ms=50 : Throughput 90.33 MB/sec

MyTopic-1
Producer
Send Buffer
Record
Accumulator
Metadata Cache
Apache Kafka Cluster
Follower Replica Follower Replica
Leader Replica
● buffer.memory
● max.block.ms

Performance Test Results
7
● With buffer.memory=100MB: Throughput 74.44 MB/sec

Producer
Record
Accumulator
Metadata Cache
Apache Kafka Cluster
Follower Replica Follower Replica
Leader Replica
MyTopic-1
Send Buffer
compression.type
[none,gzip,snappy,lz4,zstd]

9
● With compression.type=gzip: Throughput 28.24 MB/sec
● With compression.type=zstd and snappy: Throughput 56.25 and 83.93 MB/sec respectively
Performance Test Results

Producer
was it successful?
Record
Accumulator
Metadata Cache
Apache Kafka Cluster
Follower Replica Follower Replica
Leader Replica
Send Buffer
acks=[all,-1,0,1]

Performance Test Results
11
● With acks=1: Throughput= 91.84 MB/sec
● With acks=0: Throughput= 96.26 MB/sec

Best Practices
• Adjust batch.size upwards, but avoid setting it excessively high
• Determine the optimal value for linger.ms
• Choose the compression.type wisely
• Configure acknowledgments (acks) according to your specific needs
• Increase buffer.memory only when necessary

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Mastering Kafka Producer Configs: A Guide to Optimizing Performance

1. Mastering Kafka Producer Conﬁgs A Guide to Optimizing Performance

2. Agenda 2 01 Introduction An overview on Kafka Producer API 02 Configs walkthrough Understanding different kafka producer configs and test results Best Practices Learnings 03 01 03 02

3. Introduction 3 ● Producers are one of the core components of the Kafka ecosystem, responsible for publishing data to Kafka topics. ● Producer configurations are a set of properties that allow developers to customize the behavior of their Kafka producers. ● Understanding producer configurations is important for optimizing performance, ensuring reliability, and achieving specific use cases. ● Explore the most common Kafka producer configurations and how they can be used to fine-tune your Kafka applications.

4. MyTopic-1 Producer Apache Kafka Cluster Follower Replica Record Accumulator Metadata Cache Leader Replica Follower Replica ● batch.size ● linger.ms ● max.request.size

5. Performance Test Results ● With default configs: Throughput 66.83 MB/sec ● With batch.size=128000 and linger.ms=50 : Throughput 90.33 MB/sec

6. MyTopic-1 Producer Send Buffer Record Accumulator Metadata Cache Apache Kafka Cluster Follower Replica Follower Replica Leader Replica ● buffer.memory ● max.block.ms

7. Performance Test Results 7 ● With buffer.memory=100MB: Throughput 74.44 MB/sec

8. Producer Record Accumulator Metadata Cache Apache Kafka Cluster Follower Replica Follower Replica Leader Replica MyTopic-1 Send Buffer compression.type [none,gzip,snappy,lz4,zstd]

9. 9 ● With compression.type=gzip: Throughput 28.24 MB/sec ● With compression.type=zstd and snappy: Throughput 56.25 and 83.93 MB/sec respectively Performance Test Results

10. Producer was it successful? Record Accumulator Metadata Cache Apache Kafka Cluster Follower Replica Follower Replica Leader Replica Send Buffer acks=[all,-1,0,1]

11. Performance Test Results 11 ● With acks=1: Throughput= 91.84 MB/sec ● With acks=0: Throughput= 96.26 MB/sec

12. Best Practices • Adjust batch.size upwards, but avoid setting it excessively high • Determine the optimal value for linger.ms • Choose the compression.type wisely • Configure acknowledgments (acks) according to your specific needs • Increase buffer.memory only when necessary

13. Thank You

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