Kafka Producer Acknowledgments in Spring Boot Microservice

When you send out messages in Kafka, it’s essential to know they’ve been received and saved properly. That’s where two important settings come in: spring.kafka.producer.acks and min.insync.replicas. These settings help ensure that your messages are safely stored and acknowledged by the Kafka brokers.

In this tutorial, I’ll explain what these settings are, how to configure them, and why they’re important for any Kafka producer, especially in a Spring Boot application. This way, you can be confident that your data won’t be lost in transit.

Let’s get started!

If you are interested in video lessons then check my video course Apache Kafka for Event-Driven Spring Boot Microservices.

Understanding Kafka Producer Acknowledgments

Kafka Producer Acknowledgments are a way of ensuring that your messages are not only sent but also received and stored by Kafka brokers. This is important for data integrity and reliability in your Kafka ecosystem.

In this section, you will learn how to configure the spring.kafka.producer.acks property in your Spring Boot application to control the level of acknowledgment you want from Kafka.

The key property involved is spring.kafka.producer.acks. You will set this in the application.properties file of your Spring Boot application. Depending on the value you choose, Kafka changes the way it acknowledges message receipts, which directly affects the durability and reliability of your message delivery.

Here’s how it works:

  • If you set acks to 0, Kafka sends the message without waiting for any confirmation. It’s fast, but you won’t know if the message actually gets stored.
  • When you set acks to 1, Kafka waits for a confirmation from the leader broker only. It’s a middle ground, offering a moderate level of assurance.
  • The most secure setting is acks=all. This means you’re asking Kafka to confirm that all in-sync replicas have received the message before considering it a success.

Your choice here depends on how critical it is for every message to be reliably stored. Up next, I’ll show you how this setting works together with min.insync.replicas to protect your data.

The role of min.insync.replicas

min.insync.replicas determines the minimum number of replica servers that must have a copy of the data before a write operation can be considered successful. When you set spring.kafka.producer.acks to all, min.insync.replicas comes into play.

You’ll typically configure min.insync.replicas at the broker or topic level. For instance, if you have a replication factor of three, you might set min.insync.replicas to two. This means at least two broker replicas must confirm that they have received the message, providing a buffer in case one broker fails.

To learn how to configure the min.insync.replicas, follow this tutorial: Kafka’s min.insync.replicas: Avoiding Data Loss.

By carefully choosing the value for min.insync.replicas, you ensure data is not just written to Kafka, but is robustly stored across multiple servers. T

In the next section, we’ll see how to configurespring.kafka.producer.acks to make your Kafka message delivery as reliable as possible.

Configuring spring.kafka.producer.acks property

Now let’s focus on how you can configure spring.kafka.producer.acks in your Spring Boot application. This step is crucial for controlling how Kafka handles your message acknowledgments.

First, locate the application.properties file in your Spring Boot project. This is where you’ll set your Kafka producer properties.

Add or modify this line:


By setting acks to all, you’re instructing Kafka to wait for acknowledgments from all in-sync replicas before considering a message as successfully sent. This setting provides the strongest guarantee of data durability, as it ensures that your message is not just sent, but also replicated across the Kafka cluster.

Remember, while this setting offers the highest data safety, it can impact the throughput and performance of your application. So, choose the value that best balances your needs for reliability and performance. Next, you will see how this setting interacts with min.insync.replicas to ensure data integrity.

Try how it works

And this is it! Now that you have configured min.insync.replicas and spring.kafka.producer.acks, you’ve set the stage for a highly reliable Kafka environment. These settings ensure that your messages are not only sent but are also acknowledged by the necessary number of Kafka replicas for robust data integrity.

Now, you’re ready to run your Kafka Producer and see these configurations in action. If you need help to create and configure a Kafka Producer, then read this detailed tutorial: Kafka Producer in Spring Boot Microservice. It’s a great next step to put what you’ve learned here into practice.

To find more tutorials, check Kafka tutorials for beginners page.

If you are interested in video lessons then check my video course Apache Kafka for Event-Driven Spring Boot Microservices.

Happy coding!