Produce (Records / S)

Attack

Produce records to a topic at a constant rate (records per second) for the attack duration

Targets:

Kafka Topics

Install now

Produce (Records / S)

Produce records to a topic at a constant rate (records per second) for the attack duration

Attack

Targets:

Kafka Topics

Install now

Produce (Records / S)

Attack

Produce records to a topic at a constant rate (records per second) for the attack duration

Targets:

Kafka Topics

Install now

Produce (Records / S)

Produce records to a topic at a constant rate (records per second) for the attack duration

Attack

Targets:

Kafka Topics

Install now

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The action "Produce (Records / s)" within the experiment editor.

Introduction

Produces records to a Kafka topic at a constant rate (records per second) for the entire attack duration. For example, 5 records/second over 60 seconds produces 300 records total.

For producing a fixed total number of records (distributed across the duration), use Produce (# of Records) instead.

Use Cases

Generate a steady stream of messages to simulate normal production load during fault injection.
Create sustained consumer lag by producing at a rate higher than the consumer can process.
Combine with Check Consumer Lag to verify that consumers keep up under a known production rate.

Parameters

Parameter	Description	Default
Duration	How long the producer runs at the specified rate. Total records produced = rate x duration.	10s
Records per seconds	The number of records to produce per second. Min: 1, Max: 10.
Record Key	Optional. The Kafka record key. Determines which partition receives the record based on the topic's partitioning strategy (default is round-robin when no key is set).
Record Value	Required. The message body to produce. Every record uses this same value.
Record Headers	Optional. Kafka record headers to attach to each produced record. Specified as key-value pairs.
Success Rate	Minimum percentage of records that must be produced without errors for the action to succeed. If the actual success rate drops below this threshold, the experiment fails.	100%
MaxConcurrent	Maximum number of parallel produce requests in flight at once. Min: 1, Max: 10.	5

Useful Templates

See all

Simulate Kafka brokers downtime and see how consumers are handling topic lag

An experiment to block access to brokers for consumers while producing records in the topic. The consumers should get back to consume when the kafka brokers are available again and the accumulated lag must be deal with quickly.

Message Queue

Kafka

Recoverability

Validate consumer's behavior when new leader is elected

Verify that your application handles a change of the leader properly.

Motivation

By testing your system's resilience to Kafka leader changes in a partition, you can identify potential weaknesses and take appropriate measures to improve its performance.

Structure

To conduct this experiment, we will ensure that all Kafka topics and producers are ready and that the consumer receives and processes messages correctly. We will then elect a new leader for one partition in Kafka and expect the system to work fine.

Message Queue

Kafka

Recoverability