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Verify System Unavailability Status During Kafka Downtime

An unavailable Kafka broker or even entire cluster should be handled by your application gracefully and being indicated appropriately. Specifically, we want to ensure that at least one monitor in Datadog is alerting us to the outage.
Targets:

Containers

Datadog monitors

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Verify System Unavailability Status During Kafka Downtime

An unavailable Kafka broker or even entire cluster should be handled by your application gracefully and being indicated appropriately. Specifically, we want to ensure that at least one monitor in Datadog is alerting us to the outage.
Targets:

Containers

Datadog monitors

Download now

Verify System Unavailability Status During Kafka Downtime

An unavailable Kafka broker or even entire cluster should be handled by your application gracefully and being indicated appropriately. Specifically, we want to ensure that at least one monitor in Datadog is alerting us to the outage.
Targets:

Containers

Datadog monitors

Download now

Verify System Unavailability Status During Kafka Downtime

An unavailable Kafka broker or even entire cluster should be handled by your application gracefully and being indicated appropriately. Specifically, we want to ensure that at least one monitor in Datadog is alerting us to the outage.
Targets:

Containers

Datadog monitors

Download now
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The experiment editor showing the visual structure of the experiment.The experiment editor showing the visual structure of the experiment.

Intent

An unavailable Kafka broker or even entire cluster should be handled by your application gracefully and being indicated appropriately. Specifically, we want to ensure that at least one monitor in Datadog is alerting us to the outage.

Motivation

Kafka unavailability can occur due to various reasons, such as hardware failure, network connectivity issues, or even intentional attacks. Such unavailability can have severe consequences for your application, such as lost messages, data inconsistencies, and degraded performance. By testing the resilience of your system to Kafka unavailability, you can identify areas for improvement and implement measures to minimize the impact of such outages on your system.

Structure

To conduct this experiment, we will ensure that all Kafka topics and producers are ready, and the consumer is receiving and processing messages correctly. We will then simulate an unavailable Kafka cluster by shutting down one or more Kafka brokers or the entire Kafka cluster. During the outage, we will monitor the system to ensure that it continues to deliver its intended functionality and maintain its throughput. We will also verify that the system can handle the failure of a Kafka broker or a complete Kafka cluster outage without losing messages or data inconsistencies. Once the Kafka cluster becomes available again, we will verify that the system automatically recovers and resumes its normal operation. We will also analyze the monitoring data to identify any potential weaknesses in the system and take appropriate measures to address them. By conducting this experiment, we can identify any weaknesses in our system's resilience to Kafka unavailability and take appropriate measures to minimize their impact.


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.yaml (3 kB)

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    Download .yaml file
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  3. 3.

    Start your experiment!
Screenshot showing the Steadybit UI elements to import the experiment.yaml file into the Steadybit platform.
Tags
Kafka
recoverability

Used Actions

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Blackhole

Drops network traffic (incoming and outgoing).

Attack

Attack

Containers

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