:_mod-docs-content-type: CONCEPT

// Module included in the following assemblies:
//
// assembly-storage.adoc

[id='considerations-for-data-storage-{context}']
= Storage considerations

[role="_abstract"]
Efficient data storage is essential for Strimzi to operate effectively. 
Strimzi has been tested with block storage as the primary storage type for Kafka brokers, and block storage is strongly recommended. 
File system-based storage (such as NFS) is not guaranteed to work for primary broker storage and may cause stability or performance issues. 

Common block storage types supported by Kubernetes include:

* Cloud-based block storage solutions:
** Amazon EBS (for AWS)
** Azure Disk Storage (for Microsoft Azure)
** Persistent Disk (for Google Cloud)
* Persistent storage (for bare metal deployments) using {K8sLocalPersistentVolumes}
* Storage Area Network (SAN) volumes accessed by protocols like Fibre Channel or iSCSI

NOTE: Strimzi does not require Kubernetes raw block volumes.

== File systems

Kafka uses a file system for storing messages.
Strimzi is compatible with the XFS and ext4 file systems, which are commonly used with Kafka.
Consider the underlying architecture and requirements of your deployment when choosing and setting up your file system.

For more information, see the link:{ApacheKafkaDocsBase}operations/hardware-and-os/#filesystem-selection[Apache Kafka filesystem selection documentation^].

== Tiered storage

Kafka’s tiered storage feature is supported in Strimzi as an optional capability. 

With tiered storage enabled:

* Primary broker storage,such as persistent volumes or JBOD, handles recent data
* Remote tiered storage, such as object storage, is used for historical data

Strimzi allows users to integrate their own tiered storage plugins to support specific remote storage backends.
If using a custom plugin, ensure that it meets performance and compatibility requirements before deploying to production.

== Disk usage
Solid-state drives (SSDs), though not essential, can improve the performance of Kafka in large clusters where data is sent to and received from multiple topics asynchronously.

NOTE: Replicated storage is not required, as Kafka provides built-in data replication.
