# Durability in Kafka

## Durabilty in Kafka

Durability in Kafka is acheived by replication. Kafka by design makes sure the message is available to the consumers only after it's acknowledged to the topic successfully. 

The replication is defined using `replication_factor`

Here the message in topic is acknowledged based on `acks`. This defines if the message should be available to the consumers or not. 

### Types of \`acks\`

1. acks = 0
   * This is fire and forget. Once any of the Kafka node recieves the message, it is immediately considered as acknowledged and is available to consumers.
   * Even though replication factor is configured and will eventually be replicated but it does acknowledge the message immediately.
   * This is great fot high throughput but bad for durability
2. acks = 1
   * Broker acknowdges the message if the leader receives the message
   * Eventual replication will happen based on the `replication_factor`
   * Little bit of latency is introduced but the durability is much better than `acks = 0`
   * Durability is improved, but when leader re-election happens there is a chance of losing the data
3. acks = all
   * Broker acknowledges the message only when all in-sync replicas received the message
   * Provides you with highest durability but the throughput is affected
4. min.insync.replicas
   * Broker acknowledges the message when the `min.insync.replicas` receive the message rather than all in-sync replicas

{% hint style="info" %}
The above durability gurantees can be achieved in single availabilty zone (AZ). But Kafka supports disaster recorvery by having data in multiple availability zones. This is acheived using `rack_awareness`
{% endhint %}

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