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<@U04SE163WC8> what is the airbyte-server pod doin...
# replication-ask-ai
r
@kapa.ai what is the airbyte-server pod doing?
k
The 
airbyte-server
pod in Airbyte is a crucial component that handles the API part of the system. It receives API requests and coordinates the actions to the component responsible for executing them. This server acts as the main control plane for Airbyte, managing operations such as creating sources, destinations, connections, and managing configurations. However, it's important to note that the handlers for these operations are located in 
airbyte-common-server
. For a more detailed understanding of the 
airbyte-server
and other components of Airbyte, you can refer to the [Airbyte Architecture Overview](https://docs.airbyte.com/understanding-airbyte/high-level-view). Sources: - [Github Discussion](https://github.com/airbytehq/airbyte/discussions/33811) - [Airbyte Documentation](https://docs.airbyte.com/understanding-airbyte/high-level-view)
r
@kapa.ai when is run sync jobs the airbyte-server uses more memory. But when the sync job is completed the memory does not decrease. Why?
k
A message from kapa.ai
The issue you're experiencing with Airbyte, where the 
airbyte-server
uses more memory during sync jobs and the memory does not decrease after the job is completed, is a known issue. It has been reported by several users and is currently being investigated by the Airbyte team. The root cause of the issue is not yet clear, but it seems that the Airbyte server and worker gradually increase their memory usage over time, which can lead to out-of-memory errors and cause the server to crash or restart. Some users have found a temporary workaround by manually triggering the Java Garbage Collector (GC) in the worker container. However, this is not a permanent solution and it may cause issues with the sync jobs. Another user suggested updating the default JAVA_OPTS for both the worker and server to manage non-heap memory consumption in Java. Please note that these are all workarounds and the root cause of the issue is still being investigated. We recommend following the Github issues linked above for updates on this issue. Sources: - [Github Issue 16652](https://github.com/airbytehq/airbyte/issues/16652) - [Github Discussion 34483](https://github.com/airbytehq/airbyte/discussions/34483)
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