airbyte server is frequently getting out of memory

Hmm, I don't know enough to give you a confident answer yet. However, here are some general steps you can take when troubleshooting issues with Airbyte: 1. Check the logs: The logs provide detailed information about what's happening behind the scenes, and they can help pinpoint the root cause of the problem. 2. Check the documentation: Airbyte's documentation covers a wide range of topics, including common issues and their solutions, troubleshooting tips, and best practices. You can find the documentation [here](https://docs.airbyte.com/). 3. Reach out to the community: Airbyte's community forum is a great place to ask for help, share your experiences, and learn from others who have faced similar issues. You can join the forum [here](https://github.com/airbytehq/airbyte/discussions). 4. Open a Github ticket: If you're still unable to resolve the issue after reaching out to the community, it's time to open a support ticket. You can do this [here](https://github.com/airbytehq/airbyte). If you're running Airbyte Open Source with Airbyte Enterprise or have an OSS support package, you can also get help with upgrading Airbyte versions, debugging connector issues, or troubleshooting schema changes. Before opening a support ticket, it's recommended to consult the documentation and search the [Help Center](https://support.airbyte.com/hc/en-us). If your question remains unanswered, you can submit a ticket through the Help Center [here](https://airbyte1416.zendesk.com/auth/v2/login/signin?return_to=https%3A%2F%2Fsupport.airbyte.com%2Fhc%2Fen-us&theme=hc&locale=en-us&brand_id=15365055240347&auth_origin=15365055240347%2Ctrue%2Ctrue). Remember, Airbyte is an open-source project with a vibrant community that fosters collaboration and mutual support. Don't hesitate to reach out if you need help!

@kapa.ai how to increase heap of airbyte server

To increase the memory allocation for Airbyte, you can set the

JOB_MAIN_CONTAINER_MEMORY_REQUEST

and

JOB_MAIN_CONTAINER_MEMORY_LIMIT

environment variables to custom values. This is particularly useful when dealing with large data sources, as the Source worker in a Sync job reads up to 10,000 records in memory. For example, a table with an average row size of 0.5MBs will require 0.5 * 10000 / 1000 = 5GBs of RAM. Java connectors, which all Source database connectors are, follow Java's default behaviour with container memory and will only use up to 1/4 of the host's allocated memory. So, if you're running a Docker agent with 8GBs of RAM configured, a Java connector limits itself to 2Gbs of RAM and will see Out-of-Memory exceptions if this goes higher. The same applies to Kubernetes pods. To avoid this, you may need to over-specify memory resource for Java connectors. For more information, you can refer to the [Airbyte documentation on scaling](https://docs.airbyte.com/operator-guides/scaling-airbyte/).