When i am running docker stats command, i can see this stat: source-mssql-read-4152-0-rhsmk 9.06% 180.2MiB / 2GiB This mssql got 2GB of RAM, How Should i increase this to 10 GB ?

To increase the memory allocation for your

source-mssql-read

container from 2GB to 10GB, you need to adjust the

JOB_MAIN_CONTAINER_MEMORY_REQUEST

and

JOB_MAIN_CONTAINER_MEMORY_LIMIT

environment variables. This is because Airbyte's Java connectors, including the MSSQL source connector, follow Java's default behavior with container memory and will only use up to 1/4 of the host's allocated memory unless specified otherwise. Here are the steps to increase the memory allocation: 1. Locate your Airbyte configuration file: This is typically a

.env

file or a configuration file used by your Docker setup. 2. Set the environment variables: Add or update the following environment variables in your configuration file to set the memory request and limit to 10GB.

env     JOB_MAIN_CONTAINER_MEMORY_REQUEST=10G     JOB_MAIN_CONTAINER_MEMORY_LIMIT=10G

3. Restart your Airbyte services: After updating the configuration, restart your Airbyte services to apply the changes. Here is an example of what your

.env

file might look like after the update:

env # Other environment variables JOB_MAIN_CONTAINER_MEMORY_REQUEST=10G JOB_MAIN_CONTAINER_MEMORY_LIMIT=10G

By setting these environment variables, you ensure that the

source-mssql-read

container can utilize up to 10GB of RAM, which should help prevent out-of-memory exceptions and improve performance for large sync jobs. For more detailed information, you can refer to the [Scaling Airbyte documentation](https://docs.airbyte.com/operator-guides/scaling-airbyte#memory). If you encounter any issues or need further assistance, feel free to check the [Airbyte GitHub issues](https://github.com/airbytehq/airbyte/issues) or the [Airbyte discussions](https://github.com/airbytehq/airbyte/discussions) for additional support.

@kapa.ai I have already changed this configuration for

JOB_MAIN_CONTAINER_MEMORY_REQUEST

and

JOB_MAIN_CONTAINER_MEMORY_LIMIT

to 10G & Restarted But Still It is still not reflecting the change ?

It seems like you are experiencing an issue where changes to

JOB_MAIN_CONTAINER_MEMORY_REQUEST

and

JOB_MAIN_CONTAINER_MEMORY_LIMIT

are not being reflected even after restarting. This is a known issue that has been reported by other users as well. Here are some steps and considerations based on the information available: 1. Check Environment Variables: Ensure that the environment variables are correctly set. You can verify this by running:

bash    printenv JOB_MAIN_CONTAINER_MEMORY_REQUEST    printenv JOB_MAIN_CONTAINER_MEMORY_LIMIT

Make sure they output the expected values (e.g.,

10G

). 2. Restarting the Deployment: Sometimes, simply restarting the Airbyte instance might not be enough. Users have reported that performing a more thorough restart, such as using

helm uninstall

and then reinstalling, can help. This is particularly relevant if you are using Helm for deployment:

bash    helm uninstall airbyte    helm install airbyte airbyte/airbyte

3. Connection-Specific Requirements: If the instance-wide settings are not being respected, you can try setting the memory requirements at the connection level. This has been reported to work consistently: [Configuring Connection-Specific Requirements](https://docs.airbyte.com/operator-guides/configuring-connector-resources#configuring-connection-specific-requirements) 4. Known Issues and Workarounds: There have been reports of a regression where instance-wide resource requirements are not being respected. This issue affects

*-read

and

*-write

pods but not

*-check

pods. The workaround is to set the connection-specific requirements as mentioned above. 5. Documentation Reference: For more detailed information on configuring these settings, you can refer to the official documentation: [Configuring Airbyte](https://docs.airbyte.com/operator-guides/configuring-airbyte#jobs) If these steps do not resolve the issue, it might be worth checking if there are any updates or patches available for Airbyte that address this specific problem. If you need further assistance, you can also refer to the relevant GitHub issues where similar problems have been discussed: - [GitHub Issue #30814](https://github.com/airbytehq/airbyte/issues/30814) - [GitHub Issue #35749](https://github.com/airbytehq/airbyte/issues/35749) I hope this helps! If you have any more questions or need further clarification, feel free to ask.