Is this your first time deploying Airbyte: No OS Version / Instance: Amazon Linux 2 AMI x64 Deployment: Docker version 20.10.7 Airbyte Version: 0.35.31-alpha Source name/version: Twilio Destination: Azure SQL db Description: We have 2 twilio accounts that have separate calls each day. both are set as incremental updates. One we have running every 5 minutes, the other every 30 minutes. I can move this out, but the issue I'm seeing is, they both work just fine, but Airbyte consumes so much DataIO it's causing long waits on other queries, one thing that processes on this DB is an AAS tabular model, and when Airbyte is running it extends the model processing time from 20mins non-airbyte to over an hour and sometimes long enough to have to kill it. I've checked for locking, and there isn't any exclusive locks, just alot of consumer waits, or buffer waits. In monitoring the SQL performance metrics, the DataIO is consistently pegged at 60% when airbyte is on. Is there anything you can think of to reduce the load airbye takes, or a way to maybe speed up airbyte? If not, is there a way to schedule Airbyte at specific time slots, vs intervals?

You can edit the normalization files to become more perfomatic for your use case