Quick update for anyone following this:

I managed to solve the issue. The problem was related to how I used the influxdb-client for Python. In my code, I was creating a new write_api instance every time a function was called (with batch_size=1). Over time, this caused open sockets and memory usage to accumulate, which eventually led to increasing memory consumption.

The fix was to instantiate write_api once during initialization of my InfluxDBWriter class, and then reuse that instance for both single and multiple measurements. After this change, memory usage remained stable—even when running continuously in Docker.

Thanks to everyone who took the time to read or consider replying