I had a similar setup at one point, although in python. At some point I wrote a python logger talking to stackdriver http api, although I don't use it now: https://github.com/understandwork/stackdriver_python_logger .

This setup is not optimal. If you use kubernetes/gke the most optimal choice is relying on GKE logging. You just log to stdout, and GKE takes care of attaching relevant metadata (e.g. instance log came from) and transporting logs reliably and efficiently (relies on fluentd agent provided by the GKE). You don't need to do any setup, except logging to stdout in json format. In my python code I just use python-json-logger.

If you don't want to rely on GKE, instead of sending http calls with logs fluentd is a better choice:

  - open source logs collector you control, lives on your machines.
  - You can export fluentd logs to google cloud stack driver.
  - There are already well maintained client logging libraries talking to fluentd
  - Better efficiency and reliability than http calls 
  - No lock-in to any logging platform. E.g. move from StackDriver to competition by fluentd config change.
  - Handles more than just application logs - e.g. your nginx/apache logs

Regarding stack driver - article does not mention that you can export logs from StackDriver to BigQuery. I find it very useful. BigQuery internal version, Dremel, was created for that very purpose - logs analysis.

Disclaimer: I'm not affiliated with fluentd or GCP, although I use both and I used to work at Google (primarily search, no ties to GCP).