profiling api with django, gunicorn and threadpool

Question

I have an API to do the below operations. I am using python, Django framework and gunicorn/nginx for deployment.

API has deployed in AWS lightsail. Request will come in for every 2secs.

1. receives data from the client.

2. creates record in local SQLite database and sends response.

3. runs task asynchronously in thread. (running in thread). Entire task takes about 1 sec on average.

   a. gets the updated record from step 2 with ID. (0 sec)

   b. posts data to another API using requests. (.5 secs)

   c. updates to database (AWS RDS) (.5 secs)

Setup:

1. I have ThreadPoolExecutor max_workers=12.
2. gunicorn has one worker as the instance has 1vCPU. I don't use gunicorn workers with threads, since I have to perform some other task within the api.
3. The reason asyncio is not used was that base update to db in Django is not supported with this. So I kept the post API in the threading itself.
4. Each request will be unique. No same request.

Even If I keep max_worker to 1 in threadpool, it is bursting 10% mark in AWS 5$ instance. API only receive request for every 2secs.

I am not able to profile this situation where it is causing the CPU usage.

There are a couple of reason, I can think of.

1. gunicorn master is constantly checking on the worker.
2. OS is managing threads for context switching.

Any pointer will be helpful for profiling.