Am working on a gae app using python. The app involves some crowd-sourced data collection system and data used in the app is submitted by users all-over the country. Now, am using the default quotas (Free) but am faced with a problem of ensuring at least 99% up-time for my app.
The challenge is that Google blocks any further requests being routed to your app once you exhaust your allocated quotas, and during a recent testing spree, one person was able to build an automated posting script that quickly exhausted the CPU quota - after that, the app would only serve HTTP 403 Forbidden status code for the request instead of calling a request handler. Now, I have patched the system not to allow automated postings, but how can I guarantee that human users don't cause a similar "blackout" at production time?
I know of the Quota API, but am thinking that can only give me profiling info for my app, I want a way of slowing down the rate of requests (e.g per minute for the per minute quotas) without serving error pages or blackouts.
Any suggestions?
One common solution of this problem is to delegate the tasks to a rate limited taskqueue.
For example:
queue:
- name: mail-throttle
rate: 2000/d
bucket_size: 10
- name: background-processing-throttle
rate: 5/s
In this way you can control the usage of all the parts of your application forcing them to stay in the range of the available quotas.
A couple of caveats:
1. Queues deliver a best effort FIFO order
2. Enqueuing/Execution of a task counts toward several quotas