Stripe - API Request rate limit exceeded - Firebase Cloud Functions - google-cloud-platform

Question

Let's say I'm creating a PWA (Progressive Web App) where products can be added by users.
Prices of these products are variable from 0,01 EUR to 1,00 EUR.
I'm using Stripe for payments.
The Stripe Order object do not support dynamic price, passed on the fly, without any reference (kind of foreign key).
To accept the Order, Stripe needs a reference to a SKU.
This SKU will be, in my case, a variation of the price, on the product.
It means that, to cover all variations, I need 100 SKUs, from 1 (0.01 EUR) to 100 (1,00 EUR).
So, for each product created in Stripe, I need to create 100 SKUs in Stripe.
I tried to insert a test dataset of 200 products, which means (200 products + (200 x 100 SKUs)) = 20200 requests.
I got a surprising "Request rate limit exceeded" error from Stripe.
Less than half of records where created... :(
That "Request rate limit exceeded" is the core of the problem.
Right now, the insertion process is the following (x 200):
Create product in Firestore.
Firebase cloud function listener :
OMG new product inserted in Firestore. Ok let's :
Import official nodejs Stripe & Algolia libraries
Create product in Stripe to make it billable
Create the 100 SKU related to the product in Stripe, with Promise.all (This is where, at some point, I end up with a rate limit error, because my concurrent cloud functions instances are using the same Stripe key, which means the same Stripe account)
Create product in Algolia to make it searchable
I need solutions to counter this Stripe API rate limit error.
I have several solutions in mind :
Solution 1 :
Be able to increase Stripe rate API limit for a given amount of time.
Not sure this is possible.
Solution 2 :
Be able to use differents Stripe keys, then rotate over them, to perform admin stuff, such inserting multiple products/SKUs in Stripe.
Ultimately on production, be able to create programmatically 1 Stripe key per user, so each user would have its own limit.
Not sure this is possible.
Solution 3 :
Slow down insertion process in javascript.
Don't know how to perform that.
Besides, Cloud functions have a budget/limit of 60 seconds for javascript execution. So I can't delay too much.
Solution 4 :
Delay work using Pub/Sub (?), or Firestore Triggers
For example, having an integer in Firestore, that each function call increments, and same function listen the write to re-increment he number, etc, etc, etc, until the number equals 100 for the 100th SKU. That solution would sequentialize the 100 SKUs writes in Stripe.
Not sure this will really slow down enough the work to be under the API rate limit. In addition, such a solution would cost lots of money : 100+ Firestore writes, and 100+ functions calls to perform these writes, for only one product, which means 20000+/20000+ for the 200 products. That would be expensive.
Solution 5 :
Perform Just-In-Time insertions, when user pays.
The server side algorithm, after a Payment Request API call, might look like this :
Create order in Stripe
If error 'No such sku...' catched {
For each SKU { // Ideally filter here SKUs to create (only those in error)
If price not between 1 and 100 {
continue // Bad price, not legit
}
Create SKU in Stripe
If error 'Already exists' {
continue // no creation needed for that SKU
}
If error 'No such product...' catched {
If productId does not exists in Firestore {
continue // Bad productId, not legit
}
Create product in Stripe
}
Create SKU in Stripe
}
}
Create order in Stripe
This last solution could do the job.
But it might comes with some delay for the user when it executes payment, which could increase stress. Plus it might increase Stripe calls during the business hours. Many purchases in same time could lead to a Stripe API rate limit error, especially with well furnished carts (let's say an average of 30 products in the cart, so in worst case 30+ HTTPS calls during payment, times 1000 users = 30000 calls => Stripe error). That problem might decrease over time for a given product, because once a SKU is created it is created definitively. Still, as there would be new products, so products with zero SKU at creation, every day, the problem remains.
What do you think ?
Do you have any other ideas ?

Answer 1

Solution 3 and Solution 5 with some tweaks will work best.
Solution 3: You can limit number of concurrent requests to Stripe using async module's forEachLimit or queue.
Solution 5 : Just in time insertions is also a good option as it won't put much load on Stripe server at same time. Regarding your concern of getting the same error during business hour, it will a very rare case as Stripe APIs are built to perform very well. But if you still have doubt regarding this what you can do is to have a Background process for adding SKUs during non-business hours, which will keep on creating SKUs for you without encountering Stripe API rate limit error.
Solution 6 (Modified Solution 5): Have just in time insertions but also create an extra API request to your server whenever a product is entered in the cart which will then check if the SKU exist in Stripe and if not then create it in the background before cart payment happens.

Answer 2

Solution 6 :
Same idea (JIT), but moving SKU creation from payment time to product selection time. Each time a product is selected, try to create the product and its current SKU (price variation) in Stripe. This way, Stripe calls should be more distributed in the time. Or maybe it will ends with more API calls, as we select products more often than we pay, because users can select & unselect products, so they might end with more products selected during their journey than the sum of products finally being paid in the cart ?
Solution 7 :
Same idea (JIT), but with SKU cached in Algolia or Firebase, so I can perform "does this SKU exist ?" calls without querying Stripe, which should reduces Stripe calls if the existence test is performed before the create call (we do not call Stripe.skus.create() blindly). The drawback is, that Firebase and Algolia are exposed in Front so the SKUs and prices will be too, and this is a potential source of threat, so another index, dedicated and only known by the server, has to be used.