web services – Architecture for robust payment processing – Education Career Blog

Imagine 3 system components:
1. External ecommerce web service to process credit card transactions
2. Local Database to store processing results
3. Local UI (or win service) to perform payment processing of the customer order document

The external web service is obviously not transactional, so how to guarantee:
1. results to be eventually persisted to database when received from web service even in case the database is not accessible at that moment(network issue, db timeout)
2. prevent clients from processing the customer order while payment initiated by other client but results not successfully persisted to database yet(and waiting in some kind of recovery queue)

The aim is to do processing having non transactional system components and guarantee the transaction won’t be repeated by other process in case of failure.

(please look at it in the context of post sell payment processing, where multiple operators might attempt manual payment processing; not web checkout application)

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Ask the payment processor whether they can detect duplicate transactions based on an order ID you supply. Then if you are unable to store the response due to a database failure, you can safely resubmit the request without fear of double-charging (at least one PSP I’ve used returned the same response/auth code in this scenario, along with a flag to say that this was a duplicate).

Alternatively, just set a flag on your order immediately before attempting payment, and don’t attempt payment if the flag was already set. If an error then occurs during payment, you can investigate and fix the data at your leisure.

I’d be reluctant to go down the route of trying to automatically cancel the order and resubmitting, as this just gets confusing (e.g. what if cancelling fails – should you retry or not?). Best to keep the logic simple so when something goes wrong you know exactly where you stand.

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In any system like this, you need robust error handling and error reporting. This is doubly true when it comes to dealing with payments, where you absolutely do not want to accidentaly take someone’s money and not deliver the goods.

Because you’re outsourcing your payment handling to a 3rd party, you’re ultimately very reliant on the gateway having robust error handling and reporting systems.

In general then, you hand off control to the payment gateway and start a task that waits for a response from the gateway, which is either ‘payment accepted’ or ‘payment declined’. When you get that response you move onto the next step in your process and everything is good.

When you don’t get a response at all (time out), or the response is invalid, then how you proceed very much depends on the payment gateway:

  • If the gateway supports it send a ‘cancel payment’ style request. If the payment cancels successfully then you probably want to send the user to a ‘sorry, please try again’ style page.

  • If the gateway doesn’t support canceling, or you have no communications to the gateway then you will need to manually (in person, such as telephone) contact the 3rd party to discover what went wrong and how to proceed. To aid this you need to dump as much detail as you have to error logs, such as date/time, customer id, transaction value, product ids etc.

Once you’re back on your site (and payment is accepted) then you’re much more in control of errors, but in brief if you cant complete the order, then you should either dump the details to disk (such as csv file for manual handling) or contact the gateway to cancel the payment.

Its also worth having a system in place to track errors as they occur, and if an excessive number occur then consider what should happen. If its a high traffic site for example you may want to temporarily prevent further customers from placing orders whilst the issue is investigated.

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Distributed messaging.

When your payment gateway returns submit a message to a durable queue that guarantees a handler will eventually get it and process it. The handler would update the database. Should failure occur at that point the handler can leave the message in the queue or repost it to the queue, or post an alternate message.

Should something occur later that invalidates the transaction, another message could be queued to “undo” the change.

There’s a fair amount of buzz lately about eventual consistency and distribute messaging. NServiceBus is the new component hotness. I suggest looking into this, I know we are.

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