Is there a good way to retry failed subscription payments? Sometimes our customers will fail a payment but then have money the next day, so we just want to retry the payment instead of having them update their card. Some things we've tried:
Foolishly signed up for "Automatic Retry" thinking it would automatically retry, but it only retries after the customer updates their card.
In order for Automatic Retry to kick in, the subscription needs to change from Suspended to Active which has to be done manually according to support. There's really no way to do this through the API?
Our last resort: On any failed subscription, cancel the subscription and re-create it from the profile, starting on the date we want to retry the payment. Any downsides to this I'm not considering?
There is no way to automatically retry a failed subscription payment through their API. That thread is a few years old but no new endpoints were added since then to enable this functionality.
On any failed subscription, cancel the subscription and re-create it from the profile, starting on the date we want to retry the payment. Any downsides to this I'm not considering?
You will incur transaction fees for retrying even though the chance for success is low.
Make sure you control all notifications. If your user gets emails telling them they're making unexpected payments or setting up new subscriptions you run the risk of chargebacks which could cause you to lose your ability to accept credit cards.
Related
I have a question regarding the effect of eventually consistent (EC) microservice systems.
Imagine we have a booking system - a user-service A and booking-service B. Each service has its own database. Imagine the system does a concurrent booking of the same resource for distinct users at the same time. Lets assume we have a Runtime Verification System checking the concurrent booking.
Would it be possible that the monitor does not realize the concurrent booking at B, because the update in the database is done delayed because of the EC mechanism?
In your example, the Booking Service is the source of truth (presumably) for whether or not the resource is available to book. So, that service should be pretty clear on allowing the first booking request to happen and rejecting the second.
In a case like this, where "first come first served" is the requirement, you'd want an intermediate state that would wait for a response from the Booking Service and update the User Service only when a response has been received.
If your architecture is set up right, User Service shouldn't be calling Booking Service directly anyway - it should be communicating through a messaging plane. As such, when the User clicks "Book Now," you could generate a resourceBookingRequested message and submit it to the queue. You'd acknowledge this request has been queued to the user and update their UI to "Awaiting Booking Confirmation..." or something similar.
Once the booking is accepted, or rejected, the User Service subscribes to the resulting message and updates the UI (and/or takes other actions like sending an email) to let the user know their request succeeded or didn't.
Having OTRS queues to run escalations are fine. The thing is, that the tickets stay escalated if the solution time is exceeded.
The thing is sometimes it is a client responsibility to deliver something to close the ticket.
In this case the client gets a response.
How can I reset the escalation time to the time the ticket is replied and the pending is set to a specific date?
So the escalation time will occur e.g. 1 day after the pending date.
Just check https://www.znuny.com/add-ons/znuny4otrs-repository and follow the instructions. After this the package is available the package manager
try the free add-on Znuny4OTRS-EscalationSuspend. Then you can configure states where escalations are suspended. E.g. a state like 'pending customer feedback'
We have a system that manages our G Suite Reseller via the API.
Given a G Suite subscription that has been suspended because it has already passed its annual commitment period (and its renewal setting is set to "CANCEL" i.e. be suspended after its commitment period), will the "Activate" request be enough to immediately re-activate the subscription with the same plan details that it had before (i.e. same plan and renewal settings)?
I have checked this article and it only mentions briefly that to activate a suspended account, the activate code simply has to be called:
https://developers.google.com/admin-sdk/reseller/v1/reference/subscriptions/changeRenewalSettings#renewalType
Could anyone clarify or verify this? I am unable to test it since our G Suite sandbox environment does not have any subscriptions that have already exceeded its commitment period (and I am unable to create one with that setup either).
It was clearly stated in the G Suite Administrator Help to "Avoid suspension".
However, if it happen, you can follow the steps on how to renew an expired domain registration.
But you have to consider this:
Note: We can't guarantee that you can renew an expired domain
purchased through Google. It depends on whether the domain is still
available from your domain host. In any case, try to renew the domain
right away. The longer you wait, the less likely you'll be able to
renew. As a general rule, you should renew within 19 days of the
official renewal date to increase the chances that you can renew
successfully.
You have to first changeplan with customerId/domain and subscriptionId
Then call activate.
NOTE:
calling activate on subscriptions which are suspended after trail was completed will result in failure.But if the plan is set you can call activate.
Pay attention to suspensionReasons in API response.
Given that I am a bit confused with CQRS I would like to understand it further in the following scenario.
I have an Actor that charge Users' credit card. To do so it contact a bank external service that does the operation, get a confirmation result. I would like to know how can I apply this with CQRS.
The information that needs to be written here is that a specific user has been charge a certain amount. So the event generated is Charged (UserID, Card, Amount). Something like that.
The problem is that all the examples I have seen especially with AKKA, would only generate the event after a Command is validated, such that it is persisted in a journal, and used to update the state of the actor. The Journal could then be red on the other side, such that to create a Reading view here.
Also usually, in those examples, the update state function has a logic that somewhat execute the command, because the command correspond straightforwardly to a state update at the end of the day. This is the typical BasketShoping example: CreateOrder, AddLineItem. All Of this Command, are directly translated in Event, that correspond to a specific code of the Update state function.
However in this example, one needs to actually contact an external service, charge the user and then generate an event. Contacting the external service can't be done in the update state, or after reading the journal. It would not make sense.
How is that done, and where, and when exactly, in the spirit of CQRS?
I can think of 2 ways of doing this.
First is a simple way. The command is DoCharge(UserId, Card, Amount). Upon reception of this command, you call the external payment service. If this has been successfully completed, you generate an event, Charged(UserId, Card, Amount, TransactionId) and store it in the journal.
Now, of course, it's not completely safe way, because your Actor can crash after it has sent the request to payment service, but before it has received and persisted the confirmation of the successful completion. Then you risk of charging the user twice. To overcome this risk, you have to make your payment operation idempotent. Here's how to do it. This example is based on the classic "RESTify Day trader" article. I'll summarize it here.
You need to split the payment operation in 2 phases. In first one, payment service creates a transaction token. It just identifies the transaction, and no financial operations are performed yet. Upon the creation, the identifier is received by your service and persisted in the journal.
In next phase you perform a payment associated with the identifier from phase one. If your actor now fails in the middle, while operation is performed successfully on the payment service side, the transaction token will already be marked as processed by the payment service, and it won't let you charge the customer twice. Now, if you restart the failed Actor, and it tries to run the payment associated with the existing transaction token, the payment service should return result like "Already executed" or such. Of course, at the end you also persist the result of the operation in the journal.
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)
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.
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.
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.