In my company (train company) there is a sort of battle going on over two viewpoints on something. Before going to deep into the problem I'm first going to explain the different domains we have in our landscape now.
Product: All product master data and their characteristics.
Think their name, their possible list of choices...
Location: All location master data that can be chosen, like stations, stops, etc.
Quote: To get a price for a specific choice of a product with their attributes.
Order: The order domain where you can make a positive order but also a negative one for reimbursements.
Ticket: This is essentially what you get from paying the order. Its the product but in the state that its at, when gotten by the customer.
The problem
Viewpoint PURPLE (I don't want to create bias)
When an order is transformed into all "tickets", we convert the order details, like price, into the ticket model. In order to make Order something we can throw away. Order is seen as something transient. Kind of like the bag you have in a supermarket. Its the goods inside the bag that matter. Not the bag itself.
When a reimburse flow would start. You do not need to go to the order. You would have everything in the Ticket domain. So this means data from order will be duplicated to Ticket.
But not all, only the things that are relevant. Like price for example.
Viewpoint YELLOW (I don't want to create bias)
You do the same as above but you do not store the price in Ticket domain. The ticket domain only consist of details that are relevant for the "ticket" to work. Price is not allowed in there cause its a thing of the order. When a reimburse flow would start, its allowed to go fetch those details from the order. Making order not something you can throw away as its having crucial data inside of it.
The benefit here is that Order is not "polluting" the Ticket with unnecessary data. But this is debatable. The example of the price is a good example.
I wish to know your ideas about these two viewpoints.
There is no "Don't repeat yourself" when it comes to the business domain. The only thing that dictates the business domain is the business requirements. If the requirements state that the ticket should work independent of the order changes, then you have to duplicate things.
But in this case, the requirements are ambiguous. There is no correct design using the currently specified requirements. Building code based on assumptions is the #1 way of getting bad code, since you most likely will have to do a redesign down the road.
You need to go back to the product owner and ask him about the difference between the Order and the Ticket.
For instance:
What should happen to the ticket if the order is deleted?
What happens to the order and/or ticket if the product price changes?
What happens to a ticket if the order is reimbursed?
Go back, get better requirements and then start to design the application.
Related
I will try to keep this as generic as possible using the “order” and “product” example, to try and help others that come across this question.
The Structure:
In the application we have 3 different services, 2 services that follow the event sourcing pattern and one that is designed for read only having the separation between our read and write views:
- Order service (write)
- Product service (write)
- Order details service (Read)
The Background:
We are currently storing the relationship between the order and product in only one of the write services, for example within order we have a property called ‘productItems’ which contains a list of the aggregate Ids from Product for the products that have been added to the order. Each product added to an order is emitted onto Kafka where the read service will update the view and form the relationships between the data.
The Problem:
As we pull back by aggregate Id for the order and the product to update them, if a product was to be deleted, there is no way to disassociate the product from the order on the write side.
This in turn means we have inconsistency, that the order holds a reference to a product that no longer exists within the product service.
The Ideas:
Master the relationship on both sides, which means when the product is deleted, we can look at the associated orders and trigger an update to remove from each order (this would cause duplication of reference).
Create another view of the data that shows the relationships and use a saga to do a clean-up. When a delete is triggered, it will look up the view database, see the relationships within the data and then trigger an update for each of the orders that have the product associated.
Does it really matter having the inconsistencies if the Product details service shows the correct information? Because the view database will consume the product deleted event, it will be able to safely remove the relationship that means clients will be able to get the correct view of the data even if the write models appear inconsistent. Based on the order of the events, the state will always appear correct in the read view.
Another thought: as the aggregate Id is deleted, it should never be reused which means when we have checks on the aggregate such as: “is this product in the order already?” will never trigger as the aggregate Id will never be repurposed meaning the inconsistency should not cause an issue when running commands in the future.
Sorry for the long read, but these are all the ideas we have thought of so far, and I am keen to gain some insight from the community, to make sure we are on the right track or if there is another approach to consider.
Thank you in advance for your help.
Event sourcing suites very well human and specifically human-paced processes. It helps a lot to imagine that every event in an event-sourced system is delivered by some clerk printed on a sheet of paper. Than it will be much easier to figure out the suitable solution.
What's the purpose of an order? So that your back-office personnel would secure the necessary units at a warehouse, then customer would do a payment and you start shipping process.
So, I guess, after an order is placed, some back-office system can process it and confirm that it can be taken into work and invoicing. Or it can return the order with remarks that this and that line are no longer available, so that a customer could agree to the reduced order or pick other options.
Another option is, since the probability of a customer ordering a discontinued item is low, just not do this check. But if at the shipping it still occurs - then issue a refund and some coupon for inconvenience. Why is it low? Because the goods are added from an online catalogue, which reflects the current state. The availability check can be done on the 'Submit' button click. So, an inconsistency may occur if an item is discontinued the same minute (or second) the order has been submitted. And usually the actual decision to discontinue is made up well before the information was updated in the Product service due to some external reasons.
Hence, I suggest to use eventual consistency. Since an event-sourced entity should only be responsible for its own consistency and not try to fulfil someone else's responsibility.
For my internship, I need to implement a blockchain based solution to manage a drug supply chain. The management of this supply chain implies to track-and-trace (geolocate) a drug on the chain, but also to monitor the storage temperature to see if the cold chain is respected. For that I created a mock-up of the POC my Dapps (https://balsamiq.cloud/sum5oq5/p8lsped)and also I wanted to prepare myself by doing a UML and a use cases. However, I didn't find a lot of information about blockchain's UML and use cases besides two literatures which were quite different, so I don't know if what I did was correct or not...
The users of my Dapps will be the following ones:
The stakeholders (Manufacturers, Distributors and Retailers) which will use the Dapps to place orders and also monitor them. They also can search in the historic a specific order. Finally, trough IOT sensors they update the conditions of the order (temperature & location).
The administrator which roles is to update the Dapps and its rules. But also to add or delete user while also defining the rights that they have on the blockchain (I intend to use a permisionned blockchain). Finally, they are also here to help in case of technical problem.
The Dapps that I'm thinking about works in the following:
A user, the customer, can place an order (a list of products) to a
certain seller and choose the final destination of the order.
The order is then put together before being shipped or stocked in the
depots of one of the stakeholders (distributor or retailer) with a
description of the stocking and/or shipping condition of the product
(for example the product must be stocked or transported in a room
with a temperature of less than 5°C). During the shipping and
storing, an IOT device will feed the drops with the temperature and
geolocation of the product by updating the data each 5-10mn.
Obviously they will be a function that allows all the users to see
the history of the order passed and search inside a specific order.
In case where the temperature doesn't respect the temperature
recommended, then the smart-contract send an alert. The same if the
collocation of the product is "weird" like being in some European
countries and not in an Asian country, an alert will be sent again by
the smart-contractual. Finally, in the case where the product is sent
to the asked location by the customer, then the money for the order
will be paid to the seller.
So based on what I explained, I came here in hope that someone tell me if the use cases and UML that I did were correct or not.
I thank in advance anybody who'll take the time to help me.
I want to sanity check myself on a view projection, in regards to if an intermediary concept can purely exist in the read model while providing a bridge between commands.
Let me use a contrived example to explain.
We place an order which raises an OrderPlaced event. The workflow then involves generating a picking slip, which is used to prepare a shipment.
A picking slip can be generated from an order (or group of orders) without any additional information being supplied from any external source or user. Is it acceptable then that the picking slip can be represented purely as a read model?
So:
PlaceOrderCommand -> OrderPlacedEvent
OrderPlacedEvent -> PickingSlipView
The warehouse manager can then view a picking slip, select the lines they would like to ship, and then perform a PrepareShipment command. A ShipmentPrepared event will then update the original order, and remove the relevant lines from the PickingSlipView.
I know it's a toy example, but I have a conceptually similar use case where a colleague believes the PickingSlip should be a domain entity/aggregate in its own right, as it's conceptually different to order. So you have PlaceOrder, GeneratePickingSlip, and PrepareShipment commands.
The GeneratePickingSlip command however simply takes an order number (identifier), transforms the order data into a picking slip entity, and persists the entity. You can't modify or remove a picking slip or perform any action on it, apart from using it to prepare a shipment.
This feels like introducing unnecessary overhead on the write model, for what is ultimately just a transformation of existing information to enable another command.
So (and without delving deeply into the problem space of warehouses and shipping)...
Is what I'm proposing a legitimate use case for a read model?
Acting as an intermediary between two commands, via transformation of some data into a different view. Or, as my colleague proposes, should every concept be represented in the write model in all cases?
I feel my approach is simpler, and avoiding unneeded complexity, but I'm new to CQRS and so perhaps missing something.
Edit - Alternative Example
Providing another example to explore:
We have a book of record for categories, where each record is information about products and their location. The book of record is populated by an external system, and contains SKU numbers, mapped to available locations:
Book of Record (Electronics)
SKU# Location1 Location2 Location3 ... Location 10
XXXX Introduce Remove Introduce ... N/A
YYYY N/A Introduce Introduce ... Remove
Each book of record is an entity, and each line is a value object.
The book of record is used to generate different Tasks (which are grouped in a TaskPlan to be assigned to a person). The plan may only cover a subset of locations.
There are different types of Tasks: One TaskPlan is for the individual who is on a location to add or remove stock from shelves. Call this an AllocateStock task. Another type of Task exists for a regional supervisor managing multiple locations, to check that shelving is properly following store guidelines, say CheckDisplay task. For allocating stock, we are interested in both introduced and removed SKUs. For checking the displays, we're only interested in newly Introduced SKUs, etc.
We are exploring two options:
Option 1
The person creating the tasks has a View (read model) that allows them to select Book of Records. Say they select Electronics and Fashion. They then select one or more locations. They could then submit a command like:
GenerateCheckDisplayTasks(TaskPlanId, List<BookOfRecordId>, List<Locations>)
The commands would then orchestrate going through the records, filtering out locations we don't need, processing only the 'Introduced' items, and creating the corresponding CheckDisplayTasks for each SKU in the TaskPlan.
Option 2
The other option is to shift the filtering to the read model before generating the tasks.
When a book of record is added a view model for each type of task is maintained. The data might be transposed, and would only include relevant info. ie. the CheckDisplayScopeView might project the book of record to:
Category SKU Location
Electronics (BookOfRecordId) XXXX Location1
Electronics (BookOfRecordId) XXXX Location3
Electronics (BookOfRecordId) YYYY Location2
Electronics (BookOfRecordId) YYYY Location3
Fashion (BookOfRecordId) ... ... etc
When generating tasks, the view enables the user to select the category and locations they want to generate the tasks for. Perhaps they select the Electronics category and Location 1 and 3.
The command is now:
GenerateCheckDisplayTasks(TaskPlanId, List<BookOfRecordId, SKU, Location>)
Where the command now no longer is responsible for the logic needed to filter out the locations, the Removed and N/A items, etc.
So the command for the first option just submits the ID of the entity that is being converted to tasks, along with the filter options, and does all the work internally, likely utilizing domain services.
The second option offloads the filtering aspect to the view model, and now the command submits values that will generate the tasks.
Note: In terms of the guidance that Aggregates shouldn't appear out of thin air, the Task Plan aggregate will create the Tasks.
I'm trying to determine if option 2 is pushing too much responsibility onto the read model, or whether this filtering behavior is more applicable there.
Sorry, I attempted to use the PickingSlip example as I thought it would be a more recognizable problem space, but realize now that there are connotations that go along with the concept that may have muddied the waters.
The answer to your question, in my opinion, very much depends on how you design your domain, not how you implement CQRS. The way you present it, it seems that all these operations and aggregates are in the same Bounded Context but at first glance, I would think that there are 3 (naming is difficult!):
Order Management or Sales, where orders are placed
Warehouse Operations, where goods are packaged to be shipped
Shipments, where packages are put in trucks and leave
When an Order is Placed in Order Management, Warehouse reacts and starts the Packaging workflow. At this point, Warehouse should have all the data required to perform its logic, without needing the Order anymore.
The warehouse manager can then view a picking slip, select the lines they would like to ship, and then perform a PrepareShipment command.
To me, this clearly indicates the need for an aggregate that will ensure the invariants are respected. You cannot select items not present in the picking slip, you cannot select more items than the quantities specified, you cannot select items that have already been packaged in a previous package and so on.
A ShipmentPrepared event will then update the original order, and remove the relevant lines from the PickingSlipView.
I don't understand why you would modify the original order. Also, removing lines from a view is not a safe operation per se. You want to guarantee that concurrency doesn't cause a single item to be placed in multiple packages, for example. You guarantee that using an aggregate that contains all the items, generates the packaging instructions, and marks the items of each package safely and transactionally.
Acting as an intermediary between two commands
Aggregates execute the commands, they are not in between.
Viewing it from another angle, an indication that you need that aggregate is that the PrepareShippingCommand needs to create an aggregate (Shipping), and according to Udi Dahan, you should not create aggregate roots (out of thin air). Instead, other aggregate roots create them. So, it seems fair to say that there needs to be some aggregate, which ensures that the policies to create shippings are applied.
As a final note, domain design is difficult and you need to know the domain very well, so it is very likely that my proposed solution is not correct, but I hope the considerations I made on each step are helpful to you to come up with the right solution.
UPDATE after question update
I read a couple of times the updated question and updated several times my answer, but ended up every time with answers very specific to your example again and I'm most likely missing a lot of details to actually be helpful (I'd be happy to discuss it on another channel though). Therefore, I want to go back to the first sentence of your question to add an important comment that I missed:
an intermediary concept can purely exist in the read model, while providing a bridge between commands.
In my opinion, read models are disposable. They are not a single source of truth. They are a representation of the data to easily fulfil the current query needs. When these query needs change, old read models are deleted and new ones are created based on the data from the write models.
So, only based on this, I would recommend to not prepare a read model to facilitate your commands operations.
I think that your solution is here:
When a book of record is added a view model for each type of task is maintained. The data might be transposed, and would only include relevant info.
If I understand it correctly, what you should do here is not create view model, but create an Aggregate (or multiple). Then this aggregate can receive the commands, apply the business rules and mutate the state. So, instead of having a domain service reading data from "clever" read models and putting it all together, you have an aggregate which encapsulates the data it needs and the business logic.
I hope it makes sense. It's a broad topic and we could talk about it for hours probably.
I am working on DDD project and I am currently focused on two bouned contexts, Orders and Warehouse.
What confuses me is the following situation:
Order keep track of all the placed orders, and warehouse keeps track about all the available inventory. If user places one order for certain product item, that would mean one less item of that product in a warehouse. I am oversimplifying this process, so please bear with me.
Since two domain models are placed inside of a different BC, i am currently relying on eventual consistency ie. after one item has been sold, it would eventually be removed from the warehouse.
That situation unfortunately leads to the problem scenario where another user could simultaneously make another order of the same item, and it would appear as available until eventual consistency kicks is. That is something it is unacceptable by the domain expert.
So IMO I am stuck with two options
merge order and warehouse (at least the part regarding product
inventory, units available in warehouse) into one BC
have Order BC (or microservice if you wish) to be dependent of Warehouse BC (microservice) in order to pull a live product units
available
Which option does actually follows DDD patern? Is there another way out?
You could use a reservation system with a timeout.
Using a messaging analogy: With a broker-style queuing mechanism (such as RabbitMQ) you get a message from the queue and you have control over it until you either acknowledge that it can be removed from the queue or you release it back to the queue.
You could do the same thing in your ordering process. You reserve any items on your order. SO when you add them they have a status of, say, reserving and upon sending some message to reserve the items. If the response comes back you can decide how to proceed. Perhaps you could add any items that cannot be reserved onto a back order or try again later.
There are going to be different ways to approach this. Depending on your business case it may be acceptable to only check availability when someone really accepts the order.
If you domain expert reckons it is totally unacceptable that having this resolved at the end of the process then you could move it to the start. The issue is of course that user A could reserve and never buy thereby losing user B as a customer; whereas only applying the real "taking" of the item at the end of the process is closer to ensuring a purchase. But that is a business decision.
This issue is a really great example of where reality actually is eventually consistent. Is it really the best thing to decline an order if there is no inventory currently in the warehouse - even if there was a replenishment due in the next 20 minutes?
What if the item was actually on the shelf, but the operator hadn't yet keyed it into the system?
Sometimes designers and domain experts assume that people want 100% consistency, when really, users might be willing to accept a delay in confirmation of their order, if it increased the chance that their order would be accepted rather than rejected.
In the case above, why make it the user's job to retry their order N minutes later? In an eventually consistent system, you can accommodate such timing flexibility by including a timeout to retry the attempt to fulfill the order for a period of time before confirming to the client that it really wasn't possible.
There are technical solutions that will give you 100% consistency, but I think really this is not a technical challenge but a cultural/mindset one, changing people's minds about what is possible & acceptable to achieve an what is actually a better outcome.
IMO you can build a PlaceOrderSaga which will ask for inventory availability before placing the order.
I have an application in which an Engineer accesses gas wells. He can see a list of wells by choosing any combination of 7 characteristics. The characteristics are company, state, county, basin, branch, field, operator in their respective order. The application starts and I need to retrieve a list of companies. The companies the user sees is based on their security credentials. What would be my aggregate root/domain object which to base my repository. I first thought user, but I never retrieve anything about a user. The combination of those items and a couple of other attributes are collectively called wellheader information. Would that be the aggregate root or domain object for my repository?
Thanks in advance
With a short description like that, it can only be a quess on how your design could be.
As I read it, your are really interested in wells for a given engineer. (is the engineer the user you mention?)
So a first try could be to model the concept of a well as an aggregate root.
So maybe something like this:
ICollection<Well> wells = WellRepository.GetWellsForEngineer(engineerInstance);
Maybe your engineer is associated with a characteristics object.
Either way, you have to associate the engineer with wells in a given company, state and so on to be able to extract which wells the engineer is actualy assigned to.
If this dosen't help you, maybe you could elaborate on your domain.