Database – Aggregation of data from two Microservices

Reading your question I'm not sure you are thinking about microservices in the same way as me.

For example I would never create a validation microservice. In theory, sure I can see it might work, but say you have your AddUser() method on your UserService, its always gona call the validation service for that particular action right?

Separating out the validation logic is all well and good, but if nothing else is ever going to call it I wouldn't expose that code it as a service.

I see microservices as vertical slices if your monolith rather than horizontal layers, which you may already have.

So for me the naming is easy. UserService, OrderService etc perhaps we have a complex case where you can split these further, but the naming will be clear from the logic which suggest the split. ie AdminUserService/UserService

Obviously you may have a case where two service share some internal logic and ot makes sense to split that out into its own service. But again, the naming is clear from the purpose of the code rather than the layer. ie AccountService and OrderService might both call OrderPricingService.

Additionally don't get hung up on the word 'service' a UserRepository is a repository whether you access it via http or in memory.

Also, don't throw away all your OOP objects with thier business logic and make everything procedural unless it makes sense. You can have your services instanciate objects and call thier methods in a high level microservice rather than convert them all to individual OrderBusinessLogicService.ProcessOrder(Order o) services

Exceptions should be treated just like domain models. Each service works with their own domain models and should have their own set of exception models as well. When communicating with external systems, the service should convert external exceptions to its domain exceptions as soon as possible. Basically I'm saying go with solution #2.

Lets consider the communication from service A -> B. Service A should first of all have an interface defined to decouple the business logic from the implementation of requests to B. In your example A is an account service and B is a user service. So let's call the interface UserService. This interface would have a set of (ideally) compiler-checked exceptions.

interface UserService
    def getUser(id): User throws UserNotFoundException, UserServiceException

You should implement HTTP client for service B so that any service that needs to depend on service B imports the common HTTP client. The error responses from requests to service B will be defined in this HTTP client component. That way they're only defined once.

class BHttpClient
    def getUserById(id) = 
        response = http.get("/users/${id}").send
        if (response.status == 404) throw new UnknownUserException
        else if (response.status == 500) throw new InternalServerException
        else return json.parse[User](response.content)

The implementation of UserService, HttpUserService will use that HTTP client to communicate with B, should catch HTTP and transport exceptions from the client and wrap them in the appropriate "domain" exception.

class HttpUserService(client: BHttpClient) implements UserService
    def getUser(id) = 
        try {
            client.getUserById(id)
        } catch {
            case e: UnknownUserException => throw new UserNotFoundException(e)
            case e: InternalServerException => throw new UserServiceException(e)
        }

Cons: Service A will need to catch and expect that Server B is capable of returning a bunch of errors, adding coupling between Service A and B.

Service A will catch errors from the http client in HttpUserService and wrap them in meaningful errors for service A. The business logic in service A is decoupled from service B through the UserService interface. HttpUserService is coupled to BHttpClient, but decoupled from service B because you can mock service B at the transport level.

Even if you choose to use a different architecture like @Laiv describes in the comments, you'll still want to decouple yourself from message and events you receive by converting the message models and exceptions into domain exceptions in each service. I don't agree with @Laiv, that it's as cut and dry as asynchronous message architecture or you might as well implement a monolith. There are still big gains that can be made by a synchronous, distributed service oriented architecture like you've described. The first and hardest step of getting the right architecture is to decouple the components. By dividing into microservices early, you can more easily adopt an asynchronous approach later if you need it.