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| Vendor: | Arcitura Education |
|---|---|
| Exam Code: | S90.08B |
| Exam Name: | SOA Design & Architecture Lab with Services & Microservices |
| Exam Questions: | 17 |
| Last Updated: | August 23, 2026 |
| Related Certifications: | SOA Certified Professional Gen 2 |
| Exam Tags: |
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Refer to Exhibit.

Our service inventory contains the following three services that provide Invoice-related data access capabilities: Invoice, InvProc and Proclnv. These services were created at different times by different project teams and were not required to comply with any design standards. Therefore, each of these services has a different data model for representing invoice data.
Currently, each of these three services has a different service consumer: Service Consumer A accesses the Invoice service (1), Service Consumer B (2) accesses the InvProc service, and Service Consumer C (3) accesses the Proclnv service. Each service consumer invokes a data access capability of an invoice-related service, requiring that service to interact with the shared accounting database that is used by all invoice-related services (4, 5, 6).
Additionally, Service Consumer D was designed to access invoice data from the shared accounting database directly (7). (Within the context of this architecture, Service Consumer D is labeled as a service consumer because it is accessing a resource that is related to the illustrated service architectures.)
Assuming that the Invoice service, InvProc service and Proclnv service are part of the same service inventory, what steps would be required to fully apply the Official Endpoint pattern?
he Legacy Wrapper pattern can be applied so that Component B is separated into a separate utility service that wraps the shared database. The Legacy Wrapper pattern can be applied again so that Component C is separated into a separate utility service that acts as a wrapper for the legacy system API. The Legacy Wrapper pattern can be applied once more to Component D so that it is separated into another utility service that provides standardized access to the file folder. The Service Facade pattern can be applied so that three facade components are added: one between Component A and each of the new wrapper utility services. This way, the facade components can compensate for any change in behavior that may occur as a result of the separation. The Service Composability principle can be further applied to Service A and the three new wrapper utility services so that all four services are optimized for participation in the new service composition. This will help make up for any performance loss that may result from splitting the three components into separate services.
By applying the Legacy Wrapper pattern to separate Components B, C, and D into three different utility services, the shared resources within the IT enterprise (Database A, the legacy system, and the file folders) can be properly encapsulated and managed by dedicated services. The Service Facade pattern can then be used to create a facade component between Component A and each of the new wrapper utility services, allowing them to interact seamlessly without affecting Service Consumer A's behavior.
Finally, the Service Composability principle can be applied to ensure that Service A and the three new wrapper utility services are optimized for participation in the new service composition. This will help to mitigate any performance loss that may result from splitting the three components into separate services.
Refer to Exhibit.

Service A is an entity service that provides a Get capability which returns a data value that is frequently changed.
Service Consumer A invokes Service A in order to request this data value (1). For Service A to carry out this request, it must invoke Service B (2), a utility service that interacts (3, 4) with the database in which the data value is stored. Regardless of whether the data value changed, Service B returns the latest value to Service A (5), and Service A returns the latest value to Service Consumer A (6).
The data value is changed when the legacy client program updates the database (7). When this change will occur is not predictable. Note also that Service A and Service B are not always available at the same time.
Any time the data value changes, Service Consumer A needs to receive It as soon as possible. Therefore, Service Consumer A initiates the message exchange shown In the figure several times a day. When it receives the same data value as before, the response from Service A Is ignored. When Service A provides an updated data value, Service Consumer A can process it to carry out its task.
The current service composition architecture is using up too many resources due to the repeated invocation of Service A by Service Consumer A and the resulting message exchanges that occur with each invocation.
What steps can be taken to solve this problem?
This solution is the most appropriate one among the options presented. By using the Event-Driven Messaging pattern, Service A can be notified of changes to the data value without having to be invoked repeatedly by Service Consumer A, which reduces the resources required for message exchange. Asynchronous Queuing ensures that the event notification message is not lost due to the unavailability of Service A or Service B. This approach improves the efficiency of the service composition architecture.
Refer to Exhibit.

Service A sends a message to Service B (1). After Service B writes the message contents to Database A (2), it issues a response message back to Service A (3). Service A then sends a message to Service C (4). Upon receiving this message, Service C sends a message to Service D (5), which then writes the message contents to Database B (6) and issues a response message back to Service C (7).
Service A and Service D are located in Service Inventory
This solution addresses the two main challenges in the service composition architecture: the different XML schema used by services in Service Inventory A and Service Inventory B, and the incompatible data formats of the two databases.
By applying the Data Model Transformation pattern, data model transformation logic can be inserted to map the invoice-related data between the different XML schemas used by the services in Service Inventory A and Service Inventory B. This can be done at the appropriate points in the message flow: between Service A and Service B, between Service A and Service C, between Service C and Service D, and between the Service D logic and Database B.
By applying the Data Format Transformation pattern, data format transformation logic can be inserted to convert the XML-formatted data used by the services to the CSV format required by Database A, and to convert the proprietary XML schema used by Database B to the XML schema used by the services. This can be done between the Service B logic and Database A.
The Protocol Bridging pattern is not necessary in this case because all services are already communicating using the same protocol (presumably HTTP or a similar protocol).
Refer to Exhibit.

Service A is a task service that sends Service B a message (2) requesting that Service B return data back to Service A in a response message (3). Depending on the response received, Service A may be required to send a message to Service C (4) for which it requires no response.
Before it contacts Service B, Service A must first retrieve a list of code values from its own database (1) and then place this data into its own memory. If it turns out that it must send a message to Service C, then Service A must combine the data it receives from Service B with the data from the code value list in order to create the message it sends to Service C. If Service A is not required to invoke Service C, it can complete its task by discarding the code values.
Service A and Service C reside in Service Inventory
The problem is that Service A and Service B are using different technologies and cannot communicate. Therefore, an intermediate processing layer can be established that can transform messages from one data format to another at runtime. This can be achieved using the Data Format Transformation pattern.
Additionally, Service C frequently reaches its usage thresholds and is not always available, so an Asynchronous Queuing pattern can be applied to establish an intermediate queue between Service A and Service C. This queue will store the messages sent by Service A to Service C and retransmit them until they are successfully delivered. This approach improves the reliability of the system.
Moreover, the Redundant Implementation pattern can be applied to Service C to ensure its availability and scalability, and the Service Autonomy principle can be applied to make Service C independent of other services.
Refer to Exhibit.

Service Consumer A and Service A reside in Service Inventory
The Asynchronous Queuing pattern is applied to position a messaging queue between Service A, Service B, Service C, Service D, and Service Consumer A. This ensures that messages can be passed between these services without having to be in a stateful mode.
The Data Model Transformation and Protocol Bridging patterns are applied to enable communication between Service A and Service B, Service A and Service C, and Service A and Service D, despite their different data models and transport protocols.
The Redundant Implementation pattern is applied to bring a copy of Service D in-house to ensure that it can be accessed locally and reduce the unpredictability of its performance.
The Legacy Wrapper pattern is applied to wrap Service D with a standardized service contract that complies with the design standards used in Service Inventory B. This is useful for service consumers who want to use Service D but do not want to change their existing applications or service contracts.
Overall, this approach provides a comprehensive solution that addresses the issues with Service A, Service B, Service C, and Service D, while maintaining compliance with the Service Abstraction principle.
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