S90.08B PDF Dumps Real 2023 Recently Updated Questions [Q10-Q28]

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S90.08B PDF Dumps Real 2023 Recently Updated Questions

Released SOA S90.08B Updated Questions PDF

NO.10 Refer to Exhibit.

Service Consumer A sends Service A a message containing a business document (1). The business document is received by Component A, which keeps the business document in memory and forwards a copy to Component B (3). Component B first writes portions of the business document to Database A (4). Component B then writes the entire business document to Database B and uses some of the data values from the business document as query parameters to retrieve new data from Database B (5).
Next, Component B returns the new date* back to Component A (6), which merges it together with the original business document it has been keeping in memory and then writes the combined data to Database C (7). The Service A service capability invoked by Service Consumer A requires a synchronous request-response data exchange. Therefore, based on the outcome of the last database update, Service A returns a message with a success or failure code back to Service Consumer A (8).
Databases A and B are shared, and Database C is dedicated to the Service A service architecture.
There are several problems with this architecture. The business document that Component A is required to keep in memory (while it waits for Component B to complete its processing) can be very large. The amount of runtime resources Service A uses to keep this data in memory can decrease the overall performance of all service instances, especially when it is concurrently invoked by multiple service consumers. Additionally, Service A can take a long time to respond back to Service Consumer A because Database A is a shared database that sometimes takes a long time to respond to Component B. Currently, Service Consumer A will wait for up to 30 seconds for a response, after which it will assume the request to Service A has failed and any subsequent response messages from Service A will be rejected.
What steps can be taken to solve these problems?

The Service Statelessness principle can be applied together with the State Repository pattern to extend Database C so that it also becomes a state database allowing Component A to temporarily defer the business document data while it waits for a response from Component B. The Service Autonomy principle can be applied together with the Legacy Wrapper pattern to isolate Database A so that it is encapsulated by a separate wrapper utility service. The Compensating Service Transaction pattern can be applied so that whenever Service A’s response time exceeds 30 seconds, a notification is sent to a human administrator to raise awareness of the fact that the eventual response of Service A will be rejected by Service Consumer A.

The Service Statelessness principle can be applied together with the State Repository pattern to establish a state database to which Component A can defer the business document data to while it waits for a response from Component B. The Service Autonomy principle can be applied together with the Service Data Replication pattern to establish a dedicated replicated database for Component B to access instead of shared Database A. The Asynchronous Queuing pattern can be applied to establish a message queue between Service Consumer A and Service A so that Service Consumer A does not need to remain stateful while it waits for a response from Service A.

The Service Statelessness principle can be applied together with the State Repository pattern to establish a state database to which Component A can defer the business document data while it waits for a response from Component B. The Service Autonomy principle can be applied together with the Service Abstraction principle, the Legacy Wrapper pattern, and the Service Fagade pattern in order to isolate Database A so that it is encapsulated by a separate wrapper utility service and to hide the Database A implementation from Service A and to position a fagade component between Component B and the new wrapper service. This fagade component will be responsible for compensating the unpredictable behavior of Database A.

None of the above.

NO.11

When Service A receives a message from Service Consumer A (1), the message is processed by Component A. This component first invokes Component B (2), which uses values from the message to query Database A in order to retrieve additional data. Component B then returns the additional data to Component A. Component A then invokes Component C (3), which interacts with the API of a legacy system to retrieve a new data value.
Component C then returns the data value back to Component A.
Next, Component A sends some of the data It has accumulated to Component D (4), which writes the data to a text file that is placed in a specific folder. Component D then waits until this file is imported into a different system via a regularly scheduled batch import. Upon completion of the import, Component D returns a success or failure code back to Component A. Component A finally sends a response to Service Consumer A (5) containing all of the data collected so far and Service Consumer A writes all of the data to Database B (6).
Components A, B, C, and D belong to the Service A service architecture. Database A, the legacy system and the file folders are shared resources within the IT enterprise.
Service A is an entity service with a service architecture that has grown over the past few years. As a result of a service inventory-wide redesign project, you are asked to revisit the Service A service architecture in order to separate the logic provided by Components B, C, and D into three different utility services without disrupting the behavior of Service A as it relates to Service Consumer A.
What steps can be taken to fulfill these requirements?

The Legacy Wrapper pattern can be applied so that Component B is separated into a separate wrapper utility service that wraps the shared database. The Asynchronous Queuing pattern can be applied so that a messaging queue is positioned between Component A and Component C, thereby enabling communication during the times when the legacy system may be unavailable or heavily accessed by other parts of the IT enterprise. The Service Fagade pattern can be applied so that a fagade component is added between Component A and Component D so that any change In behavior can be compensated.
The Service Autonomy principle can be further applied to Service A to help make up for any performance loss that may result from splitting the component into a separate wrapper utility service.

The 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 Fagade pattern can be applied so that three fagade components are added: one between Component A and each of the new wrapper utility services. This way, the fagade 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.

The 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. Component D can also be separated into a separate service and the Event-Driven Messaging pattern can be applied to establish a publisher-subscriber relationship between this new service and Component A. The interaction between Service Consumer A and Component A can then be redesigned so that Component A first interacts with Component B and the new wrapper service. Service A then issues a final message back to Service Consumer A. 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.

The Legacy Wrapper pattern can be applied so that Component B is separated into a separate wrapper utility service that wraps the shared database. The State Repository and State Messagingpatterns can be applied so that a messaging repository is positioned between Component A and Component C, thereby enabling meta data-driven communication during the times when the legacy system may be unavailable or heavily accessed by other parts of the IT enterprise. The Service Fagade pattern can be applied so that a fagade component is added between Component A and Component D so that any change in behavior can be compensated. The Service Statelessness principle can be further applied to Service A to help make up for any performance loss that may result from splitting the component into a separate wrapper utility service.

NO.12 Refer to Exhibit.

Service Consumer A and Service A reside in Service Inventory A. Service B and Service C reside in Service Inventory B. Service D is a public service that can be openly accessed via the World Wide Web. The service is also available for purchase so that it can be deployed independently within IT enterprises. Due to the rigorous application of the Service Abstraction principle within Service Inventory B, the only information that is made available about Service B and Service C are the published service contracts. For Service D, the service contract plus a service level agreement (SLA) are made available. The SLA indicates that Service D has a planned outage every night from 11:00pm to midnight.
You are an architect with a project team that is building services for Service Inventory A. You are told that the owners of Service Inventory A and Service Inventory B are not generally cooperative or communicative. Cross-inventory service composition is tolerated, but not directly supported. As a result, no SLAs for Service B and Service C are available and you have no knowledge about how available these services are. Based on the service contracts you can determine that the services in Service Inventory B use different data models and a different transport protocol than the services in Service Inventory A. Furthermore, recent testing results have shown that the performance of Service D is highly unpredictable due to the heavy amount of concurrent access it receives from service consumers from other organizations. You are also told that there is a concern over how long Service Consumer A will need to remain stateful while waiting for a response from Service A.
What steps can be taken to solve these problems?

The Event-Driven Messaging pattern can be applied to establish a subscriber-publisher relationship between Service Consumer A and Service A. This gives Service A the flexibility to provide its response to Service Consumer A whenever it is able to collect the three data values without having to require that Service Consumer A remain stateful. The Asynchronous Queuing pattern can be applied to position a central messaging queue between Service A and Service B and between Service A and Service C. The Data Model Transformation and Protocol Bridging patterns can be applied to enable communication between Service A and Service B and between Service A and Service C. The Redundant Implementation pattern can be applied so that a copy of Service D is brought in-house and made part of Service Inventory A.

The Asynchronous Queuing pattern can be applied to position a central messaging queue between Service A and Service B and between Service A and Service C and so that a separate messaging queue is positioned between Service A and Service Consumer A. The Data Model Transformation and Protocol Bridging patterns can be applied to enable communication between Service A and Service B and between Service A and Service C. The Redundant Implementation pattern can be applied so that a copy of Service D is brought in-house. The Legacy Wrapper pattern can be further applied to wrap Service D with a standardized service contract that is in compliance with the design standards used in Service Inventory A.

The Containerization pattern can be applied to establish an environment for Service A to perform its processing autonomously. This gives Service A the flexibility to provide Service Consumer A with response messages consistently. The Asynchronous Queuing pattern can be applied so that a central messaging queue is positioned between Service A and Service B, between Service A and Service C, and between Service A and Service D. The Data Model Transformation and Protocol Bridging patterns can be applied to enable communication between Service A and Service B and between Service A and Service C.

The Asynchronous Queuing pattern can be applied to position a message queue between Service A and Service B, between Service A and Service C, and between Service A and Service D. Additionally, a separate messaging queue is positioned between Service A and Service Consumer A. The Data Model Transformation and Protocol Bridging patterns can be applied to enable communication between Service A and Service B, between Service A and Service C, and between Service A and Service D. The Redundant Implementation pattern can be applied so that a copy of Service D is brought in-house. The Legacy Wrapper pattern can be further applied to wrap Service D with a standardized service contract that is in compliance with the design standards used in Service Inventory B.

NO.13

Service A is an entity service that provides a set of generic and reusable service capabilities. In order to carry out the functionality of any one of its service capabilities, Service A is required to compose Service B (1) and Service C (2), and Service A is required to access Database A (3), Database B (4), and Database C (5). These three databases are shared by other applications within the IT enterprise.
All of service capabilities provided by Service A are synchronous, which means that for each request a service consumer makes, Service A is required to issue a response message after all of the processing has completed.
Service A is one of many entity services that reside In a highly normalized service Inventory. Because Service A provides agnostic logic, it is heavily reused and is currently part of many service compositions.
You are told that Service A has recently become unstable and unreliable. The problem has been traced to two issues with the current service architecture. First, Service B, which Is also an entity service, is being increasingly reused and has itself become unstable and unreliable. When Service B fails, the failure is carried over to Service A. Secondly, shared Database B has a complex data model. Some of the queries issued by Service A to shared Database B can take a very long time to complete.
What steps can be taken to solve these problems without compromising the normalization of the service inventory?

The Redundant Implementation pattern can be applied to Service A, thereby making duplicate deployments of the service available. This way, when one implementation of Service A is too busy, another implementation can be accessed by service consumers instead. The Service Data Replicationpattern can be applied to establish a dedicated database that contains an exact copy of the data from shared Database B that is required by Service A.

The Redundant Implementation pattern can be applied to Service B, thereby making duplicate deployments of the service available. This way, when one implementation of Service B is too busy, another implementation can be accessed by Service A instead. The Data Model Transformation pattern can be applied to establish a dedicated database that contains an exact copy of the data from shared Database B that is required by Service A.

The Redundant Implementation pattern can be applied to Service B, thereby making duplicate deployments of the service available. This way, when one implementation of Service B is too busy, another implementation can be accessed by Service A instead. The Service Data Replication pattern can be applied to establish a dedicated database that contains a copy of the data from shared Database B that is required by Service A. The replicated database is designed with an optimized data model to improve query execution performance.

The Redundant Implementation pattern can be applied to Service A, thereby making duplicate deployments of the service available. This way, when one implementation of Service A is too busy, another implementation can be accessed by service consumers instead. The Service Statelessness principle can be applied with the help of the State Repository pattern In order to establish a state database that Service A can use to defer state data it may be required to hold for extended periods, thereby improving its availability and scalability.

NO.14

Service Consumer A sends Service A a message containing a business document (1). The business document is received by Component A, which keeps the business document in memory and forwards a copy to Component B (3). Component B first writes portions of the business document to Database A (4). Component B then writes the entire business document to Database B and uses some of the data values from the business document as query parameters to retrieve new data from Database B (5).
Next, Component B returns the new date* back to Component A (6), which merges it together with the original business document it has been keeping in memory and then writes the combined data to Database C (7). The Service A service capability invoked by Service Consumer A requires a synchronousrequest-response data exchange. Therefore, based on the outcome of the last database update, Service A returns a message with a success or failure code back to Service Consumer A (8).
Databases A and B are shared, and Database C is dedicated to the Service A service architecture.
There are several problems with this architecture. The business document that Component A is required to keep in memory (while it waits for Component B to complete its processing) can be very large. The amount of runtime resources Service A uses to keep this data in memory can decrease the overall performance of all service instances, especially when it is concurrently invoked by multiple service consumers. Additionally, Service A can take a long time to respond back to Service Consumer A because Database A is a shared database that sometimes takes a long time to respond to Component B. Currently, Service Consumer A will wait for up to 30 seconds for a response, after which it will assume the request to Service A has failed and any subsequent response messages from Service A will be rejected.
What steps can be taken to solve these problems?

The Service Statelessness principle can be applied together with the State Repository pattern to establish a state database to which Component A can defer the business document data while it waits for a response from Component B. The Service Autonomy principle can be applied together with the Service Abstraction principle, the Legacy Wrapper pattern, and the Service Fagade pattern in order to isolate Database A so that it is encapsulated by a separate wrapper utility service and to hide the Database A implementation from Service A and to position a fagade component between Component B and the new wrapper service. This fagade component will be responsible for compensating the unpredictable behavior of Database A.

None of the above.

NO.15

The Client and Vendor services are agnostic services that are both currently part of multiple service compositions. As a result, these services are sometimes subjected to concurrent access by multiple service consumers.
The Client service primarily provides data access logic to a client database but also coordinates with other services to determine a clients credit rating. The Vendor service provides some data access logic but can also generate various dynamic reports based on specialized business requirements.
After reviewing historical statistics about the runtime activity of the two services, it is discovered that the Client service is serving an ever-increasing number of service consumers. It is regularly timing out, which in turn increases its call rate as service consumers retry their requests. The Vendor serviceoccasionally has difficulty meeting its service-level agreement (SLA) and when this occurs, penalties are assessed.
Recently, the custodian of the Client service was notified that the Client service will be made available to new service consumers external to its service inventory. The Client service will be providing free credit rating scores to any service consumer that connects to the service via the Internet. The Vendor service will remain internal to the service inventory and will not be exposed to external access.
Which of the following statements describes a solution that addresses these issues and requirements?

The API Gateway pattern, together with the Inventory Endpoint pattern, can be applied to the service inventory to establish an inventory endpoint service and an intermediary layer of processing that will be accessed by external service consumers and that will interact with the Client service to process external service consumer requests. The Redundant Implementation pattern can be applied to both the Client and Vendor services to increase their availability and scalability.

The Official Endpoint pattern can be applied to the Client service to establish a managed endpoint for consumption by service consumers external to the service inventory. The Concurrent Contracts pattern can be applied to the Vendor service, enabling it to connect with alternative Client service implementation, should the first attempt to connect fail.

The State Repository pattern can be applied to the Client and Vendor services to establish a central statement management database that can be used to overcome runtime performance problems. The Official Endpoint pattern can be further applied to increase the availability and scalability of the Client service for service consumers external to the service inventory.

The Microservice Deployment pattern is applied to the Client service to improve its autonomy and responsiveness to a greater range of service consumers. The Containerization pattern is applied to the Vendor service to establish a managed environment with a high degree of isolation for its report-related processing. The Endpoint Redirection pattern is further applied to ensure that request messages from service consumers outside of the service inventory are redirected away from the Client service.

NO.16 Refer to Exhibit.

Service A is a SOAP-based Web service with a functional context dedicated to invoice-related processing. Service B is a REST-based utility service that provides generic data access to a database.
In this service composition architecture, Service Consumer A sends a SOAP message containing an invoice XML document to Service A (1). Service A then sends the invoice XML document to Service B (2), which then writes the invoice document to a database (3).
The data model used by Service Consumer A to represent the invoice document is based on XML Schema A.
The service contract of Service A is designed to accept invoice documents based on XML Schema B. The service contract for Service B is designed to accept invoice documents based on XML Schema A. The database to which Service B needs to write the invoice record only accepts entire business documents in a proprietary Comma Separated Value (CSV) format.
Due to the incompatibility of the XML schemas used by the services, the sending of the invoice document from Service Consumer A through to Service B cannot be accomplished using the services as they currently exist. Assuming that the Contract Centralization pattern is being applied and that the Logic Centralization pattern is not being applied, what steps can be taken to enable the sending of the invoice document from Service Consumer A to the database without adding logic that will increase the runtime performance requirements?

Service Consumer A can be redesigned to use XML Schema B so that the SOAP message it sends is compliant with the service contract of Service A.
The Data Model Transformation pattern can then be applied to transform the SOAP message sent by Service A so that it conforms to the XML Schema A used by Service B. The Standardized Service Contract principle must then be applied to Service B and Service Consumer A so that the invoice XML document is optimized to avoid unnecessary validation.

The service composition can be redesigned so that Service Consumer A sends the invoice document directly to Service B after the specialized invoice processing logic from Service A is copied to Service B.
Because Service Consumer A and Service B use XML Schema A, the need for transformation logic is avoided. This naturally applies the Service Loose Coupling principle because Service Consumer A is not required to send the invoice document In a format that is compliant with the database used by Service B.

Service Consumer A can be redesigned to write the invoice document directly to the database. This reduces performance requirements by avoiding the involvement of Service A and Service B.
It further supports the application of the Service Loose Coupling principle by ensuring that Service Consumer A contains data access logic that couples it directly to the database.

The service composition can be redesigned so that Service Consumer A sends the invoice document directly to Service B.
Because Service Consumer A and Service B use XML Schema A, the need for transformation logic is avoided. This naturally applies the Logic Centralization pattern because Service Consumer A is not required to send the invoice document In a format that is compliant with the database used by Service B.

NO.17

Service Consumer A and Service A reside in Service Inventory A. Service B and Service C reside in Service Inventory B. Service D is a public service that can be openly accessed via the World Wide Web. The service is also available for purchase so that it can be deployed independently within IT enterprises. Due to the rigorous application of the Service Abstraction principle within Service Inventory B, the only information that is made available about Service B and Service C are the published service contracts. For Service D, the service contract plus a service level agreement (SLA) are made available. The SLA indicates that Service D has a planned outage every night from 11:00pm to midnight.
You are an architect with a project team that is building services for Service Inventory A. You are told that the owners of Service Inventory A and Service Inventory B are not generally cooperative or communicative.
Cross-inventory service composition is tolerated, but not directly supported. As a result, no SLAs for Service B and Service C are available and you have no knowledge about how available these services are. Based on the service contracts you can determine that the services in Service Inventory B use different data models and a different transport protocol than the services in Service Inventory A. Furthermore, recent testing results have shown that the performance of Service D is highly unpredictable due to the heavy amount of concurrent access it receives from service consumers from other organizations. You are also told that there is a concern over how long Service Consumer A will need to remain stateful while waiting for a response from Service A.
What steps can be taken to solve these problems?

NO.18

The architecture for Service A displayed in the figure shows how the core logic of Service A has expanded over time to connect to a database and a proprietary legacy system (1), and to support two separate service contracts (2) that are accessed by different service consumers.
The service contracts are fully decoupled from the service logic. The service logic is therefore coupled to the service contracts and to the underlying implementation resources (the database and the legacy system).
Service A currently has three service consumers. Service Consumer A and Service Consumer B access Service A’s two service contracts (3, 4). Service Consumer C bypasses the service contracts and accesses the service logic directly (5).
You are told that the database and legacy system that are currently being used by Service A are being replaced with different products. The two service contracts are completely decoupled from the core service logic, but there is still a concern that the introduction of the new products will cause the core service logic to behave differently than before.
What steps can be taken to change the Service A architecture in preparation for the introduction of the new products so that the impact on Service Consumers A and B is minimized? What further step can be taken to avoid consumer-to-implementation coupling with Service Consumer C?

The Service Fagade pattern can be applied to position fagade components between the core service logic and Service Consumers A and B. These fagade components will be designed to regulate the behavior of Service A. The Service Abstraction principle can be applied to hide the implementation details of the core service logic of Service A, thereby shielding this logic from changes to the implementation. The Schema Centralization pattern can be applied to force Service Consumer C to access Service A via one of its existing service contracts.

A third service contract can be added together with the application of the Contract Centralization pattern. This will force Service Consumer C to access Service A via the new service contract. The Service Fagade pattern can be applied to position a fagade component between the new service contract and Service Consumer C in order to regulate the behavior of Service A. The Service Abstraction principle can be applied to hide the implementation details of Service A so that no future service consumers are designed to access any of Service A’s underlying resources directly.

The Service Fagade pattern can be applied to position fagade components between the core service logic and the two service contracts. These fagade components will be designed to regulate the behavior of Service A. The Service Loose Coupling principle can be applied to avoid negative forms of coupling.

The Service Fagade pattern can be applied to position fagade components between the core service logic and the implementation resources (the database and the legacy system). These fagade components will be designed to insulate the core service logic of Service A from the changes in the underlying implementation resources. The Schema Centralization and Endpoint Redirection patterns can also be applied to force Service Consumer C to access Service A via one of its existing service contracts.

NO.19

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?

One of the invoice-related services needs to be chosen as the official service providing invoice data access capabilities. Service Consumers A, B, and C then need to be redesigned to only access the chosen invoice-related service. Because Service Consumer D does not rely on an invoice-related service, it is not affected by the Official Endpoint pattern and can continue to access the accounting database directly. The Service Abstraction principle can be further applied to hide the existence of the shared accounting database and other implementation details from current and future service consumers.

One of the invoice-related services needs to be chosen as the official service providing invoice data access capabilities and logic from the other two services needs to be moved to execute within the context of the official Invoice service. Service Consumers A, B, and C then need to be redesigned to only access the chosen invoice-related service. Service Consumer D also needs to be redesigned to not access the shared accounting database directly, but to also perform its data access by interacting with the official invoice-related service. The Service Abstraction principle can be further applied to hide the existence of the shared accounting database and other implementation details from current and future service consumers.

Because Service Consumers A, B, and C are already carrying out their data access via published contracts, they are not affected by the Official Endpoint pattern. Service Consumer D needs to be redesigned so that it does not access the shared accounting database directly, but instead performs its data access by interacting with the official invoice-related service. The Service Abstraction principle can be further applied to hide the existence of the shared accounting database and other implementation details from current and future service consumers.

One of the invoice-related services needs to be chosen as the official service providing invoice data access capabilities. Because Service Consumer D does not rely on an invoice-related service, it is not affected by the Official Endpoint pattern and can continue to access the accounting database directly.
The Service Loose Coupling principle can be further applied to decouple Service Consumers A, B, and C from the shared accounting database and other implementation details.

NO.20

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 A. Service B resides in Service Inventory B.
You are told that the services in Service Inventory A were designed with service contracts that are based on different design standards and technologies than the services In Service Inventory B. As a result,Service A is a SOAP-based Web service and Service B Is a REST service that exchanges JSON-formatted messages.
Therefore, Service A and Service B cannot currently communicate. Furthermore, Service C is an agnostic service that is heavily accessed by many concurrent service consumers. Service C frequently reaches its usage thresholds, during which it is not available and messages sent to it are not received.
What steps can be taken to solve these problems?

The Data Model Transformation pattern can be applied by establishing an intermediate processing layer between Service A and Service B that can transform a message from one data model to another at runtime. The Intermediate Routing and Service Agent patterns can be applied so that when Service B sends a response message, a service agent can intercept the message and, based on its contents, either forward the message to Service A or route the message to Service C. The Service Autonomy principle can be further applied to Service C together with the Redundant Implementation pattern to help establish a more reliable and scalable service architecture.

The Data Format Transformation pattern can be applied by establishing an intermediate processing layer between Service A and Service B that can transform a message from one data format to another at runtime. The Asynchronous Queuing pattern can be applied to establish an intermediate queue between Service A and Service C so that when Service A needs to send a message to Service C, the queue will store the message and retransmit it to Service C until it is successfully delivered. The Service Autonomy principle can be further applied to Service C together with the Redundant Implementation pattern to help establish a more reliable and scalable service architecture.

The Data Model Transformation pattern can be applied by establishing an intermediate processing layer between Service A and Service B that can transform a message from one data model to another at runtime. The Intermediate Routing and Service Agent patterns can be applied so that when Service B sends a response message, a service agent can intercept the message and, based on its contents, either forward the message to Service A or route the message to Service C. The Service Statelessness principle can be applied with the help of the State Repository pattern so that Service A can write the code value data to a state database while it is waiting for Service B to respond.

The Data Format Transformation pattern can be applied by establishing an intermediate processing layer between Service A and Service B that can transform a message from one data format to another at runtime. The Asynchronous Queuing pattern can be applied to establish an intermediate queue between Service A and Service B so that when Service A needs to send a message to Service B, the queue will store the message and retransmit it to Service B until it is successfully delivered. The Service Reusability principle can be further applied to Service C together with the Redundant Implementation pattern to help establish a more reusable and scalable service architecture.

NO.21

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 A. Service B and Service C are located in Service Inventory B.
You are told that In this service composition architecture, all four services are exchanging invoice-related data in an XML format. However, the services in Service Inventory A are standardized to use a different XML schema for invoice data than the services in Service Inventory B. Also, Database A can only accept data in the Comma Separated Value (CSV) format and therefore cannot accept XML-formatted data. Database B only accepts XML-formatted data. However, it is a legacy database that uses a proprietary XML schema to represent invoice data that is different from the XML schema used by services in Service Inventory A or Service Inventory B.
What steps can be taken to enable the planned data exchange between these four services?

The Data Model Transformation pattern can be applied so that data model transformation logic is positioned between Service A and Service B, between Service C and Service D, and between the Service D logic and Database B. The Data Format Transformation pattern can be applied so that data format transformation logic is positioned between Service A and Service C, and between the Service B logic and Database A.

The Protocol Bridging pattern can be applied so that protocol conversion logic is positioned between the Service B logic and Database A. The Data Format Transformation pattern can be applied so that data format transformation logic is positioned 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.

The Data Model Transformation pattern can be applied so that data model transformation logic is positioned between Service A and Service B, between Service A and Service C, between Service C andService D, and between the Service D logic and Database B. The Data Format Transformation pattern can be applied so that data format transformation logic is positioned between the Service B logic and Database A.

The Protocol Bridging pattern can be applied so that protocol conversion logic is positioned between Service A and Service B, between Service A and Service C, and between Service C and Service D. The Data Format Transformation pattern can be applied so that data format transformation logic is positioned between the Service B logic and Database A and between the Service D logic and Database B

NO.22 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?

One of the invoice-related services needs to be chosen as the official service providing invoice data access capabilities. Because Service Consumer D does not rely on an invoice-related service, it is not affected by the Official Endpoint pattern and can continue to access the accounting database directly. The Service Loose Coupling principle can be further applied to decouple Service Consumers A, B, and C from the shared accounting database and other implementation details.

NO.23

Service A is a SOAP-based Web service with a functional context dedicated to invoice-related processing.
Service B is a REST-based utility service that provides generic data access to a database.
In this service composition architecture, Service Consumer A sends a SOAP message containing an invoice XML document to Service A (1). Service A then sends the invoice XML document to Service B (2), which then writes the invoice document to a database (3).
The data model used by Service Consumer A to represent the invoice document is based on XML Schema A.
The service contract of Service A is designed to accept invoice documents based on XML Schema B. The service contract for Service B is designed to accept invoice documents based on XML Schema A. The database to which Service B needs to write the invoice record only accepts entire business documents in a proprietary Comma Separated Value (CSV) format.
Due to the incompatibility of the XML schemas used by the services, the sending of the invoice document from Service Consumer A through to Service B cannot be accomplished using the services as they currently exist. Assuming that the Contract Centralization pattern is being applied and that the Logic Centralization pattern is not being applied, what steps can be taken to enable the sending of the invoice document from Service Consumer A to the database without adding logic that will increase the runtime performance requirements?

Service Consumer A can be redesigned to use XML Schema B so that the SOAP message it sends is compliant with the service contract of Service A. The Data Model Transformation pattern can then be applied to transform the SOAP message sent by Service A so that it conforms to the XML Schema A used by Service B. The Standardized Service Contract principle must then be applied to Service B and Service Consumer A so that the invoice XML document is optimized to avoid unnecessary validation.

Because Service Consumer A and Service B use XML Schema A, the need for transformation logic is avoided. This naturally applies the Service Loose Coupling principle because Service Consumer A is not required to send the invoice document In a format that is compliant with the database used by Service B.

Service Consumer A can be redesigned to write the invoice document directly to the database. This reduces performance requirements by avoiding the involvement of Service A and Service B. It further supports the application of the Service Loose Coupling principle by ensuring that Service Consumer A contains data access logic that couples it directly to the database.

The service composition can be redesigned so that Service Consumer A sends the invoice document directly to Service B. Because Service Consumer A and Service B use XML Schema A, the need for transformation logic is avoided. This naturally applies the Logic Centralization pattern because Service Consumer A is not required to send the invoice document In a format that is compliant with the database used by Service B.

Another important area covered in the SOA S90.08B exam is service governance. This is a critical aspect of SOA, as it involves the management of services throughout their lifecycle. S90.08B exam covers topics such as service versioning, service contracts, and service registries, which are all essential components of service governance. By mastering these concepts, individuals can ensure that their SOA systems are well-managed and maintainable.

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