Easily To Pass New SOA S90.08B Dumps with 17 Questions [Q10-Q27]

NO.10

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.11 Refer to Exhibit.

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 Messaging patterns 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 sends a message to Service A (1), which then forwards the message to Service B (2). Service B forwards the message to Service C (3), which finally forwards the message to Service D (4). However, Services A, B and C each contain logic that reads the contents of the message to determine what intermediate processing to perform and which service to forward the message to. As a result, what is shown in the diagram is only one of several possible runtime scenarios.
Currently, this service composition architecture is performing adequately, despite the number of services that can be involved in the transmission of one message. However, you are told that new logic is being added to Service A that will require it to compose one other service to retrieve new data at runtime that Service A will need access to in order to determine where to forward the message to. The involvement of the additional service will make the service composition too large and slow.
What steps can be taken to improve the service composition architecture while still accommodating the new requirements and avoiding an increase in the amount of service composition members?

The Service Instance Routing pattern can be applied to introduce a Routing service to provide a centralized service to contain routing-related business rules. This new Routing service can be accessed by Service A and Service C so they can determine where to forward messages to at runtime. The Service Reusability principle can be further applied to ensure that the logic in all remaining services is designed to be multi-purpose and reusable.

The Asynchronous Queuing pattern can be applied together with a Routing service that is invoked by messages read from a messaging queue. This new Routing service can replace Service B and can be accessed by Service A and Service C so they can determine where to forward messages to at runtime. The Service Loose Coupling principle can be further applied to ensure that the new Routing service remains decoupled from other services so that it can perform its routing functions independently from service contract invocation.

The Intermediate Routing pattern can be applied together with the Service Agent pattern by removing Service B or Service C from the service composition and replacing it with a service agent capable of intercepting and forwarding the message at runtime based on pre-defined routing logic. The Service Discoverability principle can be further applied to ensure that Service A can be found by any future service consumers.

The Intermediate Routing pattern can be applied together with the Service Agent pattern to establish a service agent capable of intercepting and forwarding the message at runtime based on pre-defined routing logic. The Service Composability principle can be further applied to ensure that all services are designed as effective service composition participants.

NO.13 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 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.14

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.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

Services A, B, and C are non-agnostic task services. Service A and Service B use the same shared state database to defer their state data at runtime.
An assessment of the three services reveals that each contains some agnostic logic that cannot be made available for reuse because it is bundled together with non-agnostic logic.
The assessment also determines that because Service A, Service B and the shared state database are each located in physically separate environments, the remote communication required for Service A and Service B to interact with the shared state database is causing an unreasonable decrease in runtime performance.
How can the application of the Orchestration pattern improve this architecture?

The application of the Orchestration pattern will result in an environment whereby the Official Endpoint, State Repository, and Service Data Replication patterns are automatically applied, allowing the shared state database to be replicated via official service endpoints for Services A and B so that each task service can have its own dedicated state database.

The application of the Orchestration pattern will result in an environment whereby the non-agnostic logic can be cleanly separated from the agnostic logic that exists in Services A, B, and C, resulting in theneed to design new agnostic services with reuse potential assured through the application of the Service Reusability principle. The State Repository pattern, which is supported by and local to the orchestration environment, provides a central state database that can be shared by Services A and B. The local state database avoids problems with remote communication.

The application of the Orchestration pattern will result in an environment whereby the Compensating Service Transaction is automatically applied, resulting In the opportunity to create sophisticated exception logic that can be used to compensate for the performance problems caused by Services A and B having to remotely access the state database. The API Gateway and Service Broker patterns are also automatically applied, providing common transformation functions in a centralized processing layer to help overcome any disparity in the service contracts that will need to be created for the new agnostic services.

The Orchestration pattern is not applicable to this architecture because it does not support the hosting of the required state repository.

NO.17 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.18

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.19 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.20

Service A is a task service that is required to carry out a series of updates to a set of databases in order to complete a task. To perform the database updates. Service A must interact with three other services that each provides standardized data access capabilities.
Service A sends its first update request message to Service B (1), which then responds with a message containing either a success or failure code (2). Service A then sends its second update request message to Service C (3), which also responds with a message containing either a success or failure code (4). Finally, Service A sends a request message to Service D (5), which responds with its own message containing either a success or failure code (6).
Services B, C and D are agnostic services that are reused and shared by multiple service consumers. This has caused unacceptable performance degradation for the service consumers of Service A as it is taking too long to complete its overall task. You’ve been asked to enhance the service composition architecture so that Service A provides consistent and predictable runtime performance. You are furthermore notified that a new type of data will be introduced to all three databases. It is important that this data is exchanged in a standardized manner so that the data model used for the data in inter-service messages is the same.
What steps can be taken to fulfill these requirements?

The Compensating Service Transaction pattern can be applied so that exception logic is executed to notify Service A whenever the data access logic executed by Service B, C, or D takes too long. If the execution time exceeds a predefined limit, then the overall service activity is cancelled and a failure code is returned to Service A. The Schema Centralization pattern is applied to ensure that all services involved in the composition use the same schemas to represented the data consistently.

The Composition Autonomy pattern can be applied to establish an isolated environment in which redundant implementations of Services B, C and D are accessed only by Service A. The Canonical Schema pattern can be applied to ensure that the new type of data is represented by the same data model, regardless of which service sends or receives a message containing the data.

The Redundant Implementation pattern is applied to Service A, along with the Service Instance Routing pattern. This allows for multiple instances of Service A to be created across multiple physical implementations, thereby increasing scalability and availability. The Dual Protocols pattern is applied to all services to support proprietary and standardized data models.

The Service Fagade pattern is applied to all services in order to create an intermediary processing layer within each service architecture. The Content Negotiation pattern is applied so that each service fagade component within each service architecture is equipped with the logic required to defer request messages to other service instances when concurrent usage of the service is high, and to further apply the conversation logic necessary to convert proprietary data from a database into the standardized XML schema format.

NO.21

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.22

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.23

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.