Service Consumer A sends a message with a business document to Service A (1), which writes the business document to Database A (2). Service A then forwards the business document to Service B (3), which writes the business document to Database B (4).
Service B then responds to Service A with a message containing a failure or success code (5) after which Service A responds to Service Consumer A with a message containing a failure or success code (6). Upon receiving the message, Service Consumer A updates a log table in Database B (7). The log entry is comprised of the entire business document. Database A is dedicated to the Service A service architecture and Database B is a shared database.

You are told that the database updates performed by Service A and Service B must be either both successful or they cannot happen at all. The database update performed by Service Consumer A must happen after it is given the outcome of the database updates performed by Service A and Service B . Given that Service Consumer A must also update Database B as part of this service composition architecture, how is it possible to fulfill these requirements?
A. The State Repository pattern can be applied so that Service A writes the business document data to a separate state database until it receives a response message from Service B . If the response message contains a success code, Service A writes the business document to Database A. If the response contains a failure code, Service A discards the data that was written to the state database.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, each of which provides standardized data access capabilities.
Service A sends its first update request message to Service B (1), which then responds with a message containing 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 a success or failure code (4). Finally, Service A sends a request message to Service D (5), which responds with its own message containing a success or failure code (6).

You've been given a requirement that all database updates must either be completed successfully or not at all. This means that if any of the three response messages received by Service A contain a failure code, all of the updates carried out until that point must be reversed. Note that if Service A does not receive a response message back from Services B, C, or D, it must assume that a failure has occurred. How can this service composition architecture be changed to fulfill these requirements?
A. The Reliable Messaging pattern can be applied to guarantee the delivery of positive or negative acknowledgements. This way, Service A will always be informed of whether a failure condition has occurred with any of the database updates performed by Services B, C, and D. Furthermore, the Service Loose Coupling principle can be applied to ensure that the request and response messages exchanged by the services do not contain any implementation details that would indirectly couple Service A to any of the databases.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).
Services A, B, and C each contain logic that reads the content of the message and, based on this content, determines which service to forward the message to. As a result, what is shown in the Figure is 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 in order 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?
A. The Rules Centralization pattern can be applied to establish a centralized service that contains routing-related business rules. This new Rules service would replace Service B and could be accessed by Service A and Service C in order for Service A and Service C to determine where to forward a message to at runtime. The Service Composability principle can be further applied to ensure that all remaining services are designed as effective service composition participants.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 to any design standards. Therefore each of these services has a different data model for representing invoice data.
Currently each of these three services has one 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 ProcInv service are part of the same service inventory, what steps would be required to fully apply the Official Endpoint pattern?
A. 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.Service Consumer A sends a message with a business document to Service A (1), which writes the business document to Database A (2). Service A then forwards the business document to Service B (3), which writes the business document to Database B (4).
Service B then responds to Service A with a message containing a failure or success code (5) after which Service A responds to Service Consumer A with a message containing a failure or success code (6). Upon receiving the message, Service Consumer A updates a log table in Database B (7). The log entry is comprised of the entire business document.
Database A is dedicated to the Service A service architecture and Database B is a shared database.

There are two problems with this service composition architecture that you are asked to address: First, both Service Consumer A and Service B need to transform the business document data from an XML format to a proprietary Comma Separated Value (CSV) in order to write the data to Database B. This has led to redundant data format transformation logic that has been difficult to keep in synch when Database B changes. Secondly, Service A is an entity service that is being reused by several other service compositions. It has lately developed reliability problems that have caused the service to become unavailable for extended periods. What steps can be taken to solve these problems?
A. The Legacy Wrapper pattern can be applied so that data access to Database B is separated into a new wrapper utility service. This way, the Data Format Transformation pattern only needs to be applied within the logic of this new service which will expose a standardized contract that both Service Consumer A and Service B can access. The Asynchronous Queuing pattern can be applied so that messaging queues are established between Service Consumer A and Service A and between Service A and Service B . The Service Autonomy principle can be further applied to Service A in order to establish a more isolated and reliable surrounding infrastructure.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 is an entity service that primarily provides data access logic to a client database but also provides some calculation logic associated with determining a client's credit rating. The Vendor service is also an entity service that provides some data access logic but can also generate various dynamic reports.
After reviewing historical statistics about the runtime activity of the two services, it was discovered that the majority of concurrent runtime access is related to the processing of business rules. With the Client service, it is the calculation logic that is frequently required and with the Vendor service it is the dynamic reporting logic that needs to be accessed separately from the actual report generation.

Currently, due to the increasing amount of concurrent access by service consumers, the runtime performance of both the Client and Vendor services has worsened and has therefore reduced their effectiveness as service composition members. What steps can be taken to solve this problem without introducing new services?
A. The Rules Centralization pattern can be applied by extracting the business rule logic from the Client and Vendor services and placing it into a new Rules service. This will naturally improve the runtime performance of the Client and Vendor services because they will no longer be subjected to the high concurrent access of service consumers that require access to the business rules logic.Currently, due to the increasing amount of concurrent access by service consumers, the runtime performance of both the Client and Vendor services has worsened and has therefore reduced their effectiveness as service composition members. Additionally, a review of the logic of both services has revealed that some of the business rules used by the Client and Vendor services are actually the same. What steps can be taken to improve performance and reduce redundant business rule logic?
A. The Rules Centralization pattern can be applied by extracting the business rule logic from the Client and Vendor services and placing it into a new Rules service, thereby reducing the redundancy of business rules logic. The Redundant Implementation pattern can then be applied to establish a scalable Rules service that is capable of supporting concurrent access from many service consumers.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.
Depending on the nature of the service consumer request, Service A may be required to hold data it receives in memory until its underlying processing completes. This includes data it may receive from either Service A or Service B or from any of the three shared databases.
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 and several of the service consumers that access it have had to raise runtime exceptions due to these problems. What steps can be taken to solve these problems without compromising the normalization of the service inventory?
A. The Service Autonomy principle can be applied to increase the physical isolation of Service A and to reduce dependencies Service A has on external resources. In support of this, the Service Data Replication pattern can be applied in order to establish a dedicated database that contains replicated data from shared Databases A, B, and C . Furthermore, the Redundant Implementation pattern can be applied so that the logic Service A requires from Services B and C can be redundantly placed inside of Service A . This way, Service A avoids having to separately compose Services B and CService 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.
Depending on the nature of the service consumer request, Service A may be required to hold data it receives in memory until its underlying processing completes. This includes data it may receive from either Service A or Service B or from any of the three shared databases.
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?
A. 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 Replication 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 .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 in Service Inventory A. Service B and Service C are 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?
A. 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.Nowadays, the certification exams become more and more important and required by more and more enterprises when applying for a job. But how to prepare for the exam effectively? How to prepare for the exam in a short time with less efforts? How to get a ideal result and how to find the most reliable resources? Here on Vcedump.com, you will find all the answers. Vcedump.com provide not only SOA exam questions, answers and explanations but also complete assistance on your exam preparation and certification application. If you are confused on your S90-09A exam preparations and SOA certification application, do not hesitate to visit our Vcedump.com to find your solutions here.