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S90.08B Sample Questions Answers

Questions 4

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?

Options:

A.

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 servi

B.

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 Asynchron

C.

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

D.

None of the above.

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Questions 5

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?

Options:

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.

B.

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.

C.

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 databa

D.

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

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Exam Code: S90.08B
Exam Name: SOA Design & Architecture Lab with Services & Microservices
Last Update: Nov 15, 2024
Questions: 17
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