SOA Design & Architecture LabはIT業界で広く認知された認定資格であり、取得すればスキルの証明として大きな強みになります。CertShikenのS90.09練習問題（40問）は専門家チームが監修し、2026年の試験内容に対応しています。

SOA S90.09 試験概要:

認定ベンダー:	Arcitura Education
試験名:	SOA設計・アーキテクチャ演習
試験番号:	S90.09（S90.09Aも同様）
関連資格:	Certified SOA Consultant Certified Microservices Architect Certified SOA Security Specialist
出題数:	40～70問
対応言語:	英語
認定の有効期間:	3年間
合格点:	70％または700点／1000点
受験料:	295米ドル
試験形式:	シナリオ設定型, ケーススタディ形式, ドラッグアンドドロップ形式, 演習課題形式, 設計課題形式
試験時間:	90～100
推奨トレーニング:	SOAスクール公式トレーニング SOACP モジュール9 学習教材セット
受験申し込み:	Pearson VUEでの試験予約 Arcitura公式試験登録
サンプル問題:
受験方法:	オンライン監督付き受験、またはPearson VUEの試験会場での受験
前提条件:	推奨事項：S90.01、S90.02、S90.03、S90.04、S90.05、S90.08の各試験への合格または同等の知識を有すること。加えてSOA設計に関する十分な実務経験があることが望ましい
公式シラバスのURL:	https://www.arcitura.com/soacp-gen-1/exams/

SOA S90.09 試験シラバストピック:

S90.09試験の疑問を解決するFAQ

SOA Design & Architecture Lab 認定 S90.09 試験問題：

問題 #1

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 A
and Service C, 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 the Service B logic and Database A.
B. None of the above.
C. The Data Model Transformation pattern can be applied so that data model
transformation 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.
D. 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.

問題 #2

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 a task service that completes an entire business task on its own without having
to compose other services. However, you have received many complaints about the
reliability of Service A . Specifically, it has three problems. First, when Component B
accesses Database A, it may not receive a response for several minutes when the
database is being accessed by other applications in the IT enterprise. Secondly, the legacy
system accessed by Component C frequently crashes and therefore becomes unavailable
for extended periods of time. Third, for Component D to respond to Component A, it must
first wait for the batch import of the files to occur. This can take several minutes during
which Service Consumer A remains stateful and consumes excessive memory. What steps
can be taken to address these three problems?

A. The Service Data Replication pattern can be applied so that Component B can access a
replicated database instead of having to access the shared Database A directly. The
Legacy Wrapper pattern can be applied so that Component C is separated into a separate
service that acts as a wrapper of the legacy system API. Next, the Asynchronous Queuing
pattern can be applied so that a messaging queue is positioned between Component A and
the new wrapper service, thereby enabling communication during times when the legacy
system is unavailable. Finally, Component D is separated into a new service and the
Event-Driven Messaging pattern is applied to establish a publisher-subscriber relationship
between this service and Component A and between Service A and Service Consumer A.
The interaction logic is redesigned as follows: Component A interacts with Component B,
the new wrapper service, and then issues a request to the new event-driven service. Upon
receiving a response triggered by the event related to the batch import, Service A responds
to Service Consumer A.
B. The Service Data Replication pattern can be applied so that Component B can access a
replicated database instead of having to access the shared Database A directly. The
Legacy Wrapper pattern can be applied so that Component C is separated into a separate
service that acts as a wrapper of the legacy system API. Next, the Reliable Messaging
pattern can be applied so that acknowledgements are issued from the new wrapper service
to Component A, thereby enabling notifying Component A during times when the legacy
system is unavailable. Finally, Component D is separated into a separate service and the
Event-Driven Messaging pattern is applied to establish a publisher-subscriber relationship
between this new service and Component A.
The interaction between Service Consumer A and Component A is then 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.
C. None of the above.
D. The Legacy Wrapper pattern can be applied so that Component B is separated to wrap
the shared database, thereby allowing Component A to interact with this new service
instead of directly interacting with the database. The Legacy Wrapper pattern can be
applied again so that Component C is separated into a separate service that acts as a
wrapper of the legacy system API. Component D can then 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 and between Service A
and Service Consumer A.
The interaction between Service Consumer A and Component A is then redesigned so that Component A issues a message back to Service Consumer A
when the event related to the batch import is triggered.

問題 #3

Service A has become increasingly difficult to maintain. Its core service logic has become
bloated and convoluted because it has been updated numerous times during which
additional functionality was added to interact with the database and the legacy system and
to support interaction with Service Consumers A and B (via the two service contracts) as
well as interaction directly with Service Consumer C.

What steps can be taken to solve these problems and to prevent them from happening
again in the future?

A. The Official Endpoint pattern can be applied to limit access to Service A to one of its two
published service contracts. The Service Loose Coupling principle can be applied so that
Service Consumer C does not negatively couple itself directly to the core service logic of
Service A . B.
The Service Facade pattern can be applied to position a Facade component
between the core service logic and the implementation resources (the database and the
legacy system) and to position a faade component between the core service logic and the
two service contracts. The Contract Centralization pattern can be applied to limit access to
Service A to one of its two published service contracts. The Service Abstraction principle
can be applied to hide the implementation details of Service A from service consumers.
B. The Service Facade pattern can be applied to position a Facade component between
the core service logic and the implementation resources (the database and the legacy
system) and to also position a Facade component between the two service contracts and
Service Consumers A and
C. None of the above.
D. The Service Faade pattern can be applied to position a Facade component between the
core service logic and the two service contracts. The Contract Centralization pattern can be
applied to limit access to Service A to one of its two published service contracts. The
Service Loose Coupling principle can be applied so that Service Consumer C does not
negatively couple itself directly to the core service logic of Service A .

問題 #4

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.
B. None of the above.
C. The Redundant Implementation pattern can be applied to the Client and Vendor
services, thereby establishing duplicate service implementations that can be accessed
when a service reaches its runtime usage threshold. The Intermediate Routing pattern can
be further applied to provide load balancing logic that can, at runtime, determine which of
the redundant service implementations is the least busy for a given service consumer
request.
D. The Rules Centralization pattern can be applied to isolate business rules logic into a
central and reusable Rules service. Additionally, the Service Abstraction principle can be
applied to hide the implementation details of new the Rules service.

解説：