The S90.08B exam, part of the SOA Certified Professional Gen 2 credential path, validates your ability to design and architect service-oriented solutions using modern microservices patterns. This exam is designed for architects and senior developers who need to demonstrate hands-on competency in translating SOA principles into real-world implementations. Arcitura Education's SOA Design & Architecture Lab with Services & Microservices provides the practical foundation required to pass this assessment. This page outlines the exam structure, study topics, and preparation strategies to help you approach S90.08B with confidence.
Use this topic map to guide your study for Arcitura Education S90.08B (SOA Design & Architecture Lab with Services & Microservices) within the SOA Certified Professional Gen 2 path.
S90.08B uses a mix of question types to assess both conceptual understanding and practical reasoning. The exam measures your ability to make sound architectural decisions under realistic constraints.
Questions progress in difficulty, moving from definition and recognition tasks to complex decision-making that mirrors actual architecture work.
Effective preparation for S90.08B requires a structured approach that maps study time to each topic domain and builds confidence through repeated practice. Allocate 4-6 weeks to cover all areas thoroughly, with emphasis on hands-on design scenarios.
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Design & Architecture with SOA, Services & Microservices and Advanced SOA Design & Architecture with Services & Microservices typically represent the largest portion of the exam, since S90.08B focuses on applied architecture skills. Microservice Technology Concepts also appears frequently, as modern implementations require hands-on knowledge of containerization and orchestration. Allocate study time proportionally to these domains.
In practice, you start with Fundamental SOA, Services & Microservices principles to define service boundaries and contracts. You then apply Microservice Technology Concepts to choose deployment platforms and communication mechanisms. Design & Architecture with SOA, Services & Microservices guides your topology and integration patterns, while Advanced SOA Design & Architecture with Services & Microservices helps you handle cross-cutting concerns like resilience and security. The SOA Design & Architecture Lab with Services & Microservices ties everything together by requiring you to design end-to-end solutions that balance all these concerns.
Hands-on experience is valuable but not required to pass. However, working through design labs that involve containerization, service communication, and deployment strategies will significantly strengthen your understanding. Prioritize labs that ask you to design service contracts, configure API gateways, and troubleshoot integration issues. These directly mirror exam scenarios and build confidence in your decision-making.
Many candidates overlook trade-offs inherent in architectural decisions, selecting "ideal" solutions without considering constraints like cost, team skill, or legacy system integration. Another frequent error is misunderstanding when to apply specific patterns; for example, choosing synchronous communication when asynchronous messaging would be more resilient. Finally, some candidates rush through scenario analysis without fully considering the business requirements or non-functional constraints presented in the question.
In your final week, stop learning new material and focus on review and practice tests. Complete at least two full-length timed practice tests to build muscle memory for pacing and decision-making under pressure. Review your weak topic areas by re-reading explanations and working through similar questions. On the day before the exam, do a light review of key terminology and patterns, then rest well. Avoid cramming, which leads to confusion and fatigue on test day.
Refer to Exhibit.
Service A, Service B, and Service C are entity services, each designed to access the same shared legacy system. Service A manages order entities, Service B manages invoice entities, and Service C manages customer entities. Service A, Service B, and Service C are REST services and are frequently reused by different service compositions. The legacy system uses a proprietary file format that Services A, B, and C need to convert to and from.
You are told that compositions involving Service A, Service B, and Service C are unnecessarily complicated due to the fact that order, invoice, and customer entitles are all related to each other. For example, an order has a customer, an invoice has an order, and so on. This results In calls to multiple services to reconstruct a complete order document. You are asked to architect a solution that will simplify the composition logic by minimizing the number of services required to support simple business functions like order management or bill payment. Additionally, you are asked to reduce the amount of redundant data transformation logic that is found in Services A, B, and C.
How will you accomplish these goals?
The Lightweight Endpoint pattern can be applied to establish lightweight capabilities that can return related entity data directly to service consumers, simplifying the composition logic by minimizing the number of services required to support simple business functions like order management or bill payment. This approach provides a standardized and simplified interface for the legacy system, reducing the complexity of the integration process with the entity services, and enabling them to focus on their core functionality.
Refer to Exhibit.
Service Consumer A and Service A reside in Service Inventory
The Asynchronous Queuing pattern is applied to position a messaging queue between Service A, Service B, Service C, Service D, and Service Consumer A. This ensures that messages can be passed between these services without having to be in a stateful mode.
The Data Model Transformation and Protocol Bridging patterns are applied to enable communication between Service A and Service B, Service A and Service C, and Service A and Service D, despite their different data models and transport protocols.
The Redundant Implementation pattern is applied to bring a copy of Service D in-house to ensure that it can be accessed locally and reduce the unpredictability of its performance.
The Legacy Wrapper pattern is applied to wrap Service D with a standardized service contract that complies with the design standards used in Service Inventory B. This is useful for service consumers who want to use Service D but do not want to change their existing applications or service contracts.
Overall, this approach provides a comprehensive solution that addresses the issues with Service A, Service B, Service C, and Service D, while maintaining compliance with the Service Abstraction principle.
Refer to Exhibit.
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 can improve this architecture by cleanly separating the non-agnostic logic from the agnostic logic, allowing the design of new agnostic services with reuse potential. 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. Additionally, the Orchestration pattern provides a central controller that can coordinate the interactions between Services A, B, and C, reducing the need for remote communication between services and improving runtime performance.
Refer to Exhibit.
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?
This approach isolates the services used by Service A, allowing it to avoid the performance degradation caused by multiple service consumers. By creating redundant implementations of Services B, C, and D that are accessed only by Service A, the Composition Autonomy pattern also ensures that Service A's runtime performance is consistent and predictable. Applying the Canonical Schema pattern ensures that the new type of data is exchanged in a standardized manner, ensuring consistent representation of the data model used for the data in inter-service messages.
Refer to Exhibit.
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
This solution addresses both issues with the current service architecture. By applying the Redundant Implementation pattern to Service B, duplicate deployments of the service are made available, ensuring that when one implementation fails, another can be accessed by Service A. Additionally, 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. This replicated database is designed with an optimized data model to improve query execution performance, ensuring that queries issued by Service A to the database can complete more quickly, improving the overall stability and reliability of Service A. By applying these patterns, the problems with Service A can be solved without compromising the normalization of the service inventory.
