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
The problem is that Service A and Service B are using different technologies and cannot communicate. Therefore, an intermediate processing layer can be established that can transform messages from one data format to another at runtime. This can be achieved using the Data Format Transformation pattern.
Additionally, Service C frequently reaches its usage thresholds and is not always available, so an Asynchronous Queuing pattern can be applied to establish an intermediate queue between Service A and Service C. This queue will store the messages sent by Service A to Service C and retransmit them until they are successfully delivered. This approach improves the reliability of the system.
Moreover, the Redundant Implementation pattern can be applied to Service C to ensure its availability and scalability, and the Service Autonomy principle can be applied to make Service C independent of other services.
Refer to Exhibit.
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 service occasionally 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?
This solution addresses the specific requirements and issues identified in the scenario. 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, which will allow for controlled and managed access to the service. The Concurrent Contracts pattern can be applied to the Vendor service, which will enable it to connect with alternative Client service implementation if the first attempt to connect fails, thereby increasing its availability and reducing the possibility of penalties being assessed due to not meeting its SLA.
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.
Refer to Exhibit.
Service A is an entity service that provides a Get capability which returns a data value that is frequently changed.
Service Consumer A invokes Service A in order to request this data value (1). For Service A to carry out this request, it must invoke Service B (2), a utility service that interacts (3, 4) with the database in which the data value is stored. Regardless of whether the data value changed, Service B returns the latest value to Service A (5), and Service A returns the latest value to Service Consumer A (6).
The data value is changed when the legacy client program updates the database (7). When this change will occur is not predictable. Note also that Service A and Service B are not always available at the same time.
Any time the data value changes, Service Consumer A needs to receive It as soon as possible. Therefore, Service Consumer A initiates the message exchange shown In the figure several times a day. When it receives the same data value as before, the response from Service A Is ignored. When Service A provides an updated data value, Service Consumer A can process it to carry out its task.
The current service composition architecture is using up too many resources due to the repeated invocation of Service A by Service Consumer A and the resulting message exchanges that occur with each invocation.
What steps can be taken to solve this problem?
This solution is the most appropriate one among the options presented. By using the Event-Driven Messaging pattern, Service A can be notified of changes to the data value without having to be invoked repeatedly by Service Consumer A, which reduces the resources required for message exchange. Asynchronous Queuing ensures that the event notification message is not lost due to the unavailability of Service A or Service B. This approach improves the efficiency of the service composition architecture.
Refer to Exhibit.
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 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. This will minimize the impact of the introduction of the new products on Service Consumers A and B since the service contracts are fully decoupled from the core service logic. 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, avoiding direct access to the core service logic and the underlying implementation resources.
