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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 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 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.
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 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). However, Services A, B and C each contain logic that reads the contents of the message to determine what intermediate processing to perform and which service to forward the message to. As a result, what is shown in the diagram is only 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 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?
This solution addresses the issue of the service composition becoming too large and slow by introducing a new Routing service that is invoked by messages read from a messaging queue. This allows Service A and Service C to determine where to forward messages to at runtime without the need for additional services in the composition. The Service Loose Coupling principle is applied to ensure that the new Routing service remains decoupled from other services so that it can perform its routing functions independently from service contract invocation.
