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An external API frequently invokes an Employees System API to fetch employee data from a MySQL database. The architect must design a caching strategy to query the database only when there Is an update to the Employees table or else return a cached response in order to minimize the number of redundant transactions being handled by the database.

• A. Use a Scheduler with a fixed frequency set to every hour, triggering an invalidate cache flow. Use an object-store-caching-strategy and set the expiration interval to 1 hour.
• B. Use an On Table Row operation configured with the Employees table, call invalidate cache, and hardcode the new Employees data to cache. Use an object-store-caching-strategy and set the expiration interval to 1 hour.
• C. Use an On Table Row operation configured with the Employees table and cail invalidate cache. Use an object-store-caching-strategy and the default expiration interval.
• D. Use a Scheduler with a fixed frequency set to every hour to trigger an invalidate cache flow. Use an object-store-caching-strategy and the default expiration interval.

An integration Mute application is being designed to process orders by submitting them to a backend system for offline processing. Each order will be received by the Mute application through an HTTPS POST and must be acknowledged immediately. Once acknowledged, the order will be submitted to a backend system.
Orders that cannot be successfully submitted due to rejections from the backend system will need to be processed manually (outside the backend system).
The Mule application will be deployed to a customer-hosted runtime and is able to use an existing ActiveMQ broker if needed.
The backend system has a track record of unreliability both due to minor network connectivity issues and longer outages.
What idiomatic (used for their intended purposes) combination of Mule application components and ActiveMQ queues are required to ensure automatic submission of orders to the backend system, while minimizing manual order processing?

• A. Until Successful component ActiveMQ long retry Queue ActiveMQ Dead Letter Queue for manual processing
• B. An On Error scope Non-persistent VM ActiveMQ Dead Letter Queue for manual processing
• C. An On Error scope MuleSoft Object Store ActiveMQ Dead Letter Queue for manual processing
• D. Until Successful component MuleSoft Object Store ActiveMQ is NOT needed or used

Refer to the exhibit.
A business process involves the receipt of a file from an external vendor over SFTP. The file needs to be parsed and its content processed, validated, and ultimately persisted to a database. The delivery mechanism is expected to change in the future as more vendors send similar files using other mechanisms such as file transfer or HTTP POST.
What is the most effective way to design for these requirements in order to minimize the impact of future change?

• A. Create an API that receives the file and invokes a Process API with the data contained In the file, then have the Process API process the data using a MuleSoft Batch Job and other System APIs as needed
• B. Create a Process API to receive the file and process it using a MuleSoft Batch Job while delegating the data save process to a System API
• C. Use a composite data source so files can be retrieved from various sources and delivered to a MuleSoft Batch Job for processing
• D. Use a MuleSoft Scatter-Gather and a MuleSoft Batch Job to handle the different files coming from different sources

When a Mule application using VM queues is deployed to a customer-hosted cluster or multiple CloudHub v1.
0 workers/replicas, how are messages consumed across the nodes?

• A. Round-robin, within an XA transaction
• B. Sequentially, only from the primary node
• C. In a non-deterministic way
• D. Sequentially, from a dedicated Anypoint MQ queue

An external web UI application currently accepts occasional HTTP requests from client web browsers to change (insert, update, or delete) inventory pricing information in an inventory system's database. Each inventory pricing change must be transformed and then synchronized with multiple customer experience systems in near real-time (in under 10 seconds). New customer experience systems are expected to be added in the future.
The database is used heavily and limits the number of SELECT queries that can be made to the database to 10 requests per hour per user.
What is the most scalable, idiomatic (used for its intended purpose), decoupled. reusable, and maintainable integration mechanism available to synchronize each inventory pricing change with the various customer experience systems in near real-time?

• A. Replace the external web UI application with a Mule application to accept HTTP requests from client web browsersIn the same Mule application, use a Batch Job scope to test if the database request will succeed, aggregate pricing changes within a short time window, and then update both the inventory pricing database and each customer experience system using a Parallel For Each scope
• B. Write a Mule application with a Database On Table Row event source configured for the inventory pricing database, with the ID attribute set to an appropriate database columnIn the same flow, use a Batch Job scope to publish transformed Inventory-pricing records to an Anypoint MQ queueWrite other Mule applications to subscribe to the Anypoint MQ queue, transform each received message, and then update the Mule application's corresponding customer experience system(s)
• C. Write a Mule application with a Database On Table Row event source configured for the inventory pricing database, with the watermark attribute set to an appropriate database columnIn the same now, use a Scatter-Gather to call each customer experience system's REST API with transformed inventory- pricing records
• D. Add a trigger to the inventory-pricing database table so that for each change to the inventory pricing database, a stored procedure is called that makes a REST call to a Mule applicationWrite the Mule application to publish each Mule event as a message to an Anypoint MQ exchangeWrite other Mule applications to subscribe to the Anypoint MQ exchange, transform each received message, and then update the Mule application's corresponding customer experience system(s)