* If you need to scale a JMS provider/ message broker, - add nodes to scale it horizontally or - add memory to scale it vertically
* Cons of adding another JMS provider/ message broker: - adds cost. - adds complexity to use two JMS brokers - adds Operational overhead if we use two brokers, say, ActiveMQ and IBM MQ
* So Two options that mention to use two brokers are not best choice. * It's mentioned that "The Fulfillment microservice consumes Order messages, fulfills the order described therein, and then publishes an OrderFulfilled message. Each OrderFulfilled message can be consumed by any interested Mule application."
- When you publish a message on a topic, it goes to all the subscribers who are interested - so zero to many subscribers will receive a copy of the message.
- When you send a message on a queue, it will be received by exactly one consumer. * As we need multiple consumers to consume the message below option is not valid choice: "Order messages are sent to an Anypoint MQ exchange. OrderFulfilled messages are sent to an Anypoint MQ queue.
Both microservices interact with Anypoint MQ as the message broker, which must therefore scale to support the load of both microservices" * Order messages are only consumed by one Mule application, the Fulfillment microservice, so we will publish it on queue and OrderFulfilled message can be consumed by any interested Mule application so it need to be published on Topic using same broker.
* Correct:

Correct answer is Depending on the Listener operation configuration, either all messages are consumed by ONLY the primary cluster node or else EACH message is consumed by ANY ONE cluster node For applications running in clusters, you have to keep in mind the concept of primary node and how the connector will behave. When running in a cluster, the JMS listener default behavior will be to receive messages only in the primary node, no matter what kind of destination you are consuming from. In case of consuming messages from a Queue, you'll want to change this configuration to receive messages in all the nodes of the cluster, not just the primary.
This can be done with the primaryNodeOnly parameter:
<jms:listener config-ref="config" destination="${inputQueue}" primaryNodeOnly="false"/>

As the question says that data needs to be sent across multiple sftp serves , we cannot use non-repeatable streams. The non-repeatable strategy disables repeatable streams, which enables you to read an input stream only once.
You cant use in memory storage because with 0.2 vcore you will get only 1 GB of heap memory. Hence application will error out for file more than 1 GB.
Hence the correct option is file base repeatable stream

* If we store Correlation id value in step 1 as Mule event variables/attributes, the values will be cleared after server restart and we want system to be fault tolerant.
* The Correlation ID value in Step 1 should be stored in a persistent object store.
* We don't need to store Correlation ID value in Step 3 to persistent object store. We can store it but as we also need to make application performant. We can avoid this step of accessing persistent object store.
* Accessing persistent object stores slow down the performance as persistent object stores are by default stored in shared file systems.
* As the SOAP service is idempotent in nature. In case of any failures , using this Correlation ID saved in first step we can make call to SOAP service and validate the Correlation ID.
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Additional Information:
* Competing Consumers are multiple consumers that are all created to receive messages from a single Point-to-Point Channel. When the channel delivers a message, any of the consumers could potentially receive it. The messaging system's implementation determines which consumer actually receives the message, but in effect the consumers compete with each other to be the receiver. Once a consumer receives a message, it can delegate to the rest of its application to help process the message.

* In case you are unaware about term idempotent re is more info:
Idempotent operations means their result will always same no matter how many times these operations are invoked.

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