MuleSoft MCIA-Level-1 Based on Real Exam Environment

Make assets easily discoverable via a central repository

Focus project delivery efforts on custom assets that meet the specific requirements of each individual line of business

Create weekly meetings that all members of IT attend to present justification and request approval to use existing assets

Hire additional staff to meet the demand for asset creation required for approved projects and timelines

Each message is routed to ONE of the Cloudhub workers in a DETERMINSTIC round robin fashion thereby EXACTLY BALANCING messages among the cloudhub workers

Each messages routes to ONE of the available Clouhub workers in a NON- DETERMINSTIC non round-robin fashion thereby APPROXIMATELY BALANCING messages among the cloudhub workers

Each message is routed to the SAME Cloudhub worker that retrieved the file, thereby BINDING ALL messages to ONLY that ONE Cloudhub worker

Each message is duplicated to ALL of the Cloudhub workers, thereby SHARING EACH message with ALL the Cloudhub workers.

Implement eXtended Architecture (XA) transactions between the API implementations

Coordinate between the API implementations using a Saga pattern

Implement caching in each API implementation to improve performance

Implement local transactions within each API implementation

Configure each API implementation to also participate in the same eXtended Architecture (XA) transaction

Implement caching in each API implementation to improve performance

Implement local transactions in each API implementation

Coordinate between the API implementations using a Saga pattern

Apply various compensating actions depending on where a failure occurs

Implement an eXtended Architecture (XA) transaction manager in a Mule application using a Saga pattern

Connect each API implementation with the Mule application using XA transactions

Apply various compensating actions depending on where a failure occurs

Create a new metadata RAML classes in Mule from the appropriate Java objects and then perform transformations via Dataweave

From the mule application, transform via theXSLT model

Transform by calling any suitable Java class from Dataweave

Invoke any of the appropriate Java methods directly, create metadata RAML classes and then perform required transformations via Dataweave