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An organization is designing an integration solution to replicate financial transaction data from a legacy system into a data warehouse (DWH).
The DWH must contain a daily snapshot of financial transactions, to be delivered as a CSV file. Daily transaction volume exceeds tens of millions of records, with significant spikes in volume during popular shopping periods.
What is the most appropriate integration style for an integration solution that meets the organization's current requirements?
Correct answer is Batch-triggered ETL Within a Mule application, batch processing provides a construct for asynchronously processing larger-than-memory data sets that are split into individual records. Batch jobs allow for the description of a reliable process that automatically splits up source data and stores it into persistent queues, which makes it possible to process large data sets while providing reliability. In the event that the application is redeployed or Mule crashes, the job execution is able to resume at the point it stopped.
A company is designing an integration Mule application to process orders by submitting them to a back-end system for offline processing. Each order will be received by the Mule application through an HTTP5 POST and must be acknowledged immediately.
Once acknowledged the order will be submitted to a back-end system. Orders that cannot be successfully submitted due to the rejections from the back-end system will need to be processed manually (outside the banking system).
The mule application will be deployed to a customer hosted runtime and will be able to use an existing ActiveMQ broker if needed. The ActiveMQ broker is located inside the organization's firewall. The back-end system has a track record of unreliability due to both minor network connectivity issues and longer outages.
Which combination of Mule application components and ActiveMQ queues are required to ensure automatic submission of orders to the back-end system while supporting but minimizing manual order processing?
An API has been unit tested and is ready for integration testing. The API is governed by a Client ID Enforcement policy in all environments.
What must the testing team do before they can start integration testing the API in the Staging environment?
* It's mentioned that the API is governed by a Client ID Enforcement policy in all environments.
* Client ID Enforcement policy allows only authorized applications to access the deployed API implementation.
* Each authorized application is configured with credentials: client_id and client_secret.
* At runtime, authorized applications provide the credentials with each request to the API implementation.
MuleSoft Reference:https://docs.mulesoft.com/api-manager/2.x/policy-mule3-client-id-based-policies
A company is implementing a new Mule application that supports a set of critical functions driven by a rest API enabled, claims payment rules engine hosted on oracle ERP. As designed the mule application requires many data transformation operations as it performs its batch processing logic.
The company wants to leverage and reuse as many of its existing java-based capabilities (classes, objects, data model etc.) as possible
What approach should be considered when implementing required data mappings and transformations between Mule application and Oracle ERP in the new Mule application?
An organization needs to enable access to their customer data from both a mobile app and a web application, which each need access to common fields as well as certain unique fields. The data is available partially in a database and partially in a 3rd-party CRM system. What APIs should be created to best fit these design requirements?
Lets analyze the situation in regards to the different options available Option : A common Experience API but separate Process APIs Analysis : This solution will not work because having common experience layer will not help the purpose as mobile and web applications will have different set of requirements which cannot be fulfilled by single experience layer API
Option : Common Process API Analysis : This solution will not work because creating a common process API will impose limitations in terms of flexibility to customize API;s as per the requirements of different applications. It is not a recommended approach.
Option : Separate set of API's for both the applications Analysis : This goes against the principle of Anypoint API-led connectivity approach which promotes creating reusable assets. This solution may work but this is not efficient solution and creates duplicity of code.
Hence the correct answer is: Separate Experience APIs for the mobile and web app, but a common Process API that invokes separate System APIs created for the database and CRM system
Lets analyze the situation in regards to the different options available Option : A common Experience API but separate Process APIs Analysis : This solution will not work because having common experience layer will not help the purpose as mobile and web applications will have different set of requirements which cannot be fulfilled by single experience layer API
Option : Common Process API Analysis : This solution will not work because creating a common process API will impose limitations in terms of flexibility to customize API;s as per the requirements of different applications. It is not a recommended approach.
Option : Separate set of API's for both the applications Analysis : This goes against the principle of Anypoint API-led connectivity approach which promotes creating reusable assets. This solution may work but this is not efficient solution and creates duplicity of code.
Hence the correct answer is: Separate Experience APIs for the mobile and web app, but a common Process API that invokes separate System APIs created for the database and CRM system
