An SLA for the upstream API CANNOT be provided.
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>> First thing first, the default HTTP response timeout for HTTP connector is 10000 ms (10 seconds). NOT
500 ms.
>> Mule runtime does NOT apply any such "load-dependent" timeouts. There is no such behavior currently in Mule.
>> As there is default 10000 ms time out for HTTP connector, we CANNOT always guarantee that the invocation of the downstream API will run to completion without timing out due to its unreliable SLA times.
If the response time crosses 10 seconds then the request may time out.
The main impact due to this is that a proper SLA for the upstream API CANNOT be provided.

* Understanding the Requirements:
* The business needs to transfer daily data changes from the Salesforce Account and Case objects to AWS DynamoDB in a single JSON format.
* Only a subset of attributes (5 from Account and 8 from Case) is required, so it is not necessary to include all 219 attributes of the Account object.
* Design Approach:
* A System API (SAPI) should be created for each Salesforce object (Account and Case), exposing only the required fields (5 attributes for Account and 8 for Case).
* A Process API (PAPI) can be used to aggregate and transform the data from these SAPIs, combining the 13 selected attributes from Account and Case into a single JSON structure for DynamoDB.
* Evaluating the Options:
* Option A: Mimicking all attributes in the SAPI is inefficient and unnecessary, as only 13 attributes are required.
* Option B: Replicating all attributes in DynamoDB is excessive and would result in higher storage and processing costs, which is unnecessary given the requirement for only a subset of attributes.
* Option C: Implementing an Enterprise Data Model could be useful in broader data management but is not required here, as the focus is on a lightweight integration.
* Option D (Correct Answer): Creating separate entities in SAPI for Account and Case with only the required attributes and using the PAPI to aggregate them into a single JSON is the most efficient and meets the requirements effectively.
* Conclusion:
* Option D is the best choice as it provides a lightweight, efficient design that meets the requirements by transferring only the necessary attributes and minimizing resource use.
Refer to MuleSoft's best practices for API-led connectivity and data modeling to structure SAPIs and PAPIs efficiently.

Correct answer: Data on past API invocations to help identify anomalies and usage patterns across various APIs
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API Invocation metrics provided by Anypoint Platform:
>> Does NOT provide any Return Of Investment (ROI) related information. So the option suggesting it is OUT.
>> Does NOT provide any information w.r.t how APIs are reused, whether there is effective usage of APIs or not etc...
>> Does NOT prodive any prediction information as such to help us proactively identify any future policy violations.
So, the kind of data/information we can get from such metrics is on past API invocations to help identify anomalies and usage patterns across various APIs.