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A Mule application exposes an HTTPS endpoint and is deployed to three CloudHub workers that do not use static IP addresses. The Mule application expects a high volume of client requests in short time periods. What is the most cost-effective infrastructure component that should be used to serve the high volume of client requests?
A customer-hosted load balancer
The CloudHub shared load balancer
An API proxy

The CloudHub shared load balancer

Explanation: Explanation
Correct Answer: The CloudHub shared load balancer
*****************************************
The scenario in this question can be split as below:
>> There are 3 CloudHub workers (So, there are already good number of workers to
handle high volume of requests)
>> The workers are not using static IP addresses (So, one CANNOT use customer loadbalancing
solutions without static IPs)
>> Looking for most cost-effective component to load balance the client requests among
the workers.
Based on the above details given in the scenario:
>> Runtime autoscaling is NOT at all cost-effective as it incurs extra cost. Most over, there
are already 3 workers running which is a good number.
>> We cannot go for a customer-hosted load balancer as it is also NOT most cost-effective
(needs custom load balancer to maintain and licensing) and same time the Mule App is not
having Static IP Addresses which limits from going with custom load balancing.
>> An API Proxy is irrelevant there as it has no role to play w.r.t handling high volumes or
load balancing.
So, the only right option to go with and fits the purpose of scenario being most costeffective
is - using a CloudHub Shared Load Balancer

A code-centric API documentation environment should allow API consumers to investigate and execute API client source code that demonstrates invoking one or more APIs as part of representative scenarios. What is the most effective way to provide this type of code-centric API documentation environment using Anypoint Platform?
Enable mocking services for each of the relevant APIs and expose them via their Anypoint Exchange entry
Ensure the APIs are well documented through their Anypoint Exchange entries and API Consoles and share these pages with all API consumers
Create API Notebooks and include them in the relevant Anypoint Exchange entries

Create API Notebooks and include them in the relevant Anypoint Exchange entries

Explanation: Explanation
Correct Answer: Create API Notebooks and Include them in the relevant Anypoint
exchange entries
*****************************************
>> API Notebooks are the one on Anypoint Platform that enable us to provide code-centric
API documentation
: https://docs.mulesoft.com/exchange/to-use-api-notebook
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A system API has a guaranteed SLA of 100 ms per request. The system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. An upstream process API invokes the system API and the main goal of this process API is to respond to client requests in the least possible time. In what order should the system APIs be invoked, and what changes should be made in order to speed up the response time for requests from the process API?
In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment, and ONLY use the first response
In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment using a scatter-gather configured with a timeout, and then merge the responses
Invoke the system API deployed to the primary environment, and if it fails, invoke the system API deployed to the DR environment

In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment, and ONLY use the first response

Explanation: Explanation
Correct Answer: In parallel, invoke the system API deployed to the primary environment
and the system API deployed to the DR environment, and ONLY use the first response.
*****************************************
>> The API requirement in the given scenario is to respond in least possible time.
>> The option that is suggesting to first try the API in primary environment and then
fallback to API in DR environment would result in successful response but NOT in least
possible time. So, this is NOT a right choice of implementation for given requirement.
>> Another option that is suggesting to ONLY invoke API in primary environment and to
add timeout and retries may also result in successful response upon retries but NOT in
least possible time. So, this is also NOT a right choice of implementation for given
requirement.
>> One more option that is suggesting to invoke API in primary environment and API in DR
environment in parallel using Scatter-Gather would result in wrong API response as it
would return merged results and moreover, Scatter-Gather does things in parallel which is
true but still completes its scope only on finishing all routes inside it. So again, NOT a right
choice of implementation for given requirement
The Correct choice is to invoke the API in primary environment and the API in DR
environment parallelly, and using ONLY the first response received from one of them

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