MCPA-Level-1 MuleSoft Certified Platform Architect - Level 1 Questions and Answers

Explanation

Correct Answer: Spike control

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>> First things first, HTTP Caching policy is for purposes different than avoiding the backend system from overloading. So this is OUT.

>> Rate Limiting and Throttling/ Spike Control policies are designed to limit API access, but have different intentions.

>> Rate limiting protects an API by applying a hard limit on its access.

>> Throttling/ Spike Control shapes API access by smoothing spikes in traffic.

That is why, Spike Control is the right option.

Explanation

Correct Answer: By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example

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References:

https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling#response-headers

https://docs.mulesoft.com/api-manage r/2.x/rate-limiting-and-throttling-sla-based-policies#response-headers

Explanation

Correct Answer: Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the system API deployed to the DR environment

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There is one important consideration to be noted in the question which is - System API in DR environment provides only 20% of the rate limiting offered by the primary environment. So, comparitively, very less calls will be allowed into the DR environment API opposed to its primary environment. With this in mind, lets analyse what is the right and best fault-tolerant invocation strategy.

1. Invoking both the system APIs in parallel is definitely NOT a feasible approach because of the 20% limitation we have on DR environment. Calling in parallel every time would easily and quickly exhaust the rate limits on DR environment and may not give chance to genuine intermittent error scenarios to let in during the time of need.

2. Another option given is suggesting to add timeout and retry logic to process API while invoking primary environment's system API. This is good so far. However, when all retries failed, the option is suggesting to invoke the copy of process API on DR environment which is not right or recommended. Only system API is the one to be considered for fallback and not the whole process API. Process APIs usually have lot of heavy orchestration calling many other APIs which we do not want to repeat again by calling DR's process API. So this option is NOT right.

3. One more option given is suggesting to add the retry (no timeout) logic to process API to directly retry on DR environment's system API instead of retrying the primary environment system API first. This is not at all a proper fallback. A proper fallback should occur only after all retries are performed and exhausted on Primary environment first. But here, the option is suggesting to directly retry fallback API on first failure itself without trying main API. So, this option is NOT right too.

This leaves us one option which is right and best fit.

- Invoke the system API deployed to the primary environment

- Add Timeout and Retry logic on it in process API

- If it fails even after all retries, then invoke the system API deployed to the DR environment.

Explanation

Correct Answer: The CloudHub shared load balancer

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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 load-balancing 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 cost-effective is - using a CloudHub Shared Load Balancer.

Explanation

Correct Answer: A CloudHub worker fails with an out-of-memory exception.

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>> An AWS Region itself going down will definitely result in an outage as it does not matter how many workers are assigned to the Mule App as all of those in that region will go down. This is a complete downtime and outage.

>> Extended outage of API manager during initial deployment of API implementation will of course cause issues in proper application startup itself as the API Autodiscovery might fail or API policy templates and polices may not be downloaded to embed at the time of applicaiton startup etc... there are many reasons that could cause issues.

>> A network outage onpremises would of course cause the Order Management System not accessible and it does not matter how many workers are assigned to the app they all will fail and cause outage for sure.

The only option that does NOT result in a service outage is if a cloudhub worker fails with an out-of-memory exception. Even if a worker fails and goes down, there are still other workers to handle the requests and keep the API UP and Running. So, this is the right answer.

Explanation

Correct Answer: The client ID and secret obtained from Anypoint Exchange for the API instance in the STAGING environment

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>> We CANNOT use the client ID and secret of Anypoint Platform account or any individual environments for accessing the APIs

>> As the type of policy that is enforced on the API in question is "Client ID Enforcment Policy", OAuth token based access won't work.

Right way to access the API is to use the client ID and secret obtained from Anypoint Exchange for the API instance in a particular environment we want to work on.

References:

Managing API instance Contracts on API Manager

https://docs.mulesoft.com/api-manager/1.x/request-access-to-api-task

https://docs.mulesoft.com/exchange/to-request-access

https://docs.mulesoft.com/api-manager/2.x/policy-mule3-clie nt-id-based-policies

Explanation

Correct Answer: Allow System APIs to return data that is NOT currently required by the identified Process or Experience APIs.

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>> All customizations for the end-user application should be handled in "Experience API" only. Not in Process API

>> We should use tiered approach but NOT always by creating exactly one API for each of the 3 layers. Experience APIs might be one but Process APIs and System APIs are often more than one. System APIs for sure will be more than one all the time as they are the smallest modular APIs built in front of end systems.

>> Process APIs can call System APIs as well as other Process APIs. There is no such anti-design pattern in API-Led connectivity saying Process APIs should not call other Process APIs.

So, the right answer in the given set of options that makes sense as per API-Led connectivity principles is to allow System APIs to return data that is NOT currently required by the identified Process or Experience APIs. This way, some future Process APIs can make use of that data from System APIs and we need NOT touch the System layer APIs again and again.

Explanation

Correct Answer: System Layer

The APIs used in an API-led approach to connectivity fall into three categories:

System APIs – these usually access the core systems of record and provide a means of insulating the user from the complexity or any changes to the underlying systems. Once built, many users, can access data without any need to learn the underlying systems and can reuse these APIs in multiple projects.

Process APIs – These APIs interact with and shape data within a single system or across systems (breaking down data silos) and are created here without a dependence on the source systems from which that data originates, as well as the target channels through which that data is delivered.

Experience APIs – Experience APIs are the means by which data can be reconfigured so that it is most easily consumed by its intended audience, all from a common data source, rather than setting up separate point-to-point integrations for each channel. An Experience API is usually created with API-first design principles where the API is designed for the specific user experience in mind.

Explanation

Correct Answer: They are typically written using MUnit to run in an embedded Mule runtime that does not require external connectivity.

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Below TWO are characteristics of Integration Tests but NOT unit tests:

>> They test the validity of input and output of source and target systems.

>> They must be triggered by an external client tool or event source.

It is NOT TRUE that Unit Tests must be run in a unit testing environment with dedicated Mule runtimes for the environment.

MuleSoft offers MUnit for writing Unit Tests and they run in an embedded Mule Runtime without needing any separate/ dedicated Runtimes to execute them. They also do NOT need any external connectivity as MUnit supports mocking via stubs.

https://dzone.com/articles/munit-framework

Explanation

Correct Answer: API implementations can run successfully in customer-hosted Mule runtimes, even when they are unable to communicate with the control plane.

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>> We CANNOT use Shared Load balancer to load balance APIs on customer hosted runtimes

>> For Hybrid deployment models, the on-premises are first connected to Runtime Manager using Runtime Manager agent. So, the connection is initiated first from On-premises to Runtime Manager. Then all control can be done from Runtime Manager.

>> Anypoint Runtime Manager CANNOT ensure automatic HA. Clusters/Server Groups etc should be configured before hand.

Only TRUE statement in the given choices is, API implementations can run successfully in customer-hosted Mule runtimes, even when they are unable to communicate with the control plane. There are several references below to justify this statement.

References:

https://docs.mulesoft.com/runtime-manager/deployment-strategies#hybrid-deployments

https://help.mulesoft.com/s/article/On-Premise-Runtimes-Disconnected-From-US-Control-Plane-June-18th-2018

https://help.mulesoft.com/s/article/Runtime-Manager-cannot-manage-On-Prem-Applications-and-Servers-from-US-Control-Plane-June-25th-2 019

https://help.mulesoft.com/s/article/On-premise-Runtimes-Appear-Disconnected-in-Runtime-Manager-May-29th-2018

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