MCPA-LEVEL1 questions and answers

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.

The remaining capacity allowed by the API implementation.
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>> Reference:
https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling-sla-based-policies#response-headers

Convince the development team of the product API to adopt the API data model of the Order API such that integration logic of the Order API can work with one consistent internal data model
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Key details to note from the given scenario:
>> Power relationship between Order API and Product API is customer/supplier So, as per below rules of "Power Relationships", the caller (in this case Order API) would request for features to the called (Product API team) and the Product API team would need to accomodate those requests.

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-2019 (https://help.mulesoft.com/s/article/On-premise-Runtimes-Appear-Disconnected-in-Runtime-Manager-May-29th-2018)

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Create API Notebooks and Include them in the relevant Anypoint exchange entries
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>> 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

When development is already organized into several independent initiatives or groups
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>> It would require lot of process effort in an organization to have a single C4E team coordinating with multiple already organized development teams which are into several independent initiatives. A single C4E works well with different teams having at least a common initiative. So, in this scenario, federated C4E works well instead of centralized C4E.

Create a bounded-context model for the system layer to closely match the backend data model, and add an anti-corruption layer to let the different bounded contexts cooperate across the system and process layers *****************************************

>> Canonical models are not an option here as the organization has already put in efforts and created bounded-context models for Experience and Process APIs. >> Anti-corruption layers for ALL APIs is
unnecessary and invalid because it is mentioned that experience and process APIs share same bounded- context model. It is just the System layer APIs that need to choose their approach now. >> So, having an
anti-corruption layer just between the process and system layers will work well. Also to speed up the approach, system APIs can mimic the backend system data model.

Search Anypoint exchange for a suitable existing fallback API, and then implement invocations to this fallback API in addition to the order API ***************************************** >> It is not ideal and good
approach, until unless there is a pre-approved agreement with the API clients that they will receive a HTTP 3xx temporary redirect status code and they have to implement fallback logic their side to call another API.
>> Creating separate entry of same Order API in API manager would just create an another instance of it on top of same API implementation. So, it does NO GOOD by using clone od same API as a fallback API.
Fallback API should be ideally a different API implementation that is not same as primary one.
>> There is NO option currently provided by Anypoint HTTP Connector that allows us to invoke a fallback API when we receive certain HTTP status codes in response. The only statement TRUE in the given options is to Search Anypoint exchange for a suitable existing fallback API, and then implement invocations to this fallback API in addition to the order API.

When the response time of API invocations exceeds a threshold *****************************************
>> Alerts can be setup for all the given options using the default Anypoint Platform functionality
>> However, the question insists on an alert whose conditions depend on the end-to-end request processing of the API implementation. >> Alert w.r.t "Response Times" is the only one which requires end-
to-end request processing of API implementation in order to determine if the threshold is exceeded or not.
References:
https://docs.mulesoft.com/api-manager/2.x/using-api-alerts

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.

4.0.0
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As per semver.org semantic versioning specification: Given a version number MAJOR.MINOR.PATCH, increment the:
- MAJOR version when you make incompatible API changes.
- MINOR version when you add functionality in a backwards compatible manner.
- PATCH version when you make backwards compatible bug fixes. As per the scenario given in the question, the API implementation is completely changing its behavior. Although the format of the time is still being maintained as hh:mm:ss and there is no change in schema w.r.t format, the API will start functioning different after this change as the times are going to come completely different. Example: Before the change, say, time is going as 09:00:00 representing the PST. Now on, after the change, the same time
will go as 18:00:00 as Central European Summer Time is 9 hours ahead of Pacific Time. >> This may lead to some uncertain behavior on API clients depending on how they are handling the times in the API response. All the API clients need to be informed that the API functionality is going to change and will return in CEST format. So, this considered as a MAJOR change and the version of API for this new change would be 4.0.0

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.

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>> 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.

Apply a JSON threat protection policy to all APIs to detect potential threat vectors
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>> Usually, if the APIs are designed and developed for specific consumers (known consumers/customers) then we would IP Whitelist the same to ensure that traffic only comes from them. >> However, as this
scenario states that the APIs are publicly available and being used by so many mobile and web applications, it is NOT possible to identify and blacklist all possible bad actors.
>> So, JSON threat protection policy is the best chance to prevent any bad JSON payloads from such bad
actors.

The number of API specifications in RAML or OAS format published to Anypoint Exchange
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>> The success of C4E always depends on their contribution to the number of reusable assets that they have helped to build and publish to Anypoint Exchange. >> It is NOT due to any factors w.r.t # of outages,
Manual vs CI/CD deployments or Publicly accessible HTTP endpoints
>> Anypoint Platform APIs helps us to quickly run and get the number of published RAML/OAS assets to Anypoint Exchange. This clearly depicts how successful a C4E team is based on number of returned assets in the response.
References:
https://help.mulesoft.com/s/question/0D52T00004mXSTUSA4/how-should-a-
company-measure-c4e-success