MuleSoft-Platform-Architect-I Salesforce Certified MuleSoft Platform Architect 1 Exam (SU24) Questions and Answers

Explanation

Correct Answer: When server-side load-balanced TLS mutual authentication is required between API implementations and API clients

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Fact/ Memory Tip: Although there are many benefits of CloudHub Dedicated Load balancer, TWO important things that should come to ones mind for considering it are:

>> Having URL endpoints with Custom DNS names on CloudHub deployed apps

>> Configuring custom certificates for both HTTPS and Two-way (Mutual) authentication.

Coming to the options provided for this question:

>> We CANNOT use DLB to perform cross-region load balancing between separate deployments of the same Mule application.

>> We can have mapping rules to have more than one DLB URL pointing to same Mule app. But vicevera (More than one Mule app having same DLB URL) is NOT POSSIBLE

>> It is true that DLB helps to setup custom DNS names for Cloudhub deployed Mule apps but NOT true for apps deployed to Customer-hosted Mule Runtimes.

>> It is true to that we can load balance API invocations across multiple CloudHub workers using DLB but it is NOT A MUST. We can achieve the same (load balancing) using SLB (Shared Load Balancer) too. We DO NOT necessarily require DLB for achieve it.

So the only right option that fits the scenario and requires us to use DLB is when TLS mutual authentication is required between API implementations and API clients.

Explanation

Correct Answer: Configure a “Worker not responding” alert in Anypoint Runtime Manager.

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>> All the options eventually helps to generate the alert required when the application stops responding.

>> However, handling exceptions within calling API and then raising alert from API client is inappropriate and silly. There could be many API clients invoking the API implementation and it is not ideal to have this setup consistently in all of them. Not a realistic way to do.

>> Implementing a health check/ heartbeat with in the API and calling from outside to detmine the health sounds OK but needs extra setup for it and same time there are very good chances of generating false alarms when there are any intermittent network issues between external tool calling the health check API on API implementation. The API implementation itself may not have any issues but due to some other factors some false alarms may go out.

>> Creating an alert in API Manager when the API receives no requests within a specified time period would actually generate realistic alerts but even here some false alarms may go out when there are genuinely no requests from API clients.

The best and right way to achieve this requirement is to setup an alert on Runtime Manager with a condition "Worker not responding". This would generate an alert AS SOON AS the workers become unresponsive.

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Explanation

Correct Answer: Ask the Marketing Department to interact with a mocking implementation of the API using the automatically generated API Console.

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As per MuleSoft's IT Operating Model:

>> API consumers need NOT wait until the full API implementation is ready.

>> NO technical test-suites needs to be shared with end users to interact with APIs.

>> Anypoint Platform offers a mocking capability on all the published API specifications to Anypoint Exchange which also will be rich in documentation covering all details of API functionalities and working nature.

>> No needs of arranging days of workshops with end users for feedback.

API consumers can use Anypoint Exchange features on the platform and interact with the API using its mocking feature. The feedback can be shared quickly on the same to incorporate any changes.

Explanation

Correct Answer: Create reusable assets, Make them discoverable so that LOB teams can self-serve and browse the APIs, Get active feedback and usage metrics.

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Diagram, arrow Description automatically generated

Explanation

Correct Answer: At the API proxy

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>> API Policies can be enforced at two places in Mule platform.

>> One - As an Embedded Policy enforcement in the same Mule Runtime where API implementation is running.

>> Two - On an API Proxy sitting in front of the Mule Runtime where API implementation is running.

>> As the deployment scenario in the question has API Proxy involved, the policies will be enforced at the API Proxy.

Explanation

Correct Answer: At the process and system tiers

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>> Experience Layer APIs are modeled and designed exclusively for the end user's experience. So, the data models of experience layer vary based on the nature and type of such API consumer. For example, Mobile consumers will need light-weight data models to transfer with ease on the wire, where as web-based consumers will need detailed data models to render most of the info on web pages, so on. So, enterprise data models fit for the purpose of canonical models but not of good use for experience APIs.

>> That is why, EDMs should be used extensively in process and system tiers but NOT in experience tier.

Explanation

Correct Answer: From the Mule runtime irrespective of the deployment model

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>> Monitoring and Alerting metrics are always originated from Mule Runtimes irrespective of the deployment model.

>> It may seems that some metrics (Runtime Manager) are originated from Mule Runtime and some are (API Invocations/ API Analytics) from API Manager. However, this is realistically NOT TRUE. The reason is, API manager is just a management tool for API instances but all policies upon applying on APIs eventually gets executed on Mule Runtimes only (Either Embedded or API Proxy).

>> Similarly all API Implementations also run on Mule Runtimes.

So, most of the day required for monitoring and alerts are originated fron Mule Runtimes only irrespective of whether the deployment model is MuleSoft-hosted or Customer-hosted or Hybrid.

Explanation

Correct Answer: Implement required changes to the Process API implementation so that, whenever possible, the Process API’s RAML definition remains unchanged.

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Key requirement in the question is:

>> Approach that minimizes the impact of this change on API clients

Based on above:

>> Updating the RAML definition would possibly impact the API clients if the changes require any thing mandatory from client side. So, one should try to avoid doing that until really necessary.

>> Implementing the changes as a completely different API and then redirectly the clients with 3xx status code is really upsetting design and heavily impacts the API clients.

>> Organisations and IT cannot simply postpone the changes required until all API consumers acknowledge they are ready to migrate to a new Process API or API version. This is unrealistic and not possible.

The best way to handle the changes always is to implement required changes to the API implementations so that, whenever possible, the API’s RAML definition remains unchanged.

Explanation

Correct Answer: Drive consumption as much as production of assets; this enables developers to discover and reuse assets from other projects and encourages standardization

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>> The main motto of the new IT Operating Model that MuleSoft recommends and made popular is to change the way that they are delivered from a production model to a production + consumption model, which is done through an API strategy called API-led connectivity.

>> The assets built should also be discoverable and self-serveable for reusablity across LOBs and organization.

>> MuleSoft's IT operating model does not talk about SDLC model (Agile/ Lean etc) or MDM at all. So, options suggesting these are not valid.

References:

https://blogs.mulesoft.com/biz/connectivity/what-is-a-center-for-enablement-c4e/

https://www.mulesoft.com/resources/api/secret-to-managing-it-projects

Explanation

Correct Answer: Approve the client application request for the chosen SLA tier

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>> Only approving the client application request for the chosen SLA tier can be automated

>> Rest of the provided options are not valid

Explanation

Correct Answer: 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.

Explanation

Correct Answer: It makes API Manager aware of API implementations and hence enables it to enforce policies.

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>> API Autodiscovery is a mechanism that manages an API from API Manager by pairing the deployed application to an API created on the platform.

>> API Management includes tracking, enforcing policies if you apply any, and reporting API analytics.

>> Critical to the Autodiscovery process is identifying the API by providing the API name and version.

References:

https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-concept

https://docs.mulesoft.com/api-manager/1.x/api-auto-discovery

https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-conc ept

Explanation

Correct Answer: Option A

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>> Anypoint API Manager and API policies are applicable to all types of HTTP/1.x APIs.

>> They are not applicable to WebSocket APIs, HTTP/2 APIs and gRPC APIs

Explanation

Correct Answer: GET, OPTIONS, HEAD

https://restcookbook.com/HTTP%20Methods/idempotency/

Explanation

Correct Answers: API Design and Development and API Runtime Execution and Hosting

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>> API Design and Development - Anypoint Studio, Anypoint Design Center, Anypoint Connectors

>> API Runtime Execution and Hosting - Mule Runtimes, CloudHub, Runtime Services

>> API Operations and Management - Anypoint API Manager, Anypoint Exchange

>> API Consumer Management - API Contracts, Public Portals, Anypoint Exchange, API Notebooks

Explanation

Correct Answers: API Operations and Management and API Consumer Engagement

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>> API Design and Development - Anypoint Studio, Anypoint Design Center, Anypoint Connectors

>> API Runtime Execution and Hosting - Mule Runtimes, CloudHub, Runtime Services

>> API Operations and Management - Anypoint API Manager, Anypoint Exchange

>> API Consumer Management - API Contracts, Public Portals, Anypoint Exchange, API Notebooks

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Explanation

Correct Answer: The API consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation

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Terminology:

>> API Client - It is a piece of code or program the is written to invoke an API

>> API Consumer - An owner/entity who owns the API Client. API Consumers write API clients.

>> API - The provider of the API functionality. Typically an API Instance on API Manager where they are managed and operated.

>> API Implementation - The actual piece of code written by API provider where the functionality of the API is implemented. Typically, these are Mule Applications running on Runtime Manager.

Explanation

Correct Answer: Apply a basic authentication - LDAP policy; the internal Active Directory will be configured as the LDAP source for authenticating users.

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>> IP Whitelisting does NOT fit for this purpose. Moreover, the users workstations may not necessarily have static IPs in the network.

>> OAuth 2.0 enforcement requires a client provider which isn't in the organizations system components.

>> It is not an effective approach to let every user create separate client credentials and configure those for their usage.

The effective way it to apply a basic authentication - LDAP policy and the internal Active Directory will be configured as the LDAP source for authenticating users.

Explanation

Correct Answer: When the response time of API invocations exceeds a threshold

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>> 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.

Explanation

Correct Answer: When a pragmatic approach with only limited isolation from the backend system is deemed appropriate.

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General guidance w.r.t choosing Data Models:

>> If an Enterprise Data Model is in use then the API data model of System APIs should make use of data types from that Enterprise Data Model and the corresponding API implementation should translate between these data types from the Enterprise Data Model and the native data model of the backend system.

>> If no Enterprise Data Model is in use then each System API should be assigned to a Bounded Context, the API data model of System APIs should make use of data types from the corresponding Bounded Context Data Model and the corresponding API implementation should translate between these data types from the Bounded Context Data Model and the native data model of the backend system. In this scenario, the data types in the Bounded Context Data Model are defined purely in terms of their business characteristics and are typically not related to the native data model of the backend system. In other words, the translation effort may be significant.

>> If no Enterprise Data Model is in use, and the definition of a clean Bounded Context Data Model is considered too much effort, then the API data model of System APIs should make use of data types that approximately mirror those from the backend system, same semantics and naming as backend system, lightly sanitized, expose all fields needed for the given System API’s functionality, but not significantly more and making good use of REST conventions.

The latter approach, i.e., exposing in System APIs an API data model that basically mirrors that of the backend system, does not provide satisfactory isolation from backend systems through the System API tier on its own. In particular, it will typically not be possible to "swap out" a backend system without significantly changing all System APIs in front of that backend system and therefore the API implementations of all Process APIs that depend on those System APIs! This is so because it is not desirable to prolong the life of a previous backend system’s data model in the form of the API data model of System APIs that now front a new backend system. The API data models of System APIs following this approach must therefore change when the backend system is replaced.

On the other hand:

>> It is a very pragmatic approach that adds comparatively little overhead over accessing the backend system directly

>> Isolates API clients from intricacies of the backend system outside the data model (protocol, authentication, connection pooling, network address, …)

>> Allows the usual API policies to be applied to System APIs

>> Makes the API data model for interacting with the backend system explicit and visible, by exposing it in the RAML definitions of the System APIs

>> Further isolation from the backend system data model does occur in the API implementations of the Process API tier

Explanation

Correct Answer: Set a timeout of 100ms; that leaves 400ms for other two downstream APIs to complete

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Key details to take from the given scenario:

>> Upstream API's designed SLA is 500ms (median). Lets ignore maximum SLA response times.

>> This API calls 3 downstream APIs sequentially and all these are of similar complexity.

>> The first downstream API is offering median SLA of 100ms, 80th percentile: 500ms; 95th percentile: 1000ms.

Based on the above details:

>> We can rule out the option which is suggesting to set 50ms timeout. Because, if the median SLA itself being offered is 100ms then most of the calls are going to timeout and time gets wasted in retried them and eventually gets exhausted with all retries. Even if some retries gets successful, the remaining time wont leave enough room for 2nd and 3rd downstream APIs to respond within time.

>> The option suggesting to NOT set a timeout as the invocation of this API is mandatory and so we must wait until it responds is silly. As not setting time out would go against the good implementation pattern and moreover if the first API is not responding within its offered median SLA 100ms then most probably it would either respond in 500ms (80th percentile) or 1000ms (95th percentile). In BOTH cases, getting a successful response from 1st downstream API does NO GOOD because already by this time the Upstream API SLA of 500 ms is breached. There is no time left to call 2nd and 3rd downstream APIs.

>> It is NOT true that no timeout is possible to meet the upstream APIs desired SLA.

As 1st downstream API is offering its median SLA of 100ms, it means MOST of the time we would get the responses within that time. So, setting a timeout of 100ms would be ideal for MOST calls as it leaves enough room of 400ms for remaining 2 downstream API calls.

Correct Answer: Use an SLA-based rate limiting policy and assign a client application to a matching SLA tier based on its type.

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>> SLA tiers will come into play whenever any limits to be imposed on APIs based on client type

Explanation

Correct Answer: 8082

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>> 8091 and 8092 ports are to be used when keeping your HTTP and HTTPS app private to the LOCAL VPC respectively.

>> Above TWO ports are not for Shared AWS VPC/ Shared Worker Cloud.

>> 8081 is to be used when exposing your HTTP endpoint app to the internet through Shared LB

>> 8082 is to be used when exposing your HTTPS endpoint app to the internet through Shared LB

So, API invocations should be sent to port 8082 when calling this HTTPS based app.

References:

https://docs.mulesoft.com/runtime-manager/cloudhub-networking-guide

https://help.mulesoft.com/s/article/Configure-Cloudhub-Application-to-Send-a-HTTPS-Request-Directly-to-Another-Cloudhub-Application

https://help.mulesoft.com/s/question/0D52T00004mXXULSA4/multiple-http-listerners-on-cloudhub-one-with-port-9090

Explanation

Correct Answer: 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.