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MuleSoft MCPA-Level-1 Sample Questions
Question # 1
An organization has created an API-led architecture that uses various API layers to integrate mobile clients with a backend system. The backend system consists of a number of specialized components and can be accessed via a REST API. The process and experience APIs share the same bounded-context model that is different from the backend data model. What additional canonical models, bounded-context models, or anti-corruption layers are best added to this architecture to help process data consumed from the backend system?
A. Create a bounded-context model for every layer and overlap them when the boundary contexts overlap, letting API developers know about the differences between upstream anddownstream data models B. Create a canonical model that combines the backend and API-led models to simplify and unify data models, and minimize data transformations. C. 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 cooperateacross the system and process layers D. Create an anti-corruption layer for every API to perform transformation for every data model to match each other, and let data simply travel between APIs to avoid the complexityand overhead of building canonical models
Answer: C Explanation: Explanation Correct Answer: 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.
Question # 2
When designing an upstream API and its implementation, the development team has been advised to NOT set timeouts when invoking a downstream API, because that downstreamAPI has no SLA that can be relied upon. This is the only downstream API dependency of that upstream API. Assume the downstream API runs uninterrupted without crashing. What is the impact of this advice?
A. An SLA for the upstream API CANNOT be provided B. The invocation of the downstream API will run to completion without timing out C. A default timeout of 500 ms will automatically be applied by the Mule runtime in which the upstream API implementation executes D. A toad-dependent timeout of less than 1000 ms will be applied by the Mule runtime in which the downstream API implementation executes
Answer: A Explanation: Explanation Correct Answer: An SLA for the upstream API CANNOT be provided. ***************************************** >> 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 timingout 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. Reference: https://docs.mulesoft.com/http-connector/1.5/http-documentation#parameters-3
Question # 3
An organization wants to make sure only known partners can invoke the organization's APIs. To achieve this security goal, the organization wants to enforce a Client ID Enforcement policy in API Manager so that only registered partner applications can invoke the organization's APIs. In what type of API implementation does MuleSoft recommend adding an API proxy to enforce the Client ID Enforcement policy, rather than embedding the policy directly in the application's JVM?
A. A Mule 3 application using APIkit B. A Mule 3 or Mule 4 application modified with custom Java code C. A Mule 4 application with an API specification D. A Non-Mule application
Answer: D Explanation: Explanation Correct Answer: A Non-Mule application ***************************************** >> All type of Mule applications (Mule 3/ Mule 4/ with APIkit/ with Custom Java Code etc) running on Mule Runtimes support the Embedded Policy Enforcement on them. >> The only option that cannot have or does not support embedded policy enforcementand must have API Proxy is for Non-Mule Applications. So, Non-Mule application is the right answer.
Question # 4
What are the major benefits of MuleSoft proposed IT Operating Model?
A.1. Decrease the IT delivery gap 2. Meet various business demands without increasing the IT capacity 3. Focus on creation of reusable assets first. Upon finishing creation of all the possibleassets then inform the LOBs in the organization to start using them B. 1. Decrease the IT delivery gap 2. Meet various business demands by increasing the IT capacity and forming various IT departments 3. Make consumption of assets at the rate of production C. 1. Decrease the IT delivery gap 2. Meet various business demands without increasing the IT capacity 3. Make consumption of assets at the rate of production
Answer: C Explanation: Explanation Correct Answer: 1. Decrease the IT delivery gap 2. Meet various business demands without increasing the IT capacity 3. Make consumption of assets at the rate of production. ***************************************** Reference: https://www.youtube.com/watch?v=U0FpYMnMjmM
Question # 5
Which of the following sequence is correct?
A. API Client implementes logic to call an API >> API Consumer requests access to API >> API Implementation routes the request to >> API B. API Consumer requests access to API >> API Client implementes logic to call an API >> API routes the request to >> API Implementation C. API Consumer implementes logic to call an API >> API Client requests access to API >> API Implementation routes the request to >> API D. API Client implementes logic to call an API >> API Consumer requests access to API >> API routes the request to >> API Implementation
Answer: B Explanation: Explanation Correct Answer: API Consumer requests access to API >> API Client implementes logic to call an API >> API routes the request to >> API Implementation ***************************************** >> API consumer does not implement any logic to invoke APIs. It is just a role. So, the option stating "API Consumer implementes logic to call an API" is INVALID. >> API Implementation does not route any requests. It is a final piece of logic where functionality of target systems is exposed. So, the requests should be routed to the API implementation by some other entity. So, the options stating "API Implementation routes the request to >> API" is INVALID >> The statements in one of the options are correct but sequence is wrong. The sequence is given as "API Client implementes logic to call an API >> API Consumer requests access to API >> API routes the request to >> API Implementation". Here, the statements in the options are VALID but sequence is WRONG. >> Right option and sequence is the one where API consumer first requests access to API on Anypoint Exchange and obtains client credentials. API client then writes logic to call an API by using the access client credentials requested by API consumer and the requests will be routed to API implementation via the API which is managed by API Manager.
Question # 6
Due to a limitation in the backend system, a system API can only handle up to 500 requests per second. What is the best type of API policy to apply to the system API toavoid overloading the backend system?
A. Rate limiting B. HTTP caching C. Rate limiting - SLA based D. Spike control
Answer: D Explanation: Explanation Correct Answer: Spike control ***************************************** >> First things first, HTTP Caching policy is for purposes different than avoiding thebackend 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.
Question # 7
A company requires Mule applications deployed to CloudHub to be isolated between nonproduction and production environments. This is so Mule applications deployed to nonproduction environments can only access backend systems running in their customerhosted non-production environment, and so Mule applications deployed to production environments can only access backend systems running in their customer-hosted production environment. How does MuleSoft recommend modifying Mule applications, configuring environments, or changing infrastructure to support this type of perenvironment isolation between Mule applications and backend systems?
A. Modify properties of Mule applications deployed to the production Anypoint Platform environments to prevent access from non-production Mule applications B. Configure firewall rules in the infrastructure inside each customer-hosted environment so that only IP addresses from the corresponding Anypoint Platform environments are allowedto communicate with corresponding backend systems C. Create non-production and production environments in different Anypoint Platform business groups D. Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hostedenvironments
Answer: D Explanation: Explanation Correct Answer: Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hosted environments. ***************************************** >> Creating different Business Groups does NOT make any difference w.r.t accessing the non-prod and prod customer-hosted environments. Still they will be accessing from both Business Groups unless process network restrictions are put in place. >> We need to modify or couple the Mule Application Implementations with the environment. In fact, we should never implements application coupled with environments by binding them in the properties. Only basic things like endpoint URL etc should be bundled in properties but not environment level access restrictions. >> IP addresses on CloudHub are dynamic until unless a special static addresses are assigned. So it is not possible to setup firewall rules in customer-hosted infrastrcture. More over, even if static IP addresses are assigned, there could be 100s of applications running on cloudhub and setting up rules for all of them would be a hectic task, non-maintainable and definitely got a good practice. >> The best practice recommended by Mulesoft (In fact any cloud provider), is to have your Anypoint VPCs seperated for Prod and Non-Prod and perform the VPC peering or VPN tunneling for these Anypoint VPCs to respective Prod and Non-Prod customer-hosted environment networks. : https://docs.mulesoft.com/runtime-manager/virtual-private-cloud Bottom of Form Top of Form
Question # 8
A company uses a hybrid Anypoint Platform deployment model that combines the EU control plane with customer-hosted Mule runtimes. After successfully testing a Mule APIimplementation in the Staging environment, the Mule API implementation is set with environment-specific properties and must be promoted to the Production environment.What is a way that MuleSoft recommends to configure the Mule API implementation and automate its promotion to the Production environment?
A. Bundle properties files for each environment into the Mule API implementation's deployable archive, then promote the Mule API implementation to the Production environment usingAnypoint CLI or the Anypoint Platform REST APIsB. B. Modify the Mule API implementation's properties in the API Manager Properties tab, then promote the Mule API implementation to the Production environment using API Manager C. Modify the Mule API implementation's properties in Anypoint Exchange, then promote the Mule API implementation to the Production environment using Runtime M D. Use an API policy to change properties in the Mule API implementation deployed to the Staging environment and another API policy to deploy the Mule API implementation to theProduction environment
Answer: A Explanation: Explanation Correct Answer: Bundle properties files for each environment into the Mule API implementation's deployable archive, then promote the Mule API implementation to the Production environment using Anypoint CLI or the Anypoint Platform REST APIs ***************************************** >> Anypoint Exchange is for asset discovery and documentation. It has got no provision to modify the properties of Mule API implementations at all. >> API Manager is for managing API instances, their contracts, policies and SLAs. It has also got no provision to modify the properties of API implementations. >> API policies are to address Non-functional requirements of APIs and has again got no provision to modify the properties of API implementations. So, the right way and recommended way to do this as part of development practice is to bundle properties files for each environment into the Mule API implementation and just point and refer to respective file per environment.
Question # 9
A REST API is being designed to implement a Mule application. What standard interface definition language can be used to define REST APIs?
A. Web Service Definition Language(WSDL) B. OpenAPI Specification (OAS) C. YAML D. AsyncAPI Specification
Answer: B
Question # 10
A system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. A process API is a client tothe system API and is being rate limited by the system API, with different limits in each of the environments. The system API's DR environment provides only 20% of the rate limitingoffered by the primary environment. What is the best API fault-tolerant invocation strategy to reduce overall errors in the process API, given these conditions and constraints?
A. 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 deployedto the DR environment B. Invoke the system API deployed to the primary environment; add retry logic to the process API to handle intermittent failures by invoking the system API deployed to the DRenvironment C. In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment; add timeout and retry logic to the process API to avoidintermittent failures; add logic to the process API to combine the results D. 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 a copy of the process APIdeployed to the DR environment
Answer: A Explanation: 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 ***************************************** 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 faulttolerant 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.
