A set of tests must be performed prior to deploying API implementations to a staging environment. Due to data security and access restrictions, untested APIs cannot be granted access to the backend systems, so instead mocked data must be used for these tests. The amount of available mocked data and its contents is sufficient to entirely test the API implementations with no active connections to the backend systems. What type of tests should be used to incorporate this mocked data?
Correct Answer : Unit tests (Whitebox)
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As per general IT testing practice and MuleSoft recommended practice, Integration and Performance tests should be done on full end to end setup for right evaluation. Which means all end systems should be connected while doing the tests. So, these options are OUT and we are left with Unit Tests and Functional Tests.
As per attached reference documentation from MuleSoft:
Unit Tests - are limited to the code that can be realistically exercised without the need to run it inside Mule itself. So good candidates are Small pieces of modular code, Sub Flows, Custom transformers, Custom components, Custom expression evaluators etc.
Functional Tests - are those that most extensively exercise your application configuration. In these tests, you have the freedom and tools for simulating happy and unhappy paths. You also have the possibility to create stubs for target services and make them success or fail to easily simulate happy and unhappy paths respectively.
As the scenario in the question demands for API implementation to be tested before deployment to Staging and also clearly indicates that there is enough/ sufficient amount of mock data to test the various components of API implementations with no active connections to the backend systems, Unit Tests are the one to be used to incorporate this mocked data.
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 API implementation 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?
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
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>> 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.
What Anypoint Platform Capabilities listed below fall under APIs and API Invocations/Consumers category? Select TWO.
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
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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An organization has several APIs that accept JSON data over HTTP POST. The APIs are all publicly available and are associated with several mobile applications and web applications.
The organization does NOT want to use any authentication or compliance policies for these APIs, but at the same time, is worried that some bad actor could send payloads that could somehow compromise the applications or servers running the API implementations.
What out-of-the-box Anypoint Platform policy can address exposure to this threat?
Correct Answer : 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.
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 to avoid overloading the backend system?
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.
