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Salesforce MuleSoft-Platform-Architect-I Exam Syllabus Topics:
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NEW QUESTION # 76
What API policy would be LEAST LIKELY used when designing an Experience API that is intended to work with a consumer mobile phone or tablet application?
- A. JSON threat protection
- B. Client ID enforcement
- C. OAuth 2.0 access token enforcement
- D. IPwhitellst
Answer: D
Explanation:
Correct Answer : IP whitelist
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>> OAuth 2.0 access token and Client ID enforcement policies are VERY common to apply on Experience APIs as API consumers need to register and access the APIs using one of these mechanisms
>> JSON threat protection is also VERY common policy to apply on Experience APIs to prevent bad or suspicious payloads hitting the API implementations.
>> IP whitelisting policy is usually very common in Process and System APIs to only whitelist the IP range inside the local VPC. But also applied occassionally on some experience APIs where the End User/ API Consumers are FIXED.
>> When we know the API consumers upfront who are going to access certain Experience APIs, then we can request for static IPs from such consumers and whitelist them to prevent anyone else hitting the API.
However, the experience API given in the question/ scenario is intended to work with a consumer mobile phone or tablet application. Which means, there is no way we can know all possible IPs that are to be whitelisted as mobile phones and tablets can so many in number and any device in the city/state/country/globe.
So, It is very LEAST LIKELY to apply IP Whitelisting on such Experience APIs whose consumers are typically Mobile Phones or Tablets.
NEW QUESTION # 77
An enterprise is embarking on the API-led digital transformation journey, and the central IT team has started to define System APIs. Currently there is no Enterprise Data Model being defined within the enterprise, and the definition of a clean Bounded Context Data Model requires too much effort.
According to MuleSoft's recommended guidelines, how should the System API data model be defined?
- A. The data model of the System APIs should make use of data types that approximately mirror those from the back-end systems
- B. The System APIs should expose all back-end system fields
- C. If there are misspellings of the data fields in the back-end system, Systerm APIs should not correct it, and expose it as-is to mirror the back-end systems
- D. The data model should define its own naming convention, and not follow the same naming as the back-end systems
Answer: A
Explanation:
When defining data models for System APIs without an established Enterprise Data Model, MuleSoft recommends mirroring the back-end systems' data types to achieve quick and effective integration without adding complexity. This approach has several benefits:
Alignment with Backend Systems:
Mirroring data types ensures consistency with backend data sources, which simplifies integration, reduces mapping requirements, and minimizes potential data transformation issues.
Flexibility for Future Enhancements:
By retaining close alignment with backend data structures, System APIs can evolve to support an Enterprise Data Model in the future without immediate restructuring.
of Incorrect Options:
Option A (exposing misspellings) is not recommended as System APIs should still ensure a professional and coherent interface.
Option C (custom naming) complicates the API structure without adding immediate value in the absence of a clear data model.
Option D (exposing all fields) is unnecessary and can reduce performance and add complexity.
Reference
Refer to MuleSoft best practices for data modeling in System APIs for additional information on mirroring backend systems.
NEW QUESTION # 78
A retail company with thousands of stores has an API to receive data about purchases and insert it into a single database. Each individual store sends a batch of purchase data to the API about every 30 minutes. The API implementation uses a database bulk insert command to submit all the purchase data to a database using a custom JDBC driver provided by a data analytics solution provider. The API implementation is deployed to a single CloudHub worker. The JDBC driver processes the data into a set of several temporary disk files on the CloudHub worker, and then the data is sent to an analytics engine using a proprietary protocol. This process usually takes less than a few minutes. Sometimes a request fails. In this case, the logs show a message from the JDBC driver indicating an out-of-file-space message. When the request is resubmitted, it is successful. What is the best way to try to resolve this throughput issue?
- A. se a CloudHub autoscaling policy to add CloudHub workers
- B. Use a CloudHub autoscaling policy to increase the size of the CloudHub worker
- C. Increase the number of CloudHub workers
- D. Increase the size of the CloudHub worker(s)
Answer: C
Explanation:
Correct Answer : Increase the size of the CloudHub worker(s)
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The key details that we can take out from the given scenario are:
>> API implementation uses a database bulk insert command to submit all the purchase data to a database
>> JDBC driver processes the data into a set of several temporary disk files on the CloudHub worker
>> Sometimes a request fails and the logs show a message indicating an out-of-file-space message Based on above details:
>> Both auto-scaling options does NOT help because we cannot set auto-scaling rules based on error messages. Auto-scaling rules are kicked-off based on CPU/Memory usages and not due to some given error or disk space issues.
>> Increasing the number of CloudHub workers also does NOT help here because the reason for the failure is not due to performance aspects w.r.t CPU or Memory. It is due to disk-space.
>> Moreover, the API is doing bulk insert to submit the received batch data. Which means, all data is handled by ONE worker only at a time. So, the disk space issue should be tackled on "per worker" basis. Having multiple workers does not help as the batch may still fail on any worker when disk is out of space on that particular worker.
Therefore, the right way to deal this issue and resolve this is to increase the vCore size of the worker so that a new worker with more disk space will be provisioned.
NEW QUESTION # 79
A Platform Architect inherits a legacy monolithic SOAP-based web service that performs a number of tasks, including showing all policies belonging to a client. The service connects to two back-end systems - a life-insurance administration system and a general-insurance administration system - and then queries for insurance policy information within each system, aggregates the results, and presents a SOAP-based response to a user interface (UI).
The architect wants to break up the monolithic web service to follow API-led conventions.
Which part of the service should be put into the process layer?
- A. Querying the data from the administration systems
- B. Combining the insurance policy information from the administration systems
- C. Authenticating and maintaining connections to each of the back-end administration systems
- D. Presenting the SOAP-based response to the UI
Answer: B
Explanation:
In the API-led connectivity approach, each layer (System, Process, and Experience) has a distinct purpose:
System APIs: These APIs connect directly to backend systems to expose and unlock data in a standardized way.
Process APIs: These are responsible for orchestrating and processing data across different systems, combining information where needed.
Experience APIs: These are designed for specific user interfaces or applications, often transforming data formats to fit the needs of each consumer application.
Why Option A is Correct:
Process APIs are designed to combine data from multiple systems, which aligns with the function of aggregating policy information from both the life and general insurance systems. This aggregation logic would ideally reside in the Process layer, separating data retrieval from data orchestration.
Moving this functionality to the Process layer enables reusability and modularity, as other Experience APIs or services could also leverage the combined policy data if needed.
of Incorrect Options:
Option B (Presenting the SOAP-based response) would be managed by the Experience layer, as this layer adapts data formats for specific interfaces.
Option C (Authenticating and maintaining backend connections) would typically be handled within the System layer, where backend integration and security handling occurs.
Option D (Querying data) is the function of System APIs, which access the backend systems directly and expose the raw data without additional processing.
Reference
For further details on API-led architecture and the roles of each layer, refer to MuleSoft's documentation on API-led connectivity and API layers.
NEW QUESTION # 80
A customer has an ELA contract with MuleSoft. An API deployed to CloudHub is consistently experiencing performance issues. Based on the root cause analysis, it is determined that autoscaling needs to be applied.
How can this be achieved?
- A. Configure two separate policies: When CPU and memory reach certain threshold, increase the worker/replica type (vertical sealing) and the number of workers/replicas (horizontal sealing)
- B. Configure a policy so that when the response time reaches a certain threshold the worker/replica type increases (vertical scaling)
- C. Configure a policy based on CPU usage so that CloudHub auto-adjusts the number of workers/replicas (horizontal scaling)
- D. Configure a policy so that when the number of HTTP requests reaches a certain threshold the number of workers/replicas increases (horizontal scaling)
Answer: C
Explanation:
In MuleSoft CloudHub, autoscaling is essential to managing application load efficiently. CloudHub supports horizontal scaling based on CPU usage, which is well-suited to applications experiencing variable demand and needing responsive resource allocation.
Autoscaling on CloudHub:
Horizontal scaling increases the number of workers in response to CPU usage thresholds, allowing the application to handle higher loads dynamically. This approach improves performance without downtime or manual intervention.
Why Option C is Correct:
Setting up autoscaling based on CPU usage aligns with MuleSoft's best practices for scalable and responsive applications on CloudHub, particularly in an environment with fluctuating load patterns.
Option C correctly leverages CloudHub's autoscaling features based on resource metrics, which are part of CloudHub's managed scaling solutions.
of Incorrect Options:
Option A (based on HTTP request thresholds) and Option B (separate policies for CPU and memory) do not represent CloudHub's recommended scaling practices.
Option D suggests vertical scaling based on response time, which is not how CloudHub handles autoscaling.
Reference
For more on CloudHub's autoscaling configuration, refer to MuleSoft documentation on CloudHub autoscaling policies.
NEW QUESTION # 81
An API implementation is deployed on a single worker on CloudHub and invoked by external API clients (outside of CloudHub). How can an alert be set up that is guaranteed to trigger AS SOON AS that API implementation stops responding to API invocations?
- A. Configure a "worker not responding" alert in Anypoint Runtime Manager
- B. Implement a heartbeat/health check within the API and invoke it from outside the Anypoint Platform and alert when the heartbeat does not respond
- C. Create an alert for when the API receives no requests within a specified time period
- D. Handle API invocation exceptions within the calling API client and raise an alert from that API client when the API Is unavailable
Answer: A
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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NEW QUESTION # 82
Which component monitors APIs and endpoints at scheduled intervals, receives reports about whether tests pass or fail, and displays statistics about API and endpoint performance?
- A. Anypoint Runtime Manager alerts
- B. Anypoint Monitoring dashboards
- C. APT Functional Monitoring
- D. API Analytics
Answer: C
Explanation:
Understanding API Functional Monitoring:
API Functional Monitoring is a feature within MuleSoft's Anypoint Platform that enables users to monitor the health and performance of APIs and endpoints by running functional tests at scheduled intervals.
It checks whether APIs are functioning as expected by running test calls and then evaluating if the response meets the desired conditions. This is particularly useful for testing endpoint availability, checking for specific data in responses, and measuring API performance over time.
Component Features:
Scheduled Intervals: Functional monitoring allows configuring tests to run at regular intervals, such as every minute, hour, or day, depending on the monitoring requirements.
Reports on Test Pass/Fail Status: After each test run, API Functional Monitoring reports whether the API passed or failed the test conditions.
Performance Statistics: It displays metrics like average response time, success rate, and error rates, giving insights into API health and performance.
Evaluating the Options:
Option A (API Analytics): API Analytics provides insights on API usage and metrics but does not involve scheduled tests for pass/fail status or endpoint health checks.
Option B (Anypoint Monitoring Dashboards): These dashboards display API metrics but do not actively test API endpoints or provide pass/fail reporting on a scheduled basis.
Option C (Correct Answer): API Functional Monitoring fits the description, as it is designed to monitor API and endpoint health with scheduled test runs and display statistics about performance.
Option D (Anypoint Runtime Manager Alerts): Runtime Manager alerts notify users of issues with application status but do not actively test endpoints at scheduled intervals.
Conclusion:
Option C (API Functional Monitoring) is the correct answer because it provides the necessary tools to test API functionality, monitor endpoint health, and display performance statistics in real-time.
Refer to MuleSoft documentation on API Functional Monitoring for further guidance on setting up and configuring these tests in Anypoint Platform.
NEW QUESTION # 83
Refer to the exhibit.
What is the best way to decompose one end-to-end business process into a collaboration of Experience, Process, and System APIs?
A) Handle customizations for the end-user application at the Process API level rather than the Experience API level
B) Allow System APIs to return data that is NOT currently required by the identified Process or Experience APIs
C) Always use a tiered approach by creating exactly one API for each of the 3 layers (Experience, Process and System APIs)
D) Use a Process API to orchestrate calls to multiple System APIs, but NOT to other Process APIs
- A. Option D
- B. Option A
- C. Option C
- D. Option B
Answer: D
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.
NEW QUESTION # 84
When should idempotency be taken into account?
- A. When storing the results of s previous request for use in response to subsequent requests
- B. When sending concurrent update requests for the same entity
- C. When preventing duplicate processing from multiple sent requests
- D. When making requests to update currently locked entities
Answer: C
Explanation:
Understanding Idempotency:
Idempotency is a concept in APIs where an operation can be performed multiple times without changing the result beyond the initial application. This is particularly important for operations that may be repeated due to network retries or client errors.
When to Consider Idempotency:
Idempotency should be taken into account when there is a risk of duplicate processing due to multiple requests being sent (e.g., retries or errors). This ensures that repeated requests do not result in unintended side effects, such as creating multiple records or processing the same transaction more than once.
Evaluating the Options:
Option A: While locked entities may need special handling, this is not directly related to idempotency.
Option B: Storing results for future responses could be useful but does not relate to idempotent operations.
Option C: Concurrent requests for the same entity might require handling for conflicts, but this scenario is better suited for transaction management or concurrency control.
Option D (Correct Answer): Preventing duplicate processing from multiple requests is a key reason to implement idempotency, ensuring that repeat requests have no adverse effects.
Conclusion:
Option D is the correct answer as idempotency is specifically used to handle scenarios where duplicate requests might be sent, preventing unintended processing.
Refer to MuleSoft's documentation on best practices for idempotency in API design for more details.
NEW QUESTION # 85
Several times a week, an API implementation shows several thousand requests per minute in an Anypoint Monitoring dashboard, Between these bursts, the dashboard shows between two and five requests per minute. The API implementation is running on Anypoint Runtime Fabric with two non-clustered replicas, reserved vCPU 1.0 and vCPU Limit 2.0.
An API consumer has complained about slow response time, and the dashboard shows the 99 percentile is greater than 120 seconds at the time of the complaint. It also shows greater than 90% CPU usage during these time periods.
In manual tests in the QA environment, the API consumer has consistently reproduced the slow response time and high CPU usage, and there were no other API requests at this time. In a brainstorming session, the engineering team has created several proposals to reduce the response time for requests.
Which proposal should be pursued first?
- A. Increase the number of replicas of the API implementation
- B. Throttle the APT client to reduce the number of requests per minute
- C. Modify the API client to split the problematic request into smaller, less-demanding requests
- D. Increase the vCPU resources of the API implementation
Answer: D
Explanation:
Scenario Analysis:
The API implementation is experiencing high CPU usage (over 90%) during bursts of requests, which correlates with slow response times, as indicated by a 99th percentile response time greater than 120 seconds.
The API implementation is running on Anypoint Runtime Fabric with two non-clustered replicas and has a reserved vCPU of 1.0 and a vCPU limit of 2.0.
The high CPU usage during bursts suggests that the current resources may not be sufficient to handle peak loads.
Evaluating the Options:
Option A (Correct Answer): Increasing the vCPU resources for each replica would provide more processing power to handle high traffic volumes, potentially reducing the response time during spikes. Since the CPU usage is consistently high during bursts, this option directly addresses the resource bottleneck.
Option B: Modifying the API client to split requests may reduce individual request load but could be complex to implement on the client side and may not fully address the high CPU issue.
Option C: Increasing the number of replicas could help distribute the load; however, with a high CPU load on each replica, adding more replicas without increasing CPU resources may not fully resolve the problem.
Option D: Throttling the client would reduce the number of requests, but this may not be acceptable if the client needs to maintain a high request rate. It also does not directly address the CPU limitations of the API implementation.
Conclusion:
Option A is the best choice as it addresses the root cause of high CPU usage by increasing the vCPU allocation, allowing the API to handle more requests efficiently. This should be pursued first before considering other options.
Refer to MuleSoft's documentation on Runtime Fabric and vCPU resource allocation for more details on optimizing API performance in high-demand environments.
NEW QUESTION # 86
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 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 complexity and overhead of building canonical models
- B. 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 and downstream data models
- C. Create a canonical model that combines the backend and API-led models to simplify and unify data models, and minimize data transformations.
- D. 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
Answer: D
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
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>> 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.
NEW QUESTION # 87
What is true about the technology architecture of Anypoint VPCs?
- A. VPC peering can be used to link the underlying AWS VPC to an on-premises (non AWS) private network
- B. Traffic between Mule applications deployed to an Anypoint VPC and on-premises systems can stay within a private network
- C. Each CloudHub environment requires a separate Anypoint VPC
- D. The private IP address range of an Anypoint VPC is automatically chosen by CloudHub
Answer: B
Explanation:
Correct Answer : Traffic between Mule applications deployed to an Anypoint VPC and on-premises systems can stay within a private network
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>> The private IP address range of an Anypoint VPC is NOT automatically chosen by CloudHub. It is chosen by us at the time of creating VPC using thr CIDR blocks.
CIDR Block: The size of the Anypoint VPC in Classless Inter-Domain Routing (CIDR) notation.
For example, if you set it to 10.111.0.0/24, the Anypoint VPC is granted 256 IP addresses from 10.111.0.0 to 10.111.0.255.
Ideally, the CIDR Blocks you choose for the Anypoint VPC come from a private IP space, and should not overlap with any other Anypoint VPC's CIDR Blocks, or any CIDR Blocks in use in your corporate network.
that each CloudHub environment requires a separate Anypoint VPC. Once an Anypoint VPC is created, we can choose a same VPC by multiple environments. However, it is generally a best and recommended practice to always have seperate Anypoint VPCs for Non-Prod and Prod environments.
>> We use Anypoint VPN to link the underlying AWS VPC to an on-premises (non AWS) private network. NOT VPC Peering.
Reference:
Only true statement in the given choices is that the traffic between Mule applications deployed to an Anypoint VPC and on-premises systems can stay within a private network.
https://docs.mulesoft.com/runtime-manager/vpc-connectivity-methods-concept
NEW QUESTION # 88
A Platform Architect inherits a legacy monolithic SOAP-based web service that performs a number of tasks, including showing all policies belonging to a client. The service connects to two back-end systems - a life-insurance administration system and a general-insurance administration system - and then queries for insurance policy information within each system, aggregates the results, and presents a SOAP-based response to a user interface (UI).
The architect wants to break up the monolithic web service to follow API-led conventions.
Which part of the service should be put into the process layer?
- A. Querying the data from the administration systems
- B. Combining the insurance policy information from the administration systems
- C. Authenticating and maintaining connections to each of the back-end administration systems
- D. Presenting the SOAP-based response to the UI
Answer: B
NEW QUESTION # 89
Which two statements are true about the technology architecture of an Anypoint Virtual Private Cloud (VPC)?
Choose 2 answers
- A. Ports 8081 and 8082 are used
- B. Anypoint VPC is responsible for load balancing the applications
- C. CIDR blacks are used
- D. By default, HTTP requests can be made from the public internet to workers at port 6091
- E. Round-robin load balancing is used to distribute client requests across different applications
Answer: C,D
Explanation:
An Anypoint Virtual Private Cloud (VPC) provides a secure and private networking environment for MuleSoft applications, using specific architectural elements:
CIDR Blocks:
Anypoint VPCs utilize CIDR blocks to define IP ranges, allowing organizations to control and segment the VPC's IP address space.
Port 6091 for HTTP Requests:
By default, HTTP requests can be made to workers on port 6091 from the public internet, providing an accessible entry point unless additional restrictions are applied.
of Correct Answers (B, E):
CIDR blocks enable IP range management for VPCs, and port 6091 is the default public entry port, which is part of Anypoint VPC's default settings.
of Incorrect Options:
Option A (Ports 8081 and 8082) is incorrect; these are not default public ports for Anypoint VPC.
Option C (responsible for load balancing) is incorrect as load balancing requires a separate Dedicated Load Balancer (DLB).
Option D (round-robin load balancing) applies to DLBs, not directly to VPCs.
Reference
For more on VPC setup and networking, refer to MuleSoft documentation on VPC configurations and default port settings.
NEW QUESTION # 90
What correctly characterizes unit tests of Mule applications?
- A. They must be triggered by an external client tool or event source
- B. They test the validity of input and output of source and target systems
- C. They are typically written using MUnit to run in an embedded Mule runtime that does not require external connectivity
- D. They must be run in a unit testing environment with dedicated Mule runtimes for the environment
Answer: C
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
NEW QUESTION # 91
An API has been updated in Anypoint exchange by its API producer from version 3.1.1 to 3.2.0 following accepted semantic versioning practices and the changes have been communicated via the APIs public portal. The API endpoint does NOT change in the new version. How should the developer of an API client respond to this change?
- A. The API clients need to update the code on their side and need to do full regression
- B. The API producer should be contacted to understand the change to existing functionality
- C. The API client code only needs to be changed if it needs to take advantage of the new features
- D. The API producer should be requested to run the old version in parallel with the new one
Answer: C
NEW QUESTION # 92
An API implementation is deployed to CloudHub.
What conditions can be alerted on using the default Anypoint Platform functionality, where the alert conditions depend on the end-to-end request processing of the API implementation?
- A. When the response time of API invocations exceeds a threshold
- B. When the API is invoked by an unrecognized API client
- C. When the API receives a very high number of API invocations
- D. When a particular API client invokes the API too often within a given time period
Answer: A
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.
NEW QUESTION # 93
What API policy would LEAST likely be applied to a Process API?
- A. Client ID enforcement
- B. Custom circuit breaker
- C. JSON threat protection
- D. Rate limiting
Answer: C
Explanation:
Correct Answer : JSON threat protection
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Fact: Technically, there are no restrictions on what policy can be applied in what layer. Any policy can be applied on any layer API. However, context should also be considered properly before blindly applying the policies on APIs.
That is why, this question asked for a policy that would LEAST likely be applied to a Process API.
From the given options:
>> All policies except "JSON threat protection" can be applied without hesitation to the APIs in Process tier.
>> JSON threat protection policy ideally fits for experience APIs to prevent suspicious JSON payload coming from external API clients. This covers more of a security aspect by trying to avoid possibly malicious and harmful JSON payloads from external clients calling experience APIs.
As external API clients are NEVER allowed to call Process APIs directly and also these kind of malicious and harmful JSON payloads are always stopped at experience API layer only using this policy, it is LEAST LIKELY that this same policy is again applied on Process Layer API.
NEW QUESTION # 94
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?
- A. Modify the Mule API implementation's properties in Anypoint Exchange, then promote the Mule API implementation to the Production environment using Runtime Manager
- 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. 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 the Production environment
- D. 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 APIsB.
Answer: D
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
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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.
NEW QUESTION # 95
An organization uses various cloud-based SaaS systems and multiple on-premises systems. The on-premises systems are an important part of the organization's application network and can only be accessed from within the organization's intranet.
What is the best way to configure and use Anypoint Platform to support integrations with both the cloud-based SaaS systems and on-premises systems?
A) Use CloudHub-deployed Mule runtimes in an Anypoint VPC managed by Anypoint Platform Private Cloud Edition control plane
B) Use CloudHub-deployed Mule runtimes in the shared worker cloud managed by the MuleSoft-hosted Anypoint Platform control plane
C) Use an on-premises installation of Mule runtimes that are completely isolated with NO external network access, managed by the Anypoint Platform Private Cloud Edition control plane
D) Use a combination of Cloud Hub-deployed and manually provisioned on-premises Mule runtimes managed by the MuleSoft-hosted Anypoint Platform control plane
- A. Option D
- B. Option A
- C. Option C
- D. Option B
Answer: D
Explanation:
Correct Answer : Use a combination of CloudHub-deployed and manually provisioned on-premises Mule runtimes managed by the MuleSoft-hosted Platform control plane.
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Key details to be taken from the given scenario:
>> Organization uses BOTH cloud-based and on-premises systems
>> On-premises systems can only be accessed from within the organization's intranet Let us evaluate the given choices based on above key details:
>> CloudHub-deployed Mule runtimes can ONLY be controlled using MuleSoft-hosted control plane. We CANNOT use Private Cloud Edition's control plane to control CloudHub Mule Runtimes. So, option suggesting this is INVALID
>> Using CloudHub-deployed Mule runtimes in the shared worker cloud managed by the MuleSoft-hosted Anypoint Platform is completely IRRELEVANT to given scenario and silly choice. So, option suggesting this is INVALID
>> Using an on-premises installation of Mule runtimes that are completely isolated with NO external network access, managed by the Anypoint Platform Private Cloud Edition control plane would work for On-premises integrations. However, with NO external access, integrations cannot be done to SaaS-based apps. Moreover CloudHub-hosted apps are best-fit for integrating with SaaS-based applications. So, option suggesting this is BEST WAY.
The best way to configure and use Anypoint Platform to support these mixed/hybrid integrations is to use a combination of CloudHub-deployed and manually provisioned on-premises Mule runtimes managed by the MuleSoft-hosted Platform control plane.
NEW QUESTION # 96
Which out-of-the-box key performance indicator measures the success of a typical Center for Enablement and is immediately available in responses from Anypoint Platform APIs?
- A. Per published API, the number of consumers that requested access to the API and have been approved in the Production environment
- B. Per published API, the number of developers that downloaded s version of the API specification
- C. Per deployed API implementation, the amount of bandwidth consumed each day
- D. Per business group, the ratio of the number of production APT implementations deployed using a C1/CD pipeline to the number of production API implementations deployed manually
Answer: A
Explanation:
Center for Enablement (C4E) KPIs:
A Center for Enablement (C4E) in MuleSoft focuses on enabling self-service and reuse by providing APIs that can be consumed across the organization. A key metric of success is how many consumers are utilizing the published APIs.
The number of consumers who have requested and received access to an API indicates the level of adoption and reuse, which aligns with the goals of a C4E.
Evaluating the Options:
Option A: This metric could indicate deployment automation, but it is not a direct measure of C4E's success in enabling API reuse and consumption.
Option B: Bandwidth usage per API implementation provides insight into API traffic but does not measure C4E enablement or consumer engagement.
Option C: The number of developers downloading an API specification can be an indicator of interest but does not confirm actual usage or enablement.
Option D (Correct Answer): The number of consumers who have requested and received access to an API in production is a key metric indicating API adoption and reuse, which aligns with C4E's goals.
Conclusion:
Option D is the correct answer as it provides a direct measure of consumer engagement and adoption, indicating the success of the C4E in promoting API usage across the organization.
Refer to MuleSoft's documentation on C4E KPIs and API usage metrics for additional insights.
NEW QUESTION # 97
A system API has a guaranteed SLA of 100 ms per request. The system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. An upstream process API invokes the system API and the main goal of this process API is to respond to client requests in the least possible time. In what order should the system APIs be invoked, and what changes should be made in order to speed up the response time for requests from the process API?
- A. 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
- B. Invoke ONLY the system API deployed to the primary environment, and add timeout and retry logic to avoid intermittent failures
- C. In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment using a scatter-gather configured with a timeout, and then merge the responses
- D. Invoke the system API deployed to the primary environment, and if it fails, invoke the system API deployed to the DR environment
Answer: A
Explanation:
Correct Answer : 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.
NEW QUESTION # 98
Question 10: Skipped
An API implementation returns three X-RateLimit-* HTTP response headers to a requesting API client. What type of information do these response headers indicate to the API client?
- A. A correlation ID that should be sent in the next request
- B. The error codes that result from throttling
- C. The HTTP response size
- D. The remaining capacity allowed by the API implementation
Answer: D
Explanation:
Correct Answe r: 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
NEW QUESTION # 99
An Order API triggers a sequence of other API calls to look up details of an order's items in a back-end inventory database. The Order API calls the OrderItems process API, which calls the Inventory system API. The Inventory system API performs database operations in the back-end inventory database.
The network connection between the Inventory system API and the database is known to be unreliable and hang at unpredictable times.
Where should a two-second timeout be configured in the API processing sequence so that the Order API never waits more than two seconds for a response from the Orderltems process API?
- A. In the Order API implementation
- B. In the inventory database
- C. In the Inventory system API implementation
- D. In the Orderltems process API implementation
Answer: D
Explanation:
Understanding the API Flow and Timeout Requirement:
The Order API initiates a call to the OrderItems process API, which in turn calls the Inventory system API to fetch details from the inventory database.
The requirement specifies that the Order API should not wait more than two seconds for a response from the OrderItems process API, even if there are delays further down the chain (between Inventory system API and the database).
Choosing the Appropriate Timeout Location:
Setting the timeout at the OrderItems process API level ensures that if the Inventory system API takes longer than two seconds to respond, the OrderItems process API will terminate the request and send a timeout response back to the Order API. This prevents the Order API from waiting indefinitely due to the unreliable connection to the database.
If the timeout were set in the Inventory system API or database, it would not help the Order API directly, as the OrderItems process API would still be waiting for a response.
Detailed Analysis of Each Option:
Option A (Correct Answer): Setting the timeout in the OrderItems process API allows it to control how long it waits for a response from the Inventory system API. If the Inventory system API does not respond within two seconds, the OrderItems process API can terminate the call and return a timeout response to the Order API, meeting the requirement.
Option B: Setting the timeout in the Order API would not limit the wait time at the OrderItems process API level, meaning the OrderItems process API could still wait indefinitely for the Inventory system API, leading to a longer delay.
Option C: Setting the timeout in the Inventory system API only affects the connection to the database and does not influence how long the OrderItems process API waits for the Inventory system API's response.
Option D: Setting a timeout in the database is not feasible in this context since database timeouts are typically configured for database operations and would not directly control the API response times in the overall API chain.
Conclusion:
Option A is the best choice, as it ensures that the OrderItems process API does not hold the Order API longer than the required two seconds, even if the downstream connection to the database hangs. This configuration aligns with MuleSoft best practices for setting timeouts in API orchestration to manage dependencies and prevent delays across a chain of API calls.
For additional information on timeout settings, refer to MuleSoft documentation on handling timeouts and API orchestration best practices.
NEW QUESTION # 100
Once an API Implementation is ready and the API is registered on API Manager, who should request the access to the API on Anypoint Exchange?
- A. API Consumer
- B. Both
- C. API Client
- D. None
Answer: A
Explanation:
Correct Answer : API Consumer
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>> API clients are piece of code or programs that use the client credentials of API consumer but does not directly interact with Anypoint Exchange to get the access
>> API consumer is the one who should get registered and request access to API and then API client needs to use those client credentials to hit the APIs So, API consumer is the one who needs to request access on the API from Anypoint Exchange
NEW QUESTION # 101
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