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Following are some new MuleSoft-Platform-Architect-I Real Exam Questions!
NEW QUESTION # 83
A Rate Limiting policy is applied to an API implementation to protect the back-end system. Recently, there have been surges in demand that cause some API client POST requests to the API implementation to be rejected with policy-related errors, causing delays and complications to the API clients.
How should the API policies that are applied to the API implementation be changed to reduce the frequency of errors returned to API clients, while still protecting the back-end system?
- A. Remove the Rate Limiting policy and add an HTTP Caching policy
- B. Keep the Rate Limiting policy and add 9 Client ID Enforcement policy
- C. Remove the Rate Limiting policy and add a Spike Control policy
- D. Keep the Rate Limiting policy and add an SLA-based Spike Control policy
Answer: D
Explanation:
When managing high traffic to an API, especially with POST requests, it is crucial to ensure the API's policies both protect the back-end systems and provide a smooth client experience. Here's the approach to reducing errors:
Rate Limiting Policy: This policy enforces a limit on the number of requests within a defined time period. However, rate limiting alone may cause clients to hit limits during demand surges, leading to errors.
Adding an SLA-based Spike Control Policy:
Spike Control is designed to handle sudden increases in traffic by smoothing out bursts of requests, which is particularly useful during high-demand periods.
By configuring SLA-based Spike Control, you can define thresholds for specific client tiers. For instance, premium clients might have higher limits or more flexibility in traffic bursts than standard clients.
Why Option D is Correct:
Keeping the Rate Limiting policy continues to provide baseline protection for the back-end.
Adding the SLA-based Spike Control policy allows for differentiated control, where requests are queued or delayed during bursts rather than outright rejected. This approach significantly reduces error responses to clients while still controlling overall traffic.
of Incorrect Options:
Option A (adding Client ID Enforcement) would not reduce errors related to traffic surges.
Option B (HTTP Caching) is not applicable as caching is generally ineffective for non-idempotent requests like POST.
Option C (only Spike Control without Rate Limiting) may leave the back-end system vulnerable to sustained high traffic levels, reducing protection.
Reference
For more information on configuring Rate Limiting and SLA-based Spike Control policies, refer to MuleSoft documentation on API Policies and Rate Limiting.
NEW QUESTION # 84
An existing Quoting API is defined in RAML and used by REST clients for interacting with the quoting engine. Currently there is a resource defined in the RAML that allows the creation of quotes; however, a new requirement was just received to allow for the updating of existing quotes.
Which two actions need to be taken to facilitate this change so it can be processed?
Choose 2 answers
- A. Update the RAML with new method details for the update request
- B. Deprecate existing versions of the API in Exchange
- C. Remove the old client applications and create new client applications to account for the changes
- D. Add a new API policy to API Manager to allow access to the updated endpoint
- E. Update the API implementation to accommodate the new update request
Answer: A,E
Explanation:
To accommodate the new requirement of allowing updates to existing quotes, the following actions should be taken:
Update the RAML Definition (Option C):
The RAML specification defines the structure and behavior of the API. Adding a new method (such as PUT or PATCH) for updating quotes requires modifying the RAML to include this new endpoint. This ensures the API specification is up-to-date and accurately reflects the new functionality.
Update the API Implementation (Option A):
Once the RAML is updated, the backend API implementation must also be modified to handle the new update requests. This could involve adding logic to process and validate update requests, connect to necessary backend resources, and apply the changes to existing quotes.
of Incorrect Options:
Option B (removing and creating new clients) is unnecessary; client applications can remain as they are, with no need for complete replacement.
Option D (deprecating existing versions) may not be required if backward compatibility is maintained.
Option E (adding a new policy) does not facilitate functional changes and is unrelated to implementing the update feature.
Reference
For more details on updating RAML definitions and API implementations, refer to MuleSoft's API Design documentation on RAML and RESTful API practices.
NEW QUESTION # 85
A company has created a successful enterprise data model (EDM). The company is committed to building an application network by adopting modern APIs as a core enabler of the company's IT operating model. At what API tiers (experience, process, system) should the company require reusing the EDM when designing modern API data models?
- A. At the experience and process tiers
- B. At the process and system tiers
- C. At the experience, process, and system tiers
- D. At the experience and system tiers
Answer: B
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.
NEW QUESTION # 86
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. The HTTP response size
- B. A correlation ID that should be sent in the next request
- C. The error codes that result from throttling
- D. The remaining capacity allowed by the API implementation
Answer: D
Explanation:
Correct Answer : 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 # 87
An IT Security Compliance Auditor is assessing which nonfunctional requirements (NFRs) are already being implemented to meet security measures.
* The Web API has Rate-Limiting SLA
* Basic Authentication - LDAP
* JSON Threat Protection
* TP Allowlist policies applied
Which two NFRs-are enforced?
- A. The API invocations are coming from a known subnet range
- B. Performance expectations are to be allowed up to 1,000 requests per second
- C. Username/password supported to validate login credentials
- D. Sensitive data is masked to prevent compromising critical information
- E. The API is protected against XML invocation attacks
Answer: A,C
Explanation:
Understanding Nonfunctional Requirements (NFRs):
The NFRs in this context are related to security measures implemented for the Web API, such as rate limiting, LDAP-based authentication, JSON threat protection, and IP allowlist policies.
Evaluating the Options:
Option A (Correct Answer): The IP allowlist policy restricts access to known subnets, ensuring that API invocations come from a defined range of IPs.
Option B (Correct Answer): Basic Authentication with LDAP enforces a username/password validation, satisfying an NFR for identity verification.
Option C: Masking sensitive data is not part of the listed NFRs, as none of the mentioned policies address data masking.
Option D: XML threat protection is not mentioned, so this option is incorrect.
Option E: While rate-limiting implies performance control, it does not directly enforce a specific performance expectation.
Conclusion:
Options A and B are correct as they directly address the implemented security measures related to IP range restrictions and username/password authentication.
Refer to MuleSoft's documentation on API security policies for details on LDAP, rate limiting, and allowlist policies.
NEW QUESTION # 88
A European company has customers all across Europe, and the IT department is migrating from an older platform to MuleSoft. The main requirements are that the new platform should allow redeployments with zero downtime and deployment of applications to multiple runtime versions, provide security and speed, and utilize Anypoint MQ as the message service.
Which runtime plane should the company select based on the requirements without additional network configuration?
- A. MuleSoft-hosted runtime plane (CloudHub)
- B. Anypoint Runtime Fabric on Self-Managed Kubernetes for the runtime plane
- C. Runtime Fabric on VMs / Bare Metal for the runtime plane
- D. Customer-hosted runtime plane
Answer: A
Explanation:
For a European company with requirements such as zero-downtime redeployment, deployment to multiple runtime versions, secure and fast performance, and the use of Anypoint MQ without additional network configuration, CloudHub is the best choice for the following reasons:
Zero-Downtime Redeployment: CloudHub supports zero-downtime deployment, which allows seamless redeployment of applications without impacting availability.
Support for Multiple Runtime Versions: CloudHub allows deploying applications across different Mule runtime versions, giving flexibility to test and migrate applications as needed.
Integrated Anypoint MQ: Anypoint MQ, which is fully integrated with CloudHub, provides reliable messaging across applications. Choosing CloudHub removes the need for additional network configurations, as Anypoint MQ can be directly accessed in this hosted environment.
Security and Performance: CloudHub offers secure networking, automatic scaling, and optimized performance without requiring a complex setup. This is managed by MuleSoft's infrastructure, meeting the speed and security requirements with minimal overhead.
of Incorrect Options:
Option A and D (Runtime Fabric on VMs or Self-Managed Kubernetes): While Runtime Fabric offers flexibility, it requires more complex network and infrastructure configurations, which is not ideal if the company seeks simplicity.
Option B (Customer-hosted): This would require additional network and security configuration, which does not align with the requirement of minimizing setup complexity.
Reference
For more information on CloudHub's capabilities regarding zero-downtime deployments and integration with Anypoint MQ, refer to MuleSoft documentation on CloudHub.
NEW QUESTION # 89
Which of the following best fits the definition of API-led connectivity?
- A. API-led connectivity is a 3-layered architecture covering Experience, Process and System layers
- B. API-led connectivity is a technology which enabled us to implement Experience, Process and System layer based APIs
- C. API-led connectivity is not just an architecture or technology but also a way to organize people and processes for efficient IT delivery in the organization
Answer: C
Explanation:
Correct Answer : API-led connectivity is not just an architecture or technology but also a way to organize people and processes for efficient IT delivery in the organization.
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Reference:
NEW QUESTION # 90
When must an API implementation be deployed to an Anypoint VPC?
- A. When the API implementation must be accessible within a subnet of a restricted customer-hosted network that does not allow public access
- B. When the API Implementation must write to a persistent Object Store
- C. When the API Implementation must invoke publicly exposed services that are deployed outside of CloudHub in a customer- managed AWS instance
- D. When the API implementation must be deployed to a production AWS VPC using the Mule Maven plugin
Answer: C
NEW QUESTION # 91
Refer to the exhibit.
What is a valid API in the sense of API-led connectivity and application networks?
A) Java RMI over TCP
B) Java RMI over TCP
C) CORBA over HOP
D) XML over UDP
- A. Option D
- B. Option B
- C. Option C
- D. Option A
Answer: A
Explanation:
Correct Answer : XML over HTTP
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>> API-led connectivity and Application Networks urge to have the APIs on HTTP based protocols for building most effective APIs and networks on top of them.
>> The HTTP based APIs allow the platform to apply various varities of policies to address many NFRs
>> The HTTP based APIs also allow to implement many standard and effective implementation patterns that adhere to HTTP based w3c rules.
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NEW QUESTION # 92
An organization makes a strategic decision to move towards an IT operating model that emphasizes consumption of reusable IT assets using modern APIs (as defined by MuleSoft).
What best describes each modern API in relation to this new IT operating model?
- A. Each modem API must be treated like a product and designed for a particular target audience (for instance, mobile app developers)
- B. Each modern API must be easy to consume, so should avoid complex authentication mechanisms such as SAML or JWT D
- C. Each modern API must be REST and HTTP based
- D. Each modern API has its own software development lifecycle, which reduces the need for documentation and automation
Answer: A
Explanation:
Correct Answers:
1. Each modern API must be treated like a product and designed for a particular target audience (for instance mobile app developers)
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NEW QUESTION # 93
Version 3.0.1 of a REST API implementation represents time values in PST time using ISO 8601 hh:mm:ss format. The API implementation needs to be changed to instead represent time values in CEST time using ISO 8601 hh:mm:ss format. When following the semver.org semantic versioning specification, what version should be assigned to the updated API implementation?
- A. 3.1.0
- B. 3.0.1
- C. 4.0.0
- D. 3.0.2
Answer: C
Explanation:
Correct Answer : 4.0.0
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As per semver.org semantic versioning specification:
Given a version number MAJOR.MINOR.PATCH, increment the:
- MAJOR version when you make incompatible API changes.
- MINOR version when you add functionality in a backwards compatible manner.
- PATCH version when you make backwards compatible bug fixes.
As per the scenario given in the question, the API implementation is completely changing its behavior. Although the format of the time is still being maintained as hh:mm:ss and there is no change in schema w.r.t format, the API will start functioning different after this change as the times are going to come completely different.
Example: Before the change, say, time is going as 09:00:00 representing the PST. Now on, after the change, the same time will go as 18:00:00 as Central European Summer Time is 9 hours ahead of Pacific Time.
>> This may lead to some uncertain behavior on API clients depending on how they are handling the times in the API response. All the API clients need to be informed that the API functionality is going to change and will return in CEST format. So, this considered as a MAJOR change and the version of API for this new change would be 4.0.0
NEW QUESTION # 94
Refer to the exhibit.
Three business processes need to be implemented, and the implementations need to communicate with several different SaaS applications.
These processes are owned by separate (siloed) LOBs and are mainly independent of each other, but do share a few business entities. Each LOB has one development team and their own budget In this organizational context, what is the most effective approach to choose the API data models for the APIs that will implement these business processes with minimal redundancy of the data models?
A) Build several Bounded Context Data Models that align with coherent parts of the business processes and the definitions of associated business entities
B) Build distinct data models for each API to follow established micro-services and Agile API-centric practices
C) Build all API data models using XML schema to drive consistency and reuse across the organization
D) Build one centralized Canonical Data Model (Enterprise Data Model) that unifies all the data types from all three business processes, ensuring the data model is consistent and non-redundant
- A. Option B
- B. Option A
- C. Option C
- D. Option D
Answer: B
Explanation:
Correct Answer : Build several Bounded Context Data Models that align with coherent parts of the business processes and the definitions of associated business entities.
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>> The options w.r.t building API data models using XML schema/ Agile API-centric practices are irrelevant to the scenario given in the question. So these two are INVALID.
>> Building EDM (Enterprise Data Model) is not feasible or right fit for this scenario as the teams and LOBs work in silo and they all have different initiatives, budget etc.. Building EDM needs intensive coordination among all the team which evidently seems not possible in this scenario.
So, the right fit for this scenario is to build several Bounded Context Data Models that align with coherent parts of the business processes and the definitions of associated business entities.
NEW QUESTION # 95
A retail company is using an Order API to accept new orders. The Order API uses a JMS queue to submit orders to a backend order management service. The normal load for orders is being handled using two (2) CloudHub workers, each configured with 0.2 vCore. The CPU load of each CloudHub worker normally runs well below 70%. However, several times during the year the Order API gets four times (4x) the average number of orders. This causes the CloudHub worker CPU load to exceed 90% and the order submission time to exceed 30 seconds. The cause, however, is NOT the backend order management service, which still responds fast enough to meet the response SLA for the Order API. What is the MOST resource-efficient way to configure the Mule application's CloudHub deployment to help the company cope with this performance challenge?
- A. Permanently increase the number of CloudHub workers by four times (4x) to eight (8) CloudHub workers
- B. Use a vertical CloudHub autoscaling policy that triggers on CPU utilization greater than 70%
- C. Permanently increase the size of each of the two (2) CloudHub workers by at least four times (4x) to one (1) vCore
- D. Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater than 70%
Answer: D
Explanation:
Correct Answer : Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater than 70%
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The scenario in the question is very clearly stating that the usual traffic in the year is pretty well handled by the existing worker configuration with CPU running well below 70%. The problem occurs only "sometimes" occasionally when there is spike in the number of orders coming in.
So, based on above, We neither need to permanently increase the size of each worker nor need to permanently increase the number of workers. This is unnecessary as other than those "occasional" times the resources are idle and wasted.
We have two options left now. Either to use horizontal Cloudhub autoscaling policy to automatically increase the number of workers or to use vertical Cloudhub autoscaling policy to automatically increase the vCore size of each worker.
Here, we need to take two things into consideration:
1. CPU
2. Order Submission Rate to JMS Queue
>> From CPU perspective, both the options (horizontal and vertical scaling) solves the issue. Both helps to bring down the usage below 90%.
>> However, If we go with Vertical Scaling, then from Order Submission Rate perspective, as the application is still being load balanced with two workers only, there may not be much improvement in the incoming request processing rate and order submission rate to JMS queue. The throughput would be same as before. Only CPU utilization comes down.
>> But, if we go with Horizontal Scaling, it will spawn new workers and adds extra hand to increase the throughput as more workers are being load balanced now. This way we can address both CPU and Order Submission rate.
Hence, Horizontal CloudHub Autoscaling policy is the right and best answer.
NEW QUESTION # 96
Which statement is true about identity management and client management on Anypoint Platform?
- A. If an external identity provider is configured, the SAML 2.0 bearer tokens issued by the identity provider cannot be used for invocations of the Anypoint Platform web APIs
- B. Anypoint Platform supports configuring one external identity provider
- C. Both client management and identity management require an identity provider
- D. If an external client provider is configured, it must be configured at the Anypoint Platform organization level and cannot be assigned to individual business groups and environments
Answer: B
Explanation:
Anypoint Platform allows organizations to integrate one external identity provider (IdP) for identity and access management (IAM), supporting SSO and centralized user authentication.
Identity Provider Limit:
Anypoint Platform supports configuring a single IdP for the organization, which can be used to authenticate all users across business groups and environments within that Anypoint organization.
of Correct Answer (C):
Configuring one IdP ensures centralized and secure identity management, aligned with MuleSoft's architecture.
of Incorrect Options:
Option A is incorrect because SAML 2.0 bearer tokens from external IdPs can indeed be used for invoking Anypoint Platform APIs.
Option B is incorrect as client providers can be assigned to specific business groups and environments.
Option D is incorrect since only identity management strictly requires an IdP; client management does not.
Reference
For further details on identity management options, consult MuleSoft documentation on Anypoint Platform's IAM capabilities.
NEW QUESTION # 97
When can CloudHub Object Store v2 be used?
- A. To store an unlimited number of key-value pairs
- B. To store key-value pairs with keys up to 300 characters
- C. To store information in Mule 4 Object Store v1
- D. To store payloads with an average size greater than 15MB
Answer: B
Explanation:
CloudHub Object Store v2 is a managed key-value store provided by MuleSoft to support various use cases where temporary data storage is required. Here's why Option D is correct:
Key Length Support: Object Store v2 allows storage of keys with a length of up to 300 characters, making it suitable for applications needing flexible and descriptive keys.
Limitations on Size:
Object Store v2 is not intended for large payload storage and has a recommended size limit below 10 MB for each value. Payloads exceeding 15 MB may cause performance issues and are better suited to a file storage system or database.
Option B is incorrect because storing payloads above 15 MB exceeds Object Store's optimal usage specifications.
Key-Value Limits: Object Store v2 is designed for moderate, transient storage needs, and does not support unlimited storage. Thus, Option A is incorrect.
Backward Compatibility: Object Store v2 does not support Mule 4 applications running Object Store v1. Option C is incorrect as Object Store v1 and v2 are distinct.
Reference
For more on CloudHub Object Store v2, refer to MuleSoft documentation on Object Store limitations and configuration.
NEW QUESTION # 98
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 B
- B. Option C
- C. Option D
- D. Option A
Answer: A
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 # 99
Which layer in the API-led connectivity focuses on unlocking key systems, legacy systems, data sources etc and exposes the functionality?
- A. System Layer
- B. Process Layer
- C. Experience Layer
Answer: A
Explanation:
Correct Answer : System Layer
The APIs used in an API-led approach to connectivity fall into three categories:
System APIs - these usually access the core systems of record and provide a means of insulating the user from the complexity or any changes to the underlying systems. Once built, many users, can access data without any need to learn the underlying systems and can reuse these APIs in multiple projects.
Process APIs - These APIs interact with and shape data within a single system or across systems (breaking down data silos) and are created here without a dependence on the source systems from which that data originates, as well as the target channels through which that data is delivered.
Experience APIs - Experience APIs are the means by which data can be reconfigured so that it is most easily consumed by its intended audience, all from a common data source, rather than setting up separate point-to-point integrations for each channel. An Experience API is usually created with API-first design principles where the API is designed for the specific user experience in mind.
NEW QUESTION # 100
4A developer for a transportation organization is implementing exactly one processing functionality in a Reservation Mule application to process and store passenger records. This Reservation application will be deployed to multiple CloudHub workers/replicas. It is possible that several external systems could send duplicate passenger records to the Reservation application.
An appropriate storage mechanism must be selected to help the Reservation application process each passenger record exactly once as much as possible. The selected storage mechanism must be shared by all the CloudHub workers/replicas in order to synchronize the state information to assist attempting exactly once processing of each passenger record by the deployed Reservation Mule application.
Which type of simple storage mechanism in Anypoint Platform allows the Reservation Mule application to update and share data between the CloudHub workers/replicas exactly once, with minimal development effort?
- A. Persistent Object Store
- B. In-memory Mule Object Store
- C. Non-persistent Object Store
- D. Runtime Fabric Object Store
Answer: A
Explanation:
Processing Requirements and Storage Mechanism:
The Reservation Mule application will be deployed to multiple CloudHub workers/replicas, meaning that each worker must share state information to handle records exactly once. This requires a shared storage mechanism where state can be stored and accessed by multiple instances to avoid duplicate processing of the same records.
A Persistent Object Store in Anypoint Platform can be used to store records in a way that is accessible across multiple workers, providing a reliable mechanism for "exactly once" processing.
Evaluating the Options:
Option A (Correct Answer): A Persistent Object Store is designed to retain data across different application instances and can be shared by all workers on CloudHub. It helps achieve idempotency by ensuring that a record is processed exactly once.
Option B: Runtime Fabric Object Store is used for applications deployed in Anypoint Runtime Fabric, not CloudHub. This option would not be compatible with the CloudHub deployment.
Option C: A Non-persistent Object Store does not retain data across application restarts or different instances, making it unsuitable for the requirement of synchronized storage for exactly-once processing.
Option D: An In-memory Mule Object Store is local to each worker and is not shared across instances, so it does not meet the requirement for a shared storage mechanism accessible to all CloudHub workers.
Conclusion:
Option A is the correct answer, as a Persistent Object Store allows data sharing across multiple CloudHub workers, enabling them to synchronize and achieve "exactly once" processing of passenger records with minimal development effort.
Refer to MuleSoft's documentation on Object Store configurations and usage for best practices on handling state across distributed instances.
NEW QUESTION # 101
An API experiences a high rate of client requests (TPS) vwth small message paytoads. How can usage limits be imposed on the API based on the type of client application?
- A. Use an SLA-based rate limiting policy and assign a client application to a matching SLA tier based on its type
- B. Use a spike control policy that limits the number of requests for each client application type
- C. Use a cross-origin resource sharing (CORS) policy to limit resource sharing between client applications, configured by the client application type
- D. Use a rate limiting policy and a client ID enforcement policy, each configured by the client application type
Answer: A
Explanation:
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
NEW QUESTION # 102
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 Inventory system API implementation
- B. In the Order API implementation
- C. In the inventory database
- 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 # 103
How can the application of a rate limiting API policy be accurately reflected in the RAML definition of an API?
- A. By refining the response definitions by adding the out-of-the-box Anypoint Platform rate-limit-enforcement securityScheme with description, type, and example
- B. By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example
- C. By refining the resource definitions by adding a description of the rate limiting policy behavior
- D. By refining the request definitions by adding a remaining Requests query parameter with description, type, and example
Answer: B
Explanation:
Correct Answer : By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example
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Reference:
https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling#response-headers
https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling-sla-based-policies#response-headers
NEW QUESTION # 104
An operations team is analyzing the effort needed to set up monitoring of their application network. They are looking at which API invocation metrics can be used to identify and predict trouble without having to write custom scripts or install additional analytics software or tools.
Which type of metrics can satisfy this goal of directly identifying and predicting failures?
- A. The effectiveness of the application network based on the level of reuse
- B. The ROI from each APT invocation
- C. The number and types of API policy violations per day
- D. The number and types of past API invocations across the application network
Answer: C
Explanation:
To monitor an application network and predict issues without custom scripts, policy violation metrics are critical. They provide insights into potential problems by tracking instances where API usage does not conform to defined policies. Here's why this approach is suitable:
Predictive Monitoring:
Tracking API policy violations (such as rate limits or spike controls being hit) can indicate surges in traffic or misuse, which may lead to throttling or service degradation if not addressed.
By monitoring these violations, teams can proactively adjust limits or optimize API handling to prevent actual failures.
No Custom Scripting Needed:
Policy violation metrics are available within MuleSoft's Anypoint Monitoring, meaning there's no need to implement custom solutions or external tools to gather and interpret this data.
of Incorrect Options:
Option B (effectiveness based on reuse) does not directly predict failures.
Option C (past invocation counts) offers historical usage data but does not inherently identify issues.
Option D (ROI from API invocation) is a business metric and does not provide technical insights for failure prediction.
Reference
For more details on leveraging policy violation metrics for proactive monitoring, refer to MuleSoft documentation on Anypoint Monitoring.
NEW QUESTION # 105
An Order API must be designed that contains significant amounts of integration logic and involves the invocation of the Product API.
The power relationship between Order API and Product API is one of "Customer/Supplier", because the Product API is used heavily throughout the organization and is developed by a dedicated development team located in the office of the CTO.
What strategy should be used to deal with the API data model of the Product API within the Order API?
- A. Convince the development team of the Product API to adopt the API data model of the Order API such that the integration logic of the Order API can work with one consistent internal data model
- B. Implement an anti-corruption layer in the Order API that transforms the Product API data model into internal data types of the Order API
- C. Start an organization-wide data modeling initiative that will result in an Enterprise Data Model that will then be used in both the Product API and the Order API
- D. Work with the API data types of the Product API directly when implementing the integration logic of the Order API such that the Order API uses the same (unchanged) data types as the Product API
Answer: B
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.
NEW QUESTION # 106
What is most likely NOT a characteristic of an integration test for a REST API implementation?
- A. The test runs immediately after the Mule application has been compiled and packaged
- B. The test prepares a known request payload and validates the response payload
- C. The test needs all source and/or target systems configured and accessible
- D. The test is triggered by an external HTTP request
Answer: A
Explanation:
Correct Answer : The test runs immediately after the Mule application has been compiled and packaged
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>> Integration tests are the last layer of tests we need to add to be fully covered.
>> These tests actually run against Mule running with your full configuration in place and are tested from external source as they work in PROD.
>> These tests exercise the application as a whole with actual transports enabled. So, external systems are affected when these tests run.
So, these tests do NOT run immediately after the Mule application has been compiled and packaged.
FYI... Unit Tests are the one that run immediately after the Mule application has been compiled and packaged.
NEW QUESTION # 107
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