Exam Questions and Answers for MuleSoft-Platform-Architect-I Study Guide Questions and Answers!
Salesforce Certified MuleSoft Platform Architect I Certification Sample Questions and Practice Exam
NEW QUESTION # 30
A Mule application implements an API. The Mule application has an HTTP Listener whose connector configuration sets the HTTPS protocol and hard-codes the port value. The Mule application is deployed to an Anypoint VPC and uses the CloudHub 1.0 Shared Load Balancer (SLB) for all incoming traffic.
Which port number must be assigned to the HTTP Listener's connector configuration so that the Mule application properly receives HTTPS API invocations routed through the SLB?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: D
Explanation:
When using CloudHub 1.0's Shared Load Balancer (SLB) for a Mule application configured with HTTPS in an Anypoint VPC, specific ports must be configured for the application to correctly route incoming traffic:
Port Requirement for SLB:
The CloudHub Shared Load Balancer for HTTPS traffic requires that applications listen on port 8092 for secure (HTTPS) communication. This port is reserved specifically for SSL traffic when using SLB with Anypoint VPCs.
Why Option B is Correct:
Setting the HTTP Listener's connector configuration to 8092 aligns with CloudHub requirements for HTTPS via the Shared Load Balancer.
of Incorrect Options:
Option A (8082) is used for non-HTTPS (HTTP) traffic.
Option C (80) and Option D (443) are standard web ports but are not applicable within CloudHub SLB's internal configuration for VPC routing.
Reference
For more information on the Shared Load Balancer port configurations, refer to MuleSoft's documentation on CloudHub and VPC load balancer requirements.
NEW QUESTION # 31
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 A
- B. Option B
- C. Option C
- D. Option D
Answer: A
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 # 32
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 # 33
A customer wants to monitor and gain insights about the number of requests coming in a given time period as well as to measure key performance indicators (response times, CPU utilization, number of active APIs).
Which tool provides these data insights?
- A. Functional Monitoring
- B. APT Manager
- C. Anypoint Monitoring
- D. Runtime Alerts
Answer: C
Explanation:
Understanding Anypoint Monitoring and Its Capabilities:
Anypoint Monitoring provides comprehensive visibility into Mule applications, offering metrics and analytics such as request counts, response times, CPU utilization, memory usage, and other key performance indicators (KPIs). This tool is designed to help teams monitor API usage, troubleshoot issues, and optimize application performance.
Evaluating the Options:
Option A (Correct Answer): Anypoint Monitoring is the ideal tool for this requirement. It provides real-time insights into metrics such as the number of requests, response times, CPU utilization, and active API usage.
Option B (API Manager): API Manager focuses on API lifecycle management, including applying policies, managing contracts, and setting access controls. It does not provide performance monitoring or KPI tracking.
Option C (Runtime Alerts): Runtime Alerts can notify users of specific conditions, like high CPU usage, but they do not provide a full suite of metrics or insights over a given time period.
Option D (Functional Monitoring): Functional Monitoring focuses on functional testing of APIs rather than performance and usage metrics. It does not provide continuous KPI tracking.
Conclusion:
Option A is the correct answer. Anypoint Monitoring is the most suitable tool to track the specified metrics, providing detailed insights into API requests, response times, CPU usage, and active API counts.
For further details, refer to MuleSoft's Anypoint Monitoring documentation on configuring dashboards and tracking performance metrics.
NEW QUESTION # 34
A Mule application exposes an HTTPS endpoint and is deployed to the CloudHub Shared Worker Cloud. All traffic to that Mule application must stay inside the AWS VPC.
To what TCP port do API invocations to that Mule application need to be sent?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: B
Explanation:
Correct Answer : 8082
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>> 8091 and 8092 ports are to be used when keeping your HTTP and HTTPS app private to the LOCAL VPC respectively.
>> Above TWO ports are not for Shared AWS VPC/ Shared Worker Cloud.
>> 8081 is to be used when exposing your HTTP endpoint app to the internet through Shared LB
>> 8082 is to be used when exposing your HTTPS endpoint app to the internet through Shared LB So, API invocations should be sent to port 8082 when calling this HTTPS based app.
Reference:
https://docs.mulesoft.com/runtime-manager/cloudhub-networking-guide
https://help.mulesoft.com/s/article/Configure-Cloudhub-Application-to-Send-a-HTTPS-Request-Directly-to-Another-Cloudhub-Application
https://help.mulesoft.com/s/question/0D52T00004mXXULSA4/multiple-http-listerners-on-cloudhub-one-with-port-9090
NEW QUESTION # 35
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 A
- C. Option C
- D. Option D
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 # 36
What best explains the use of auto-discovery in API implementations?
- A. It makes API Manager aware of API implementations and hence enables it to enforce policies
- B. It enables Anypoint Analytics to gain insight into the usage of APIs
- C. It enables Anypoint Exchange to discover assets and makes them available for reuse
- D. It enables Anypoint Studio to discover API definitions configured in Anypoint Platform
Answer: A
Explanation:
Correct Answer : It makes API Manager aware of API implementations and hence enables it to enforce policies.
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>> API Autodiscovery is a mechanism that manages an API from API Manager by pairing the deployed application to an API created on the platform.
>> API Management includes tracking, enforcing policies if you apply any, and reporting API analytics.
>> Critical to the Autodiscovery process is identifying the API by providing the API name and version.
Reference:
https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-concept
https://docs.mulesoft.com/api-manager/1.x/api-auto-discovery
https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-concept
NEW QUESTION # 37
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 invoke publicly exposed services that are deployed outside of CloudHub in a customer- managed AWS instance
- C. When the API implementation must be deployed to a production AWS VPC using the Mule Maven plugin
- D. When the API Implementation must write to a persistent Object Store
Answer: B
NEW QUESTION # 38
When can CloudHub Object Store v2 be used?
- A. To store information in Mule 4 Object Store v1
- B. To store an unlimited number of key-value pairs
- C. To store key-value pairs with keys up to 300 characters
- D. To store payloads with an average size greater than 15MB
Answer: C
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 # 39
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 error codes that result from throttling
- B. A correlation ID that should be sent in the next request
- 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 # 40
An organization is implementing a Quote of the Day API that caches today's quote.
What scenario can use the GoudHub Object Store via the Object Store connector to persist the cache's state?
- A. When there is one CloudHub deployment of the API implementation to three CloudHub workers that must share the cache state
- B. When there is one deployment of the API implementation to CloudHub and anottV deployment to a customer-hosted Mule runtime that must share the cache state
- C. When there are three CloudHub deployments of the API implementation to three separate CloudHub regions that must share the cache state
- D. When there are two CloudHub deployments of the API implementation by two Anypoint Platform business groups to the same CloudHub region that must share the cache state
Answer: A
Explanation:
Correct Answer : When there is one CloudHub deployment of the API implementation to three CloudHub workers that must share the cache state.
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Key details in the scenario:
>> Use the CloudHub Object Store via the Object Store connector
Considering above details:
>> CloudHub Object Stores have one-to-one relationship with CloudHub Mule Applications.
>> We CANNOT use an application's CloudHub Object Store to be shared among multiple Mule applications running in different Regions or Business Groups or Customer-hosted Mule Runtimes by using Object Store connector.
>> If it is really necessary and very badly needed, then Anypoint Platform supports a way by allowing access to CloudHub Object Store of another application using Object Store REST API. But NOT using Object Store connector.
So, the only scenario where we can use the CloudHub Object Store via the Object Store connector to persist the cache's state is when there is one CloudHub deployment of the API implementation to multiple CloudHub workers that must share the cache state.
NEW QUESTION # 41
A new upstream API Is being designed to offer an SLA of 500 ms median and 800 ms maximum (99th percentile) response time. The corresponding API implementation needs to sequentially invoke 3 downstream APIs of very similar complexity.
The first of these downstream APIs offers the following SLA for its response time: median: 100 ms, 80th percentile: 500 ms, 95th percentile: 1000 ms.
If possible, how can a timeout be set in the upstream API for the invocation of the first downstream API to meet the new upstream API's desired SLA?
- A. Do not set a timeout; the Invocation of this API Is mandatory and so we must wait until it responds
- B. Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to complete
- C. Set a timeout of 50 ms; this times out more invocations of that API but gives additional room for retries
- D. No timeout is possible to meet the upstream API's desired SLA; a different SLA must be negotiated with the first downstream API or invoke an alternative API
Answer: B
Explanation:
Correct Answer : Set a timeout of 100ms; that leaves 400ms for other two downstream APIs to complete
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Key details to take from the given scenario:
>> Upstream API's designed SLA is 500ms (median). Lets ignore maximum SLA response times.
>> This API calls 3 downstream APIs sequentially and all these are of similar complexity.
>> The first downstream API is offering median SLA of 100ms, 80th percentile: 500ms; 95th percentile: 1000ms.
Based on the above details:
>> We can rule out the option which is suggesting to set 50ms timeout. Because, if the median SLA itself being offered is 100ms then most of the calls are going to timeout and time gets wasted in retried them and eventually gets exhausted with all retries. Even if some retries gets successful, the remaining time wont leave enough room for 2nd and 3rd downstream APIs to respond within time.
>> The option suggesting to NOT set a timeout as the invocation of this API is mandatory and so we must wait until it responds is silly. As not setting time out would go against the good implementation pattern and moreover if the first API is not responding within its offered median SLA 100ms then most probably it would either respond in 500ms (80th percentile) or 1000ms (95th percentile). In BOTH cases, getting a successful response from 1st downstream API does NO GOOD because already by this time the Upstream API SLA of 500 ms is breached. There is no time left to call 2nd and 3rd downstream APIs.
>> It is NOT true that no timeout is possible to meet the upstream APIs desired SLA.
As 1st downstream API is offering its median SLA of 100ms, it means MOST of the time we would get the responses within that time. So, setting a timeout of 100ms would be ideal for MOST calls as it leaves enough room of 400ms for remaining 2 downstream API calls.
NEW QUESTION # 42
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 error codes that result from throttling
- B. A correlation ID that should be sent in the next request
- C. The HTTP response size
- 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 # 43
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 B
- B. Option A
- C. Option C
- D. Option D
Answer: A
Explanation:
Correct Answe r: 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 # 44
Select the correct Owner-Layer combinations from below options
- A. 1. App Developers owns and focuses on Experience Layer APIs
2. LOB IT owns and focuses on Process Layer APIs
3. Central IT owns and focuses on System Layer APIs - B. 1. Central IT owns and focuses on Experience Layer APIs
2. LOB IT owns and focuses on Process Layer APIs
3. App Developers owns and focuses on System Layer APIs - C. 1. App Developers owns and focuses on Experience Layer APIs
2. Central IT owns and focuses on Process Layer APIs
3. LOB IT owns and focuses on System Layer APIs
Answer: A
Explanation:
Correct Answer :
1. App Developers owns and focuses on Experience Layer APIs
2. LOB IT owns and focuses on Process Layer APIs
3. Central IT owns and focuses on System Layer APIs
Reference:
https://blogs.mulesoft.com/biz/api/experience-api-ownership/
https://blogs.mulesoft.com/biz/api/process-api-ownership/
https://blogs.mulesoft.com/biz/api/system-api-ownership/
NEW QUESTION # 45
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. 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
- B. The System APIs should expose all back-end system fields
- C. The data model should define its own naming convention, and not follow the same naming as the back-end systems
- D. The data model of the System APIs should make use of data types that approximately mirror those from the back-end systems
Answer: D
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 # 46
An organization wants MuleSoft-hosted runtime plane features (such as HTTP load balancing, zero downtime, and horizontal and vertical scaling) in its Azure environment. What runtime plane minimizes the organization's effort to achieve these features?
- A. A hybrid combination of customer-hosted and MuleSoft-hosted Mule runtimes
- B. Anypoint Platform for Pivotal Cloud Foundry
- C. CloudHub
- D. Anypoint Runtime Fabric
Answer: D
Explanation:
Correct Answer : Anypoint Runtime Fabric
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>> When a customer is already having an Azure environment, It is not at all an ideal approach to go with hybrid model having some Mule Runtimes hosted on Azure and some on MuleSoft. This is unnecessary and useless.
>> CloudHub is a Mulesoft-hosted Runtime plane and is on AWS. We cannot customize to point CloudHub to customer's Azure environment.
>> Anypoint Platform for Pivotal Cloud Foundry is specifically for infrastructure provided by Pivotal Cloud Foundry
>> Anypoint Runtime Fabric is right answer as it is a container service that automates the deployment and orchestration of Mule applications and API gateways. Runtime Fabric runs within a customer-managed infrastructure on AWS, Azure, virtual machines (VMs), and bare-metal servers.
-Some of the capabilities of Anypoint Runtime Fabric include:
-Isolation between applications by running a separate Mule runtime per application.
-Ability to run multiple versions of Mule runtime on the same set of resources.
-Scaling applications across multiple replicas.
-Automated application fail-over.
-Application management with Anypoint Runtime Manager.
NEW QUESTION # 47
How are an API implementation, API client, and API consumer combined to invoke and process an API?
- A. The ApI consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation
- B. The API consumer creates an API implementation, which receives API invocations from an API such that they are processed for an API client
- C. The API client creates an API consumer, which receives API invocations from an API such that they are processed for an API implementation
- D. The ApI client creates an API consumer, which sends API invocations to an API such that they are processed by an API implementation
Answer: A
Explanation:
Correct Answer : The API consumer creates an API client, which sends API invocations to an API such that they are processed by an API implementation
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Terminology:
>> API Client - It is a piece of code or program the is written to invoke an API
>> API Consumer - An owner/entity who owns the API Client. API Consumers write API clients.
>> API - The provider of the API functionality. Typically an API Instance on API Manager where they are managed and operated.
>> API Implementation - The actual piece of code written by API provider where the functionality of the API is implemented. Typically, these are Mule Applications running on Runtime Manager.
NEW QUESTION # 48
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