[Dec 07, 2023] Valid MCPA-Level-1-Maintenance Test Answers & MuleSoft MCPA-Level-1-Maintenance Exam PDF
Realistic MCPA-Level-1-Maintenance Exam Dumps with Accurate & Updated Questions
MuleSoft MCPA-Level-1-Maintenance exam is a certification exam designed to test the knowledge of MuleSoft Certified Platform Architects who have already passed the MCPA-Level-1 exam. MCPA-Level-1-Maintenance exam is focused on testing the candidate's knowledge of the latest MuleSoft platform updates, new features, and best practices for maintaining and supporting MuleSoft applications.
NEW QUESTION # 45
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:
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 # 46
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 producer should be requested to run the old version in parallel with the new one
- D. The API client code only needs to be changed if it needs to take advantage of the new features
Answer: D
NEW QUESTION # 47
A REST API is being designed to implement a Mule application.
What standard interface definition language can be used to define REST APIs?
- A. Web Service Definition Language(WSDL)
- B. YAML
- C. AsyncAPI Specification
- D. OpenAPI Specification (OAS)
Answer: D
NEW QUESTION # 48
What is true about where an API policy is defined in Anypoint Platform and how it is then applied to API instances?
- A. The API policy is defined in API Manager, and then applied to ALL API instances in the specified environment
- B. The API policy Is defined In API Manager for a specific API Instance, and then ONLY applied to the specific API instance
- C. The API policy Is defined in API Manager and then automatically applied to ALL API instances
- D. The API policy Is defined In Runtime Manager as part of the API deployment to a Mule runtime, and then ONLY applied to the specific API Instance
Answer: B
Explanation:
The API policy is defined in API Manager for a specific API instance, and then ONLY applied to the specific API instance.
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>> Once our API specifications are ready and published to Exchange, we need to visit API Manager and register an API instance for each API.
>> API Manager is the place where management of API aspects takes place like addressing NFRs by enforcing policies on them.
>> We can create multiple instances for a same API and manage them differently for different purposes.
>> One instance can have a set of API policies applied and another instance of same API can have different set of policies applied for some other purpose.
>> These APIs and their instances are defined PER environment basis. So, one need to manage them seperately in each environment.
>> We can ensure that same configuration of API instances (SLAs, Policies etc..) gets promoted when promoting to higher environments using platform feature. But this is optional only. Still one can change them per environment basis if they have to.
>> Runtime Manager is the place to manage API Implementations and their Mule Runtimes but NOT APIs itself. Though API policies gets executed in Mule Runtimes, We CANNOT enforce API policies in Runtime Manager. We would need to do that via API Manager only for a cherry picked instance in an environment.
So, based on these facts, right statement in the given choices is - "The API policy is defined in API Manager for a specific API instance, and then ONLY applied to the specific API instance".
NEW QUESTION # 49
What Mule application deployment scenario requires using Anypoint Platform Private Cloud Edition or Anypoint Platform for Pivotal Cloud Foundry?
- A. When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data
- B. When ALL backend systems in the application network are deployed in the organization's intranet
- C. When it Is required to make ALL applications highly available across multiple data centers
- D. When it is required that ALL APIs are private and NOT exposed to the public cloud
Answer: A
Explanation:
When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data.
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We need NOT require to use Anypoint Platform PCE or PCF for the below. So these options are OUT.
>> We can make ALL applications highly available across multiple data centers using CloudHub too.
>> We can use Anypoint VPN and tunneling from CloudHub to connect to ALL backend systems in the application network that are deployed in the organization's intranet.
>> We can use Anypoint VPC and Firewall Rules to make ALL APIs private and NOT exposed to the public cloud.
Only valid reason in the given options that requires to use Anypoint Platform PCE/ PCF is - When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data.
NEW QUESTION # 50
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. None
- C. API Client
- D. Both
Answer: A
Explanation:
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 # 51
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 x-ratelimit-* response headers with description, type, and example
- B. By refining the response definitions by adding the out-of-the-box Anypoint Platform rate-limit-enforcement securityScheme with description, type, and example
- C. By refining the request definitions by adding a remaining Requests query parameter with description, type, and example
- D. By refining the resource definitions by adding a description of the rate limiting policy behavior
Answer: A
Explanation:
By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example
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References:
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 # 52
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 the API Manager Properties tab, then promote the Mule API implementation to the Production environment using API Manager
- B. 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
- C. 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.
- D. Modify the Mule API implementation's properties in Anypoint Exchange, then promote the Mule API implementation to the Production environment using Runtime Manager
Answer: C
Explanation:
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 # 53
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 API is invoked by an unrecognized API client
- B. When the API receives a very high number of API invocations
- C. When a particular API client invokes the API too often within a given time period
- D. When the response time of API invocations exceeds a threshold
Answer: D
Explanation:
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 # 54
When using CloudHub with the Shared Load Balancer, what is managed EXCLUSIVELY by the API implementation (the Mule application) and NOT by Anypoint Platform?
- A. The logging configuration that enables log entries to be visible in Runtime Manager
- B. The assignment of each HTTP request to a particular CloudHub worker
- C. The SSL certificates used by the API implementation to expose HTTPS endpoints
- D. The number of DNS entries allocated to the API implementation
Answer: C
Explanation:
The SSL certificates used by the API implementation to expose HTTPS endpoints
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>> The assignment of each HTTP request to a particular CloudHub worker is taken care by Anypoint Platform itself. We need not manage it explicitly in the API implementation and in fact we CANNOT manage it in the API implementation.
>> The logging configuration that enables log entries to be visible in Runtime Manager is ALWAYS managed in the API implementation and NOT just for SLB. So this is not something we do EXCLUSIVELY when using SLB.
>> We DO NOT manage the number of DNS entries allocated to the API implementation inside the code.
Anypoint Platform takes care of this.
It is the SSL certificates used by the API implementation to expose HTTPS endpoints that is to be managed EXCLUSIVELY by the API implementation. Anypoint Platform does NOT do this when using SLBs.
NEW QUESTION # 55
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 D
- B. Option A
- C. Option B
- D. Option C
Answer: B
Explanation:
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 # 56
A company wants to move its Mule API implementations into production as quickly as possible. To protect access to all Mule application data and metadata, the company requires that all Mule applications be deployed to the company's customer-hosted infrastructure within the corporate firewall. What combination of runtime plane and control plane options meets these project lifecycle goals?
- A. Manually provisioned customer-hosted runtime plane and MuleSoft-hosted control plane
- B. MuleSoft-hosted runtime plane and customer-hosted control plane
- C. Manually provisioned customer-hosted runtime plane and customer-hosted control plane
- D. iPaaS provisioned customer-hosted runtime plane and MuleSoft-hosted control plane
Answer: C
Explanation:
Manually provisioned customer-hosted runtime plane and customer-hosted control plane
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There are two key factors that are to be taken into consideration from the scenario given in the question.
>> Company requires both data and metadata to be resided within the corporate firewall
>> Company would like to go with customer-hosted infrastructure.
Any deployment model that is to deal with the cloud directly or indirectly (Mulesoft-hosted or Customer's own cloud like Azure, AWS) will have to share atleast the metadata.
Application data can be controlled inside firewall by having Mule Runtimes on customer hosted runtime plane. But if we go with Mulsoft-hosted/ Cloud-based control plane, the control plane required atleast some minimum level of metadata to be sent outside the corporate firewall.
As the customer requirement is pretty clear about the data and metadata both to be within the corporate firewall, even though customer wants to move to production as quickly as possible, unfortunately due to the nature of their security requirements, they have no other option but to go with manually provisioned customer-hosted runtime plane and customer-hosted control plane.
NEW QUESTION # 57
The application network is recomposable: it is built for change because it "bends but does not break"
- A. FALSE
- B. TRUE
Answer: B
Explanation:
Explanation
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>> Application Network is a disposable architecture.
>> Which means, it can be altered without disturbing entire architecture and its components.
>> It bends as per requirements or design changes but does not break
NEW QUESTION # 58
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. IPwhitellst
- B. Client ID enforcement
- C. OAuth 2.0 access token enforcement
- D. JSON threat protection
Answer: A
Explanation:
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 # 59
An API client calls one method from an existing API implementation. The API implementation is later updated. What change to the API implementation would require the API client's invocation logic to also be updated?
- A. When a new required field is added to the method called by the API client
- B. When a new method is added to the resource used by the API client
- C. When the data type of the response is changed for the method called by the API client
- D. When a child method is added to the method called by the API client
Answer: A
Explanation:
When a new required field is added to the method called by the API client
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>> Generally, the logic on API clients need to be updated when the API contract breaks.
>> When a new method or a child method is added to an API , the API client does not break as it can still continue to use its existing method. So these two options are out.
>> We are left for two more where "datatype of the response if changed" and "a new required field is added".
>> Changing the datatype of the response does break the API contract. However, the question is insisting on the "invocation" logic and not about the response handling logic. The API client can still invoke the API successfully and receive the response but the response will have a different datatype for some field.
>> Adding a new required field will break the API's invocation contract. When adding a new required field, the API contract breaks the RAML or API spec agreement that the API client/API consumer and API provider has between them. So this requires the API client invocation logic to also be updated.
NEW QUESTION # 60
Which of the following best fits the definition of API-led connectivity?
- A. API-led connectivity is a technology which enabled us to implement Experience, Process and System layer based APIs
- B. API-led connectivity is a 3-layered architecture covering Experience, Process and System layers
- 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:
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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NEW QUESTION # 61
Due to a limitation in the backend system, a system API can only handle up to 500 requests per second. What is the best type of API policy to apply to the system API to avoid overloading the backend system?
- A. Spike control
- B. HTTP caching
- C. Rate limiting - SLA based
- D. Rate limiting
Answer: A
Explanation:
Spike control
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>> First things first, HTTP Caching policy is for purposes different than avoiding the backend system from overloading. So this is OUT.
>> Rate Limiting and Throttling/ Spike Control policies are designed to limit API access, but have different intentions.
>> Rate limiting protects an API by applying a hard limit on its access.
>> Throttling/ Spike Control shapes API access by smoothing spikes in traffic.
That is why, Spike Control is the right option.
NEW QUESTION # 62
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. Use a CloudHub autoscaling policy to increase the size of the CloudHub worker
- B. Increase the number of CloudHub workers
- C. se a CloudHub autoscaling policy to add CloudHub workers
- D. Increase the size of the CloudHub worker(s)
Answer: B
Explanation:
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 # 63
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. Invoke the system API deployed to the primary environment, and if it fails, invoke the system API deployed to the DR environment
- B. 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
- C. 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
- D. Invoke ONLY the system API deployed to the primary environment, and add timeout and retry logic to avoid intermittent failures
Answer: C
Explanation:
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 # 64
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 API's 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 producer should be contacted to understand the change to existing functionality
- B. The update should be identified as a project risk and full regression testing of the functionality that uses this API should be run
- C. The API producer should be requested to run the old version in parallel with the new one
- D. The API client code ONLY needs to be changed if it needs to take advantage of new features
Answer: D
NEW QUESTION # 65
A system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. A process API is a client to the system API and is being rate limited by the system API, with different limits in each of the environments. The system API's DR environment provides only 20% of the rate limiting offered by the primary environment. What is the best API fault-tolerant invocation strategy to reduce overall errors in the process API, given these conditions and constraints?
- A. Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke a copy of the process API deployed to the DR environment
- B. Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the system API deployed to the DR environment
- C. In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment; add timeout and retry logic to the process API to avoid intermittent failures; add logic to the process API to combine the results
- D. Invoke the system API deployed to the primary environment; add retry logic to the process API to handle intermittent failures by invoking the system API deployed to the DR environment
Answer: B
Explanation:
Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the system API deployed to the DR environment
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There is one important consideration to be noted in the question which is - System API in DR environment provides only 20% of the rate limiting offered by the primary environment. So, comparitively, very less calls will be allowed into the DR environment API opposed to its primary environment. With this in mind, lets analyse what is the right and best fault-tolerant invocation strategy.
1. Invoking both the system APIs in parallel is definitely NOT a feasible approach because of the 20% limitation we have on DR environment. Calling in parallel every time would easily and quickly exhaust the rate limits on DR environment and may not give chance to genuine intermittent error scenarios to let in during the time of need.
2. Another option given is suggesting to add timeout and retry logic to process API while invoking primary environment's system API. This is good so far. However, when all retries failed, the option is suggesting to invoke the copy of process API on DR environment which is not right or recommended. Only system API is the one to be considered for fallback and not the whole process API. Process APIs usually have lot of heavy orchestration calling many other APIs which we do not want to repeat again by calling DR's process API. So this option is NOT right.
3. One more option given is suggesting to add the retry (no timeout) logic to process API to directly retry on DR environment's system API instead of retrying the primary environment system API first. This is not at all a proper fallback. A proper fallback should occur only after all retries are performed and exhausted on Primary environment first. But here, the option is suggesting to directly retry fallback API on first failure itself without trying main API. So, this option is NOT right too.
This leaves us one option which is right and best fit.
- Invoke the system API deployed to the primary environment
- Add Timeout and Retry logic on it in process API
- If it fails even after all retries, then invoke the system API deployed to the DR environment.
NEW QUESTION # 66
What is typically NOT a function of the APIs created within the framework called API-led connectivity?
- A. They provide an additional layer of resilience on top of the underlying backend system, thereby insulating clients from extended failure of these systems.
- B. They can compose data from various sources and combine them with orchestration logic to create higher level value.
- C. They reduce the dependency on the underlying backend systems by helping unlock data from backend systems In a reusable and consumable way.
- D. They allow for innovation at the user Interface level by consuming the underlying assets without being aware of how data Is being extracted from backend systems.
Answer: A
Explanation:
They provide an additional layer of resilience on top of the underlying backend system, thereby insulating clients from extended failure of these systems.
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In API-led connectivity,
>> Experience APIs - allow for innovation at the user interface level by consuming the underlying assets without being aware of how data is being extracted from backend systems.
>> Process APIs - compose data from various sources and combine them with orchestration logic to create higher level value
>> System APIs - reduce the dependency on the underlying backend systems by helping unlock data from backend systems in a reusable and consumable way.
However, they NEVER promise that they provide an additional layer of resilience on top of the underlying backend system, thereby insulating clients from extended failure of these systems.
https://dzone.com/articles/api-led-connectivity-with-mule
NEW QUESTION # 67
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