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質問 # 40
An API implementation is updated. When must the RAML definition of the API also be updated?
- A. When the API implementation changes from interacting with a legacy backend system deployed on-premises to a modern, cloud-based (SaaS) system
- B. When the API implementation is optimized to improve its average response time
- C. When the API implementation is migrated from an older to a newer version of the Mule runtime
- D. When the API implementation changes the structure of the request or response messages
正解：D
解説：
Correct Answer : When the API implementation changes the structure of the request or response messages
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>> RAML definition usually needs to be touched only when there are changes in the request/response schemas or in any traits on API.
>> It need not be modified for any internal changes in API implementation like performance tuning, backend system migrations etc..
質問 # 41
What is true about API implementations when dealing with legal regulations that require all data processing to be performed within a certain jurisdiction (such as in the USA or the EU)?
- A. They must use a Jurisdiction-local external messaging system such as Active MQ rather than Anypoint MQ
- B. They must avoid using the Object Store as it depends on services deployed ONLY to the US East region
- C. They must te deployed to Anypoint Platform runtime planes that are managed by Anypoint Platform control planes, with both planes in the same Jurisdiction
- D. They must ensure ALL data is encrypted both in transit and at rest
正解：C
解説：
Correct Answer : They must be deployed to Anypoint Platform runtime planes that are managed by Anypoint Platform control planes, with both planes in the same Jurisdiction.
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>> As per legal regulations, all data processing to be performed within a certain jurisdiction. Meaning, the data in USA should reside within USA and should not go out. Same way, the data in EU should reside within EU and should not go out.
>> So, just encrypting the data in transit and at rest does not help to be compliant with the rules. We need to make sure that data does not go out too.
>> The data that we are talking here is not just about the messages that are published to Anypoint MQ. It includes the apps running, transaction states, application logs, events, metric info and any other metadata. So, just replacing Anypoint MQ with a locally hosted ActiveMQ does NOT help.
>> The data that we are talking here is not just about the key/value pairs that are stored in Object Store. It includes the messages published, apps running, transaction states, application logs, events, metric info and any other metadata. So, just avoiding using Object Store does NOT help.
>> The only option left and also the right option in the given choices is to deploy application on runtime and control planes that are both within the jurisdiction.
質問 # 42
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. Rate limiting - SLA based
- C. HTTP caching
- D. Rate limiting
正解：A
解説：
Correct Answer : Spike control
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>> First things first, HTTP Caching policy is for purposes different than avoiding the backend system from overloading. So this is OUT.
>> Rate Limiting and Throttling/ Spike Control policies are designed to limit API access, but have different intentions.
>> Rate limiting protects an API by applying a hard limit on its access.
>> Throttling/ Spike Control shapes API access by smoothing spikes in traffic.
That is why, Spike Control is the right option.
質問 # 43
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 retry logic to the process API to handle intermittent failures by invoking the system 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. 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
- D. 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
正解：B
解説：
Correct Answer : 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.
質問 # 44
Say, there is a legacy CRM system called CRM-Z which is offering below functions:
1. Customer creation
2. Amend details of an existing customer
3. Retrieve details of a customer
4. Suspend a customer
- A. Implement different system APIs named createCustomer, amendCustomer, retrieveCustomer and suspendCustomer as they are modular and has seperation of concerns
- B. Implement different system APIs named createCustomerInCRMZ, amendCustomerInCRMZ, retrieveCustomerFromCRMZ and suspendCustomerInCRMZ as they are modular and has seperation of concerns
- C. Implement a system API named customerManagement which has all the functionalities wrapped in it as various operations/resources
正解：A
解説：
Correct Answer : Implement different system APIs named createCustomer, amendCustomer, retrieveCustomer and suspendCustomer as they are modular and has seperation of concerns
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>> It is quite normal to have a single API and different Verb + Resource combinations. However, this fits well for an Experience API or a Process API but not a best architecture style for System APIs. So, option with just one customerManagement API is not the best choice here.
>> The option with APIs in createCustomerInCRMZ format is next close choice w.r.t modularization and less maintenance but the naming of APIs is directly coupled with the legacy system. A better foreseen approach would be to name your APIs by abstracting the backend system names as it allows seamless replacement/migration of any backend system anytime. So, this is not the correct choice too.
>> createCustomer, amendCustomer, retrieveCustomer and suspendCustomer is the right approach and is the best fit compared to other options as they are both modular and same time got the names decoupled from backend system and it has covered all requirements a System API needs.
質問 # 45
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. Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to complete
- B. 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
- C. Set a timeout of 50 ms; this times out more invocations of that API but gives additional room for retries
- D. Do not set a timeout; the Invocation of this API Is mandatory and so we must wait until it responds
正解：A
解説：
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.
質問 # 46
What Anypoint Connectors support transactions?
- A. Database, 3MS, HTTP
- B. Database, VM, File
- C. Database, JMS, VM
- D. Database, JMS, VM, SFTP
正解：C
質問 # 47
What Mule application can have API policies applied by
Anypoint Platform to the endpoint exposed by that Mule application?
A) A Mule application that accepts requests over HTTP/1.x
B) A Mule application that accepts JSON requests over TCP but is NOT required to provide a response
C) A Mute application that accepts JSON requests over WebSocket
D) A Mule application that accepts gRPC requests over HTTP/2
- A. Option D
- B. Option B
- C. Option A
- D. Option C
正解：C
解説：
Correct Answer : Option A
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>> Anypoint API Manager and API policies are applicable to all types of HTTP/1.x APIs.
>> They are not applicable to WebSocket APIs, HTTP/2 APIs and gRPC APIs
質問 # 48
What is a typical result of using a fine-grained rather than a coarse-grained API deployment model to implement a given business process?
- A. An overall tower usage of resources because each fine-grained API consumes less resources
- B. A higher number of discoverable API-related assets in the application network
- C. A decrease in the number of connections within the application network supporting the business process
- D. A better response time for the end user as a result of the APIs being smaller in scope and complexity
正解：B
解説：
Correct Answer : A higher number of discoverable API-related assets in the application network.
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>> We do NOT get faster response times in fine-grained approach when compared to coarse-grained approach.
>> In fact, we get faster response times from a network having coarse-grained APIs compared to a network having fine-grained APIs model. The reasons are below.
Fine-grained approach:
1. will have more APIs compared to coarse-grained
2. So, more orchestration needs to be done to achieve a functionality in business process.
3. Which means, lots of API calls to be made. So, more connections will needs to be established. So, obviously more hops, more network i/o, more number of integration points compared to coarse-grained approach where fewer APIs with bulk functionality embedded in them.
4. That is why, because of all these extra hops and added latencies, fine-grained approach will have bit more response times compared to coarse-grained.
5. Not only added latencies and connections, there will be more resources used up in fine-grained approach due to more number of APIs.
That's why, fine-grained APIs are good in a way to expose more number of resuable assets in your network and make them discoverable. However, needs more maintenance, taking care of integration points, connections, resources with a little compromise w.r.t network hops and response times.
質問 # 49
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. Anypoint Platform for Pivotal Cloud Foundry
- B. Anypoint Runtime Fabric
- C. CloudHub
- D. A hybrid combination of customer-hosted and MuleSoft-hosted Mule runtimes
正解：B
解説：
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.
質問 # 50
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 resource definitions by adding a description of the rate limiting policy behavior
- C. By refining the request definitions by adding a remaining Requests query parameter with description, type, and example
- D. By refining the response definitions by adding the out-of-the-box Anypoint Platform rate-limit-enforcement securityScheme with description, type, and example
正解：A
解説：
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
質問 # 51
What should be ensured before sharing an API through a public Anypoint Exchange portal?
- A. The visibility level of the API instances of that API that need to be publicly accessible should be set to public visibility
- B. The API should be functional with at least an initial implementation deployed and accessible for users to interact with
- C. The API should be secured using one of the supported authentication/authorization mechanisms to ensure that data is not compromised
- D. The users needing access to the API should be added to the appropriate role in Anypoint Platform
正解：A
解説：
Correct Answer : The visibility level of the API instances of that API that need to be publicly accessible should be set to public visibility.
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Reference:
https://docs.mulesoft.com/exchange/to-share-api-asset-to-portal
質問 # 52
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 deployment of the API implementation to CloudHub and anottV deployment to a customer-hosted Mule runtime that must share the cache state
- B. 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
- 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 is one CloudHub deployment of the API implementation to three CloudHub workers that must share the cache state
正解：D
解説：
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.
質問 # 53
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. 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.
- 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. Modify the Mule API implementation's properties in Anypoint Exchange, then promote the Mule API implementation to the Production environment using Runtime Manager
- D. 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
正解：A
解説：
Correct Answer : Bundle properties files for each environment into the Mule API implementation's deployable archive, then promote the Mule API implementation to the Production environment using Anypoint CLI or the Anypoint Platform REST APIs
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>> Anypoint Exchange is for asset discovery and documentation. It has got no provision to modify the properties of Mule API implementations at all.
>> API Manager is for managing API instances, their contracts, policies and SLAs. It has also got no provision to modify the properties of API implementations.
>> API policies are to address Non-functional requirements of APIs and has again got no provision to modify the properties of API implementations.
So, the right way and recommended way to do this as part of development practice is to bundle properties files for each environment into the Mule API implementation and just point and refer to respective file per environment.
質問 # 54
What is true about the technology architecture of Anypoint VPCs?
- A. Each CloudHub environment requires a separate Anypoint VPC
- B. The private IP address range of an Anypoint VPC is automatically chosen by CloudHub
- C. VPC peering can be used to link the underlying AWS VPC to an on-premises (non AWS) private network
- D. Traffic between Mule applications deployed to an Anypoint VPC and on-premises systems can stay within a private network
正解：D
解説：
Correct Answer : Traffic between Mule applications deployed to an Anypoint VPC and on-premises systems can stay within a private network
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>> The private IP address range of an Anypoint VPC is NOT automatically chosen by CloudHub. It is chosen by us at the time of creating VPC using thr CIDR blocks.
CIDR Block: The size of the Anypoint VPC in Classless Inter-Domain Routing (CIDR) notation.
For example, if you set it to 10.111.0.0/24, the Anypoint VPC is granted 256 IP addresses from 10.111.0.0 to 10.111.0.255.
Ideally, the CIDR Blocks you choose for the Anypoint VPC come from a private IP space, and should not overlap with any other Anypoint VPC's CIDR Blocks, or any CIDR Blocks in use in your corporate network.
that each CloudHub environment requires a separate Anypoint VPC. Once an Anypoint VPC is created, we can choose a same VPC by multiple environments. However, it is generally a best and recommended practice to always have seperate Anypoint VPCs for Non-Prod and Prod environments.
>> We use Anypoint VPN to link the underlying AWS VPC to an on-premises (non AWS) private network. NOT VPC Peering.
Reference:
Only true statement in the given choices is that the traffic between Mule applications deployed to an Anypoint VPC and on-premises systems can stay within a private network.
https://docs.mulesoft.com/runtime-manager/vpc-connectivity-methods-concept
質問 # 55
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. 3.0.1
- B. 3.0.2
- C. 3.1.0
- D. 4.0.0
正解：D
解説：
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
質問 # 56
What best explains the use of auto-discovery in API implementations?
- A. It enables Anypoint Exchange to discover assets and makes them available for reuse
- B. It enables Anypoint Studio to discover API definitions configured in Anypoint Platform
- C. It makes API Manager aware of API implementations and hence enables it to enforce policies
- D. It enables Anypoint Analytics to gain insight into the usage of APIs
正解：C
解説：
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
質問 # 57
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
正解：C
解説：
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:
質問 # 58
When must an API implementation be deployed to an Anypoint VPC?
- A. When the API Implementation must invoke publicly exposed services that are deployed outside of CloudHub in a customer- managed AWS instance
- B. When the API Implementation must write to a persistent Object Store
- C. When the API implementation must be deployed to a production AWS VPC using the Mule Maven plugin
- D. When the API implementation must be accessible within a subnet of a restricted customer-hosted network that does not allow public access
正解：A
質問 # 59
Which of the following sequence is correct?
- A. API Consumer requests access to API >> API Client implementes logic to call an API >> API routes the request to >> API Implementation
- B. API Client implementes logic to call an API >> API Consumer requests access to API >> API Implementation routes the request to >> API
- C. API Client implementes logic to call an API >> API Consumer requests access to API >> API routes the request to >> API Implementation
- D. API Consumer implementes logic to call an API >> API Client requests access to API >> API Implementation routes the request to >> API
正解：A
解説：
Correct Answer : API Consumer requests access to API >> API Client implementes logic to call an API >> API routes the request to >> API Implementation
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>> API consumer does not implement any logic to invoke APIs. It is just a role. So, the option stating "API Consumer implementes logic to call an API" is INVALID.
>> API Implementation does not route any requests. It is a final piece of logic where functionality of target systems is exposed. So, the requests should be routed to the API implementation by some other entity. So, the options stating "API Implementation routes the request to >> API" is INVALID
>> The statements in one of the options are correct but sequence is wrong. The sequence is given as "API Client implementes logic to call an API >> API Consumer requests access to API >> API routes the request to >> API Implementation". Here, the statements in the options are VALID but sequence is WRONG.
>> Right option and sequence is the one where API consumer first requests access to API on Anypoint Exchange and obtains client credentials. API client then writes logic to call an API by using the access client credentials requested by API consumer and the requests will be routed to API implementation via the API which is managed by API Manager.
質問 # 60
What is a best practice when building System APIs?
- A. Model all API resources and methods to closely mimic the operations of the backend system
- B. Build an Enterprise Data Model (Canonical Data Model) for each backend system and apply it to System APIs
- C. Expose to API clients all technical details of the API implementation's interaction wifch the backend system
- D. Document the API using an easily consumable asset like a RAML definition
正解：A
解説：
Correct Answer : Model all API resources and methods to closely mimic the operations of the backend system.
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>> There are NO fixed and straight best practices while opting data models for APIs. They are completly contextual and depends on number of factors. Based upon those factors, an enterprise can choose if they have to go with Enterprise Canonical Data Model or Bounded Context Model etc.
>> One should NEVER expose the technical details of API implementation to their API clients. Only the API interface/ RAML is exposed to API clients.
>> It is true that the RAML definitions of APIs should be as detailed as possible and should reflect most of the documentation. However, just that is NOT enough to call your API as best documented API. There should be even more documentation on Anypoint Exchange with API Notebooks etc. to make and create a developer friendly API and repository..
>> The best practice always when creating System APIs is to create their API interfaces by modeling their resources and methods to closely reflect the operations and functionalities of that backend system.
質問 # 61
What Anypoint Platform Capabilities listed below fall under APIs and API Invocations/Consumers category? Select TWO.
- A. API Design and Development
- B. API Operations and Management
- C. API Runtime Execution and Hosting
- D. API Consumer Engagement
正解：A
解説：
Correct Answers: API Design and Development and API Runtime Execution and Hosting
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>> API Design and Development - Anypoint Studio, Anypoint Design Center, Anypoint Connectors
>> API Runtime Execution and Hosting - Mule Runtimes, CloudHub, Runtime Services
>> API Operations and Management - Anypoint API Manager, Anypoint Exchange
Correct Answers: API Operations and Management and API Consumer Engagement
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>> API Design and Development - Anypoint Studio, Anypoint Design Center, Anypoint Connectors
>> API Runtime Execution and Hosting - Mule Runtimes, CloudHub, Runtime Services
>> API Operations and Management - Anypoint API Manager, Anypoint Exchange
>> API Consumer Management - API Contracts, Public Portals, Anypoint Exchange, API Notebooks
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Top of Form
質問 # 62
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
正解：A
解説：
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.
質問 # 63
In which layer of API-led connectivity, does the business logic orchestration reside?
- A. Process Layer
- B. Experience Layer
- C. System Layer
正解：A
解説：
Correct Answer : Process Layer
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>> Experience layer is dedicated for enrichment of end user experience. This layer is to meet the needs of different API clients/ consumers.
>> System layer is dedicated to APIs which are modular in nature and implement/ expose various individual functionalities of backend systems
>> Process layer is the place where simple or complex business orchestration logic is written by invoking one or many System layer modular APIs So, Process Layer is the right answer.
質問 # 64
When could the API data model of a System API reasonably mimic the data model exposed by the corresponding backend system, with minimal improvements over the backend system's data model?
- A. When there is an existing Enterprise Data Model widely used across the organization
- B. When a pragmatic approach with only limited isolation from the backend system is deemed appropriate
- C. When the System API can be assigned to a bounded context with a corresponding data model
- D. When the corresponding backend system is expected to be replaced in the near future
正解：B
解説：
Correct Answer : When a pragmatic approach with only limited isolation from the backend system is deemed appropriate.
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General guidance w.r.t choosing Data Models:
>> If an Enterprise Data Model is in use then the API data model of System APIs should make use of data types from that Enterprise Data Model and the corresponding API implementation should translate between these data types from the Enterprise Data Model and the native data model of the backend system.
>> If no Enterprise Data Model is in use then each System API should be assigned to a Bounded Context, the API data model of System APIs should make use of data types from the corresponding Bounded Context Data Model and the corresponding API implementation should translate between these data types from the Bounded Context Data Model and the native data model of the backend system. In this scenario, the data types in the Bounded Context Data Model are defined purely in terms of their business characteristics and are typically not related to the native data model of the backend system. In other words, the translation effort may be significant.
>> If no Enterprise Data Model is in use, and the definition of a clean Bounded Context Data Model is considered too much effort, then the API data model of System APIs should make use of data types that approximately mirror those from the backend system, same semantics and naming as backend system, lightly sanitized, expose all fields needed for the given System API's functionality, but not significantly more and making good use of REST conventions.
The latter approach, i.e., exposing in System APIs an API data model that basically mirrors that of the backend system, does not provide satisfactory isolation from backend systems through the System API tier on its own. In particular, it will typically not be possible to "swap out" a backend system without significantly changing all System APIs in front of that backend system and therefore the API implementations of all Process APIs that depend on those System APIs! This is so because it is not desirable to prolong the life of a previous backend system's data model in the form of the API data model of System APIs that now front a new backend system. The API data models of System APIs following this approach must therefore change when the backend system is replaced.
On the other hand:
>> It is a very pragmatic approach that adds comparatively little overhead over accessing the backend system directly
>> Isolates API clients from intricacies of the backend system outside the data model (protocol, authentication, connection pooling, network address, ...)
>> Allows the usual API policies to be applied to System APIs
>> Makes the API data model for interacting with the backend system explicit and visible, by exposing it in the RAML definitions of the System APIs
>> Further isolation from the backend system data model does occur in the API implementations of the Process API tier
質問 # 65
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