Question # 1 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. A decrease in the number of connections within the application network supporting the business process
B. A higher number of discoverable API-related assets in the application network
C. A better response time for the end user as a result of the APIs being smaller in scope and complexity
D. An overall tower usage of resources because each fine-grained API consumes less resources
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B. A higher number of discoverable API-related assets in the application network
Answer Description Explanation: Explanation Correct Answer: A higher number of discoverable API-related assets in the application network. ***************************************** >> 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 finegrained 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.
Question # 2 What is most likely NOT a characteristic of an integration test for a REST API implementation?
A. The test needs all source and/or target systems configured and accessible
B. The test runs immediately after the Mule application has been compiled and packaged
C. The test is triggered by an external HTTP request
D. The test prepares a known request payload and validates the response payload
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B. The test runs immediately after the Mule application has been compiled and packaged
Answer Description Explanation: Explanation Correct Answer: The test runs immediately after the Mule application has been compiled and packaged ***************************************** >> Integration tests are the last layer of tests we need to add to be fully covered. >> These tests actually run against Mule running with your full configuration in place and are tested from external source as they work in PROD. >> These tests exercise the application as a whole with actual transports enabled. So, external systems are affected when these tests run. So, these tests do NOT run immediately after the Mule application has been compiled and packaged. FYI... Unit Tests are the one that run immediately after the Mule application has been compiled and packaged. Reference: https://docs.mulesoft.com/mule-runtime/3.9/testing-strategies#integrationtesting
Question # 3 Which of the below, when used together, makes the IT Operational Model effective?
A. Create reusable assets, Do marketing on the created assets across organization, Arrange time to time LOB reviews to ensure assets are being consumed or not
B. Create reusable assets, Make them discoverable so that LOB teams can self-serve and browse the APIs, Get active feedback and usage metrics
C. Create resuable assets, make them discoverable so that LOB teams can self-serve and browse the APIs
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C. Create resuable assets, make them discoverable so that LOB teams can self-serve and browse the APIs
Answer Description Explanation: Explanation Correct Answer: Create reusable assets, Make them discoverable so that LOB teams can self-serve and browse the APIs, Get active feedback and usage metrics. Diagram, arrow Description automatically generated
Question # 4 Which layer in the API-led connectivity focuses on unlocking key systems, legacy systems, data sources etc and exposes the functionality?
A. Experience Layer
B. Process Layer
C. System Layer
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Answer Description Explanation: Explanation Correct Answer: System Layer
Question # 5 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. Modify the Mule API implementation's properties in the API Manager Properties tab, then promote the Mule API implementation to the Production environment using API Manager
C. Modify the Mule API implementation's properties in Anypoint Exchange, then promote the Mule API implementation to the Production environment using Runtime Manager
D. 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
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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.
Answer Description Explanation: Explanation Correct Answer: Bundle properties files for each environment into the Mule API implementation's deployable archive, then promote the Mule API implementation to the Production environment using Anypoint CLI or the Anypoint Platform REST APIs ***************************************** >> 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.
Question # 6 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 50 ms; this times out more invocations of that API but gives additional room for retries
B. Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to complete
C. 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
D. Do not set a timeout; the Invocation of this API Is mandatory and so we must wait until it responds
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B. Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to complete
Answer Description Explanation: Explanation Correct Answer: Set a timeout of 100ms; that leaves 400ms for other two downstream APIs to complete ***************************************** 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.
Question # 7 Which of the following best fits the definition of API-led connectivity?
A. 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
B. API-led connectivity is a 3-layered architecture covering Experience, Process and System layers
C. API-led connectivity is a technology which enabled us to implement Experience, Process and System layer based APIs
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A. 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 Description Explanation: Explanation Correct Answer: API-led connectivity is not just an architecture or technology but also a way to organize people and processes for efficient IT delivery in the organization. ***************************************** Reference: https://blogs.mulesoft.com/dev/api-dev/what-is-api-led-connectivity/
Question # 8 In an organization, the InfoSec team is investigating Anypoint Platform related data traffic. From where does most of the data available to Anypoint Platform for monitoring and alerting originate?
A. From the Mule runtime or the API implementation, depending on the deployment model
B. From various components of Anypoint Platform, such as the Shared Load Balancer, VPC, and Mule runtimes
C. From the Mule runtime or the API Manager, depending on the type of data
D. From the Mule runtime irrespective of the deployment model
Click for Answer
D. From the Mule runtime irrespective of the deployment model
Answer Description Explanation: Explanation Correct Answer: From the Mule runtime irrespective of the deployment model ***************************************** >> Monitoring and Alerting metrics are always originated from Mule Runtimes irrespective of the deployment model. >> It may seems that some metrics (Runtime Manager) are originated from Mule Runtime and some are (API Invocations/ API Analytics) from API Manager. However, this is realistically NOT TRUE. The reason is, API manager is just a management tool for API instances but all policies upon applying on APIs eventually gets executed on Mule Runtimes only (Either Embedded or API Proxy). >> Similarly all API Implementations also run on Mule Runtimes. So, most of the day required for monitoring and alerts are originated fron Mule Runtimes only irrespective of whether the deployment model is MuleSoft-hosted or Customer-hosted or Hybrid.
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