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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Deploying API Implementations to CloudHub | 11% | - CloudHub 2.0 & Runtime Fabric - CloudHub Architecture - Deployment Strategies |
| Topic 2: Understanding the MuleSoft Platform & Application Networks | 11% | - MuleSoft Anypoint Platform Core Concepts - Application Network Fundamentals - C4E (Center for Enablement) Definition |
| Topic 3: Designing and Sharing APIs | 11% | - API Design Best Practices - API-Led Connectivity Approach - Anypoint Exchange for Sharing Assets |
| Topic 4: Monitoring and Analyzing Application Networks | 8% | - Alerting & Auditing - Analytics & Business Insights - Anypoint Monitoring Tools |
| Topic 5: Establishing Organizational and Platform Foundations | 17% | - IT Delivery & C4E Operating Model - Platform Foundation Setup - Governance and Compliance Framework |
| Topic 6: Applying Integration Patterns | 11% | - Batch Processing - Integration Scenarios & Patterns - Event-Driven Architecture (EDA) |
| Topic 7: Managing APIs | 12% | - API Versioning - API Security (Policies, SLAs) - API Lifecycle Management |
| Topic 8: Meeting API Quality Goals | 8% | - Resilience & Reliability Patterns - API Performance Optimization - Unit & Integration Testing |
| Topic 9: Architecting and Deploying API Implementations | 11% | - High Availability (HA) Design - Disaster Recovery (DR) Strategies - Mule Runtime Architecture |
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NEW QUESTION # 139
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?
Answer: D
Explanation:
Correct Answe r: 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 # 140
The application network is recomposable: it is built for change because it "bends but does not break"
Answer: A
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 # 141
What is a typical result of using a fine-grained rather than a coarse-grained API deployment model to implement a given business process?
Answer: C
Explanation:
Correct Answe r: 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.
NEW QUESTION # 142
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?
Answer: D
Explanation:
Correct Answe r: 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 # 143
A manufacturing company has deployed an API implementation to CloudHub and has not configured it to be automatically restarted by CloudHub when the worker is not responding.
Which statement is true when no API Client invokes that API implementation?
Answer: D
Explanation:
When an API implementation is deployed on CloudHub without configuring automatic restarts in case of worker non-responsiveness, MuleSoft's monitoring and alerting behavior is as follows:
API Invocation Alerts:
If no clients are invoking the API, there will be no invocation alerts triggered, as alerts related to invocations depend on actual client requests.
Implementation-Level Alerts:
Even without invocation, CloudHub can still monitor the state of the API implementation. If the worker becomes unresponsive, an alert related to the API implementation's health or availability could still be raised.
Why Option C is Correct:
This option correctly identifies that no invocation-related alerts would be triggered in the absence of client requests, while implementation-level alerts could still be generated based on the worker's state.
Reference
For additional information, check MuleSoft documentation on CloudHub monitoring and alert configurations to understand worker status alerts versus invocation alerts.
NEW QUESTION # 144
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