最新MuleSoft-Integration-Architect-I題庫資訊 & MuleSoft-Integration-Architect-I測試

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Salesforce MuleSoft-Integration-Architect-I 考試大綱:
| 主題 | 簡介 |
|---|
| 主題 1 | - Designing Integration Solutions to Meet Security Requirements: This topic emphasizes securing access to the Anypoint Platform and APIs, using Anypoint Security, counteracting security vulnerabilities, and understanding audit logging capabilities.
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| 主題 2 | - Initiating Integration Solutions on Anypoint Platform: Summarizing MuleSoft Catalyst and Catalyst Knowledge Hub, differentiating between functional and non-functional requirements, selecting features for designing and managing APIs, and choosing deployment options are its sub-topics.
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| 主題 3 | - Designing for the Runtime Plane Technology Architecture: It includes analyzing Mule runtime clusters, designing solutions for CloudHub, choosing Mule runtime domains, leveraging Mule 4 class loader isolation, and understanding the reactive event processing model.
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| 主題 4 | - Designing and Developing Mule Applications: It includes selecting application properties, using fundamental features, designing with core routers, understanding the Salesforce Connector, and leveraging core connectors.
|
| 主題 5 | - Applying DevOps Practices and Operating Integration Solutions: Its sub-topics are related to designing CI
- CD pipelines with MuleSoft plugins, automating interactions with Anypoint Platform, designing logging configurations, and identifying Anypoint Monitoring features.
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| 主題 6 | - Designing Integration Solutions to Meet Performance Requirements: This topic covers meeting performance and capacity goals, using streaming features, and processing large message sequences.
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| 主題 7 | - Designing Integration Solutions to Meet Reliability Requirements: It includes selecting alternatives to traditional transactions, recognizing the purpose of various scopes and strategies, differentiating disaster recovery and high availability, and using local and XA transactions.
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| 主題 8 | - Designing Automated Tests for Mule Applications: This topic covers unit test suites, and scenarios for integration and performance testing.
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| 主題 9 | - Designing Integration Solutions to Meet Persistence Requirements: It addresses the usage of VM queues and connectors, object stores and services, and stateful components configured with object stores.
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>> 最新MuleSoft-Integration-Architect-I題庫資訊 <<
MuleSoft-Integration-Architect-I測試 & MuleSoft-Integration-Architect-I考證
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最新的 Salesforce MuleSoft MuleSoft-Integration-Architect-I 免費考試真題 (Q250-Q255):
問題 #250
An organization uses Mule runtimes which are managed by Anypoint Platform - Private Cloud Edition. What MuleSoft component is responsible for feeding analytics data to non-MuleSoft analytics platforms?
- A. Anypoint Runtime Manager
- B. The Mule runtimes
- C. Anypoint API Manager
- D. Anypoint Exchange
答案:A
解題說明:
Correct answer is Anypoint Runtime Manager
MuleSoft Anypoint Runtime Manager (ARM) provides connectivity to Mule Runtime engines deployed across your organization to provide centralized management, monitoring and analytics reporting. However, most enterprise customers find it necessary for these on-premises runtimes to integrate with their existing non MuleSoft analytics / monitoring systems such as Splunk and ELK to support a single pane of glass view across the infrastructure.
* You can configure the Runtime Manager agent to export data to external analytics tools.
Using either the Runtime Manager cloud console or Anypoint Platform Private Cloud Edition, you can:
--> Send Mule event notifications, including flow executions and exceptions, to Splunk or ELK.
--> Send API Analytics to Splunk or ELK. Sending data to third-party tools is not supported for applications deployed on CloudHub.
You can use the CloudHub custom log appender to integrate with your logging system. Reference:
https://docs.mulesoft.com/runtime-manager/ https://docs.mulesoft.com/release-notes/runtime-manager-agent
/runtime-manager-agent-release-notes
Additional Info:
It can be achieved in 3 steps:
1) register an agent to a runtime manager,
2) configure a gateway to enable API analytics to be sent to non MuleSoft analytics platform (Splunk for ex.)
- as highlighted in the following diagram and
3) setup dashboards.
問題 #251
An organization has implemented a continuous integration (CI) lifecycle that promotes Mule applications through code, build, and test stages. To standardize the organization's CI journey, a new dependency control approach is being designed to store artifacts that include information such as dependencies, versioning, and build promotions.
To implement these process improvements, the organization will now require developers to maintain all dependencies related to Mule application code in a shared location.
What is the most idiomatic (used for its intended purpose) type of system the organization should use in a shared location to standardize all dependencies related to Mule application code?
- A. API Community Manager
- B. The Anypoint Object Store service at cloudhub.io
- C. A binary artifact repository
- D. A MuleSoft-managed repository at repository.mulesoft.org
答案:A
問題 #252
Mule applications need to be deployed to CloudHub so they can access on-premises database systems. These systems store sensitive and hence tightly protected data, so are not accessible over the internet.
What network architecture supports this requirement?
- A. Static IP addresses for the Mule applications deployed to the CloudHub Shared Worker Cloud, plus matching firewall rules and IP whitelisting in the on-premises network
- B. Relocation of the database systems to a DMZ in the on-premises network, with Mule applications deployed to the CloudHub Shared Worker Cloud connecting only to the DMZ
- C. An Anypoint VPC with one Dedicated Load Balancer fronting each on-premises database system, plus matching IP whitelisting in the load balancer and firewall rules in the VPC and on-premises network
- D. An Anypoint VPC connected to the on-premises network using an IPsec tunnel or AWS DirectConnect, plus matching firewall rules in the VPC and on-premises network
答案:D
解題說明:
* "Relocation of the database systems to a DMZ in the on-premises network, with Mule applications deployed to the CloudHub Shared Worker Cloud connecting only to the DMZ" is not a feasible option
* "Static IP addresses for the Mule applications deployed to the CloudHub Shared Worker Cloud, plus matching firewall rules and IP whitelisting in the on-premises network" - It is risk for sensitive data. - Even if you whitelist the database IP on your app, your app wont be able to connect to the database so this is also not a feasible option
* "An Anypoint VPC with one Dedicated Load Balancer fronting each on-premises database system, plus matching IP whitelisting in the load balancer and firewall rules in the VPC and on-premises network" Adding one VPC with a DLB for each backend system also makes no sense, is way too much work. Why would you add a LB for one system.
* Correct answer: "An Anypoint VPC connected to the on-premises network using an IPsec tunnel or AWS DirectConnect, plus matching firewall rules in the VPC and on-premises network" IPsec Tunnel You can use an IPsec tunnel with network-to-network configuration to connect your on- premises data centers to your Anypoint VPC. An IPsec VPN tunnel is generally the recommended solution for VPC to on-premises connectivity, as it provides a standardized, secure way to connect. This method also integrates well with existing IT infrastructure such as routers and appliances. Reference: https://docs.mulesoft.
com/runtime-manager/vpc-connectivity-methods-concept
Diagram Description automatically generated

問題 #253
An organization plans to migrate its deployment environment from an onpremises cluster to a Runtime Fabric (RTF) cluster. The on-premises Mule applications are currently configured with persistent object stores.
There is a requirement to enable Mule applications deployed to the RTF cluster to store and share data across application replicas and through restarts of the entire RTF cluster, How can these reliability requirements be met?
- A. Configure the Persistence Gateway in the RTF installation
- B. Replace persistent object stores with persistent VM queues in each Mule application deployment
- C. Configure Anypoint Object Store v2 to share data between replicas in the RTF cluster
- D. Install the Object Store pod on one of the cluster nodes
答案:B
問題 #254
Refer to the exhibit.

One of the backend systems invoked by an API implementation enforces rate limits on the number of requests a particular client can make. Both the backend system and the API implementation are deployed to several non-production environments in addition to production.
Rate limiting of the backend system applies to all non-production environments. The production environment, however, does NOT have any rate limiting.
What is the most effective approach to conduct performance tests of the API implementation in a staging (non- production) environment?
- A. Use MUnit to simulate standard responses from the backend system then conduct performance tests to identify other bottlenecks in the system
- B. Create a mocking service that replicates the backend system's production performance characteristics.
Then configure the API implementation to use the mocking service and conduct the performance tests - C. Include logic within the API implementation that bypasses invocations of the backend system in a performance test situation. Instead invoking local stubs that replicate typical backend system responses then conduct performance tests using this API Implementation
- D. Conduct scaled-down performance tests in the staging environment against the rate limited backend system then upscale performance results to full production scale
答案:B
解題說明:
Correct answer is Create a mocking service that replicates the backend system's production performance characteristics. Then configure the API implementation to use the mocking service and conduct the performance tests
* MUnit is for only Unit and integration testing for APIs and Mule apps. Not for performance Testing, even if it has the ability to Mock the backend.
* Bypassing the backend invocation defeats the whole purpose of performance testing. Hence it is not a valid answer.
* Scaled down performance tests cant be relied upon as performance of API's is not linear against load.
問題 #255
......
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