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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Monitoring and Analyzing Application Networks | 8% | - Anypoint Monitoring Tools - Analytics & Business Insights - Alerting & Auditing |
| Topic 2: Deploying API Implementations to CloudHub | 11% | - CloudHub 2.0 & Runtime Fabric - Deployment Strategies - CloudHub Architecture |
| Topic 3: Architecting and Deploying API Implementations | 11% | - Mule Runtime Architecture - Disaster Recovery (DR) Strategies - High Availability (HA) Design |
| Topic 4: Understanding the MuleSoft Platform & Application Networks | 11% | - MuleSoft Anypoint Platform Core Concepts - C4E (Center for Enablement) Definition - Application Network Fundamentals |
| Topic 5: Designing and Sharing APIs | 11% | - API Design Best Practices - Anypoint Exchange for Sharing Assets - API-Led Connectivity Approach |
| Topic 6: Managing APIs | 12% | - API Security (Policies, SLAs) - API Versioning - API Lifecycle Management |
| Topic 7: Establishing Organizational and Platform Foundations | 17% | - Platform Foundation Setup - IT Delivery & C4E Operating Model - Governance and Compliance Framework |
| Topic 8: Meeting API Quality Goals | 8% | - Unit & Integration Testing - Resilience & Reliability Patterns - API Performance Optimization |
| Topic 9: Applying Integration Patterns | 11% | - Event-Driven Architecture (EDA) - Integration Scenarios & Patterns - Batch Processing |
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NEW QUESTION # 40
What best explains the use of auto-discovery in API implementations?
Answer: B
Explanation:
Correct Answe r: 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
NEW QUESTION # 41
An online store's marketing team has noticed an increase in customers leaving online baskets without checking out. They suspect a technology issue is at the root cause of the baskets being left behind. They approach the Center for Enablement to ask for help identifying the issue. Multiple APIs from across all the layers of their application network are involved in the shopping application.
Which feature of the Anypoint Platform can be used to view metrics from all involved APIs at the same time?
Answer: D
Explanation:
Understanding the Need for Cross-API Monitoring:
The Center for Enablement (C4E) needs to investigate potential technical issues across multiple APIs in the application network that may be causing customers to abandon their carts.
This requires a solution that allows viewing metrics across several APIs in real-time to identify any performance issues or bottlenecks.
Evaluating Anypoint Platform Features:
Built-in Dashboards: Anypoint Platform provides built-in dashboards in Anypoint Monitoring, allowing teams to view metrics from multiple APIs in a single interface. This feature is designed to monitor API performance, latency, errors, and throughput, and is ideal for tracking performance across all layers of the application network.
Custom Dashboards: While custom dashboards allow for more tailored views, the built-in dashboards already aggregate metrics for multiple APIs, making it unnecessary to build a custom solution for this scenario.
Functional Monitoring: This feature is used to set up tests to monitor specific API functionality and uptime but is not suited for tracking metrics across multiple APIs in real-time.
API Manager: API Manager primarily focuses on managing API policies, contracts, and access control rather than providing detailed, real-time metrics across the entire application network.
Conclusion:
Option B (Built-in dashboards) is the best choice because it provides a comprehensive view of metrics from all APIs involved, enabling the C4E team to quickly identify any issues that may be contributing to abandoned shopping carts.
Refer to MuleSoft's documentation on Anypoint Monitoring and built-in dashboards for more details on configuring and using these dashboards effectively.
NEW QUESTION # 42
To minimize operation costs, a customer wants to use a CloudHub 1.0 solution. The customer's requirements are:
* Separate resources with two Business groups
* High-availability (HA) for all APIs
* Route traffic via Dedicated load balancer (DLBs)
* Separate environments into production and non-production
Which solution meets the customer's needs?
Answer: A
Explanation:
Understanding the Requirements:
Business Groups: The solution must support two business groups, which typically require separate VPCs for logical separation.
High Availability (HA): Requires deploying resources across multiple availability zones.
Dedicated Load Balancer (DLB): Traffic should be routed via DLBs, which operate within VPCs on CloudHub.
Separate Environments: There needs to be separation between production and non-production environments.
Evaluating the Options:
Option A: Using a single production and non-production VPC and differentiating business groups via availability zones is not ideal as it does not provide full separation for each business group, and using maximum CIDR allocation is wasteful.
Option B (Correct Answer): Creating separate production and non-production VPCs per business group with minimized CIDR blocks, multiple availability zones, and multiple workers per application for HA meets all requirements effectively.
Option C: While this option separates VPCs per business group, it does not fully address the requirement for HA across availability zones by specifying multi-zone deployment only during API deployment, which may not guarantee redundancy.
Option D: Configuring subnets to differentiate business groups within a single production and non-production VPC does not fully separate the business groups, which is a requirement.
Conclusion:
Option B is the best choice as it meets the requirements for high availability, business group separation, and cost efficiency by using minimized CIDR allocations and deploying multiple workers across availability zones.
For further reference, refer to MuleSoft's documentation on VPC configuration and high availability deployment strategies.
NEW QUESTION # 43
Which APIs can be used with DataGraph to create a unified schema?
Answer: D
Explanation:
To create a unified schema in MuleSoft's DataGraph, APIs must be exposed in a way that allows DataGraph to pull and consolidate data from these APIs into a single schema accessible to consumers. DataGraph provides a federated approach, combining multiple APIs to form a single, unified API endpoint.
In this setup:
APIs 1, 2, 3, and 4 are suitable candidates for DataGraph because they are hosted within the Customer VPC on CloudHub and are accessible either through a Shared Load Balancer (LB) or a Dedicated Load Balancer (DLB). Both of these load balancers provide public access, which is a necessary condition for DataGraph as it must access the APIs to aggregate data.
APIs 5 and 6 are hosted on Customer Hosted Server 2, which is explicitly marked as "Not public". Since DataGraph requires API access through a publicly reachable endpoint to aggregate them into a unified schema, APIs 5 and 6 cannot be used with DataGraph in this configuration.
APIs 3 and 4 on Customer Hosted Server 1 appear accessible through a Shared LB, implying public accessibility that meets DataGraph's requirements.
By combining APIs 1, 2, 3, and 4 within DataGraph, you can create a unified schema that enables clients to query data seamlessly from all these APIs as if it were from a single source.
This setup allows for efficient data retrieval and can simplify API consumption by reducing the need to call multiple APIs individually, thus optimizing performance and developer experience.
Reference
For more detailed information on setting up and managing unified schemas in DataGraph, refer to the DataWeave documentation and MuleSoft DataGraph resources which provide in-depth guidelines on schema aggregation and API federation.
NEW QUESTION # 44
Refer to the exhibit.
An organization uses one specific CloudHub (AWS) region for all CloudHub deployments.
How are CloudHub workers assigned to availability zones (AZs) when the organization's Mule applications are deployed to CloudHub in that region?
Answer: A
Explanation:
Correct Answe r: Workers are randomly distributed across available AZs within that region.
*****************************************
>> Currently, we only have control to choose which AWS Region to choose but there is no control at all using any configurations or deployment options to decide what Availability Zone (AZ) to assign to what worker.
>> There are NO fixed or implicit rules on platform too w.r.t assignment of AZ to workers based on environment or application.
>> They are completely assigned in random. However, cloudhub definitely ensures that HA is achieved by assigning the workers to more than on AZ so that all workers are not assigned to same AZ for same application.
Reference:
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NEW QUESTION # 45
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