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| Section | Weight | Objectives |
|---|---|---|
| Monitoring and Analyzing Application Networks | 8% | - Operational visibility and optimization - Analytics and insight generation - Logging and alerting configuration - Monitoring strategies and tools |
| Explaining Application Network Basics | 11% | - Benefits of modern API design - Core concepts of application networks - API-led connectivity principles |
| Architecting and Deploying API Implementations | 11% | - High availability and fault tolerance - CI/CD and DevOps integration - Runtime architecture and deployment options - Networking and security configuration |
| Meeting API Quality Goals | 8% | - Performance and latency requirements - Maintainability and testability - Reliability and availability targets - Security and compliance standards |
| Establishing Organizational and Platform Foundations | 17% | - Platform strategy and roadmap definition - Governance and organizational structure - Anypoint Platform architecture and components - Center for Enablement (C4E) operating model |
| Applying Integration Patterns | 11% | - Error handling and reliability patterns - Scalability and performance patterns - Event-driven and synchronous integration - Common integration patterns and use cases |
| Managing APIs | 12% | - Rate limiting and throttling - API lifecycle management - API policies and security enforcement - Versioning and deprecation strategies |
| Deploying API Implementations to CloudHub | 11% | - Worker sizing and resource planning - VPC and private space configuration - Deployment optimization and scaling - CloudHub architecture and capabilities |
| Designing and Sharing APIs | 11% | - Asset sharing and reuse via Anypoint Exchange - API design standards and best practices - API specification and documentation - API layering: Experience, Process, System APIs |
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NEW QUESTION # 103
A large lending company has developed an API to unlock data from a database server and web server. The API has been deployed to Anypoint Virtual Private Cloud (VPC) on CloudHub 1.0.
The database server and web server are in the customer's secure network and are not accessible through the public internet. The database server is in the customer's AWS VPC, whereas the web server is in the customer's on-premises corporate data center.
How can access be enabled for the API to connect with the database server and the web server?
Answer: B
Explanation:
Scenario Overview:
The API resides in Anypoint Virtual Private Cloud (VPC) on CloudHub 1.0, where it requires connectivity to both an AWS-hosted database server and an on-premises web server.
Both servers are isolated from the public internet: the database server is within the customer's AWS VPC, and the web server is within the customer's on-premises corporate data center.
Connectivity Requirements:
To connect to the AWS database server from the API in Anypoint VPC, VPC peering is ideal. This would allow a private network connection between the MuleSoft Anypoint VPC and the customer's AWS VPC, enabling secure, direct access to the database.
To connect to the on-premises web server, a VPN tunnel is suitable. This would establish a secure, encrypted connection from the Anypoint VPC to the customer's corporate data center, allowing secure data flow between the API and the on-premises web server.
Analysis of Options:
Option A (Correct Answer): Setting up VPC peering with AWS VPC enables private network connectivity with the database server, while a VPN tunnel to the on-premises data center allows secure access to the web server. This combination meets the requirements for secure, controlled access to both resources.
Option B: VPC peering alone would not suffice because it does not support a connection from the Anypoint VPC directly to an on-premises network. A VPN is necessary for on-premises access.
Option C: Setting up a transit gateway would provide connectivity within AWS but would not enable direct connectivity from CloudHub to the on-premises network.
Option D: VPC peering with the on-premises network is not possible because VPC peering is typically used to connect two VPCs, not a VPC with an on-premises network.
Conclusion:
Option A is the correct choice, as it provides a complete solution by using VPC peering for AWS VPC connectivity and a VPN tunnel for secure on-premises connectivity. This setup aligns with Anypoint Platform best practices for connecting Anypoint VPCs to both AWS-hosted and on-premises systems, ensuring secure, controlled access to both the database and web server.
For more detailed reference, MuleSoft documentation on Anypoint VPC peering and VPN connectivity provides additional context on best practices for setting up these connections within a hybrid network infrastructure.
NEW QUESTION # 104
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?
Answer: D
Explanation:
Correct Answe r: Spike control
*****************************************
>> 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.
NEW QUESTION # 105
An organization has built an application network following the API-led connectivity approach recommended by MuleSoft. To protect the application network against attacks from malicious external API clients, the organization plans to apply JSON Threat Protection policies.
To which API-led connectivity layer should the JSON Threat Protection policies most commonly be applied?
Answer: A
Explanation:
Understanding JSON Threat Protection Policies:
JSON Threat Protection policies are used to protect APIs from attacks that exploit JSON payloads, such as oversized payloads, deeply nested objects, and excessive array elements. This helps prevent Denial of Service (DoS) attacks and other malicious payload-related threats.
These policies are typically applied to safeguard APIs that are directly exposed to external clients, where the risk of receiving malicious payloads is highest.
API-led Connectivity Layers:
Experience Layer: This layer is designed to expose APIs to end-users or external API clients, often acting as the interface that interacts with users or applications.
Process Layer: This layer is used for orchestration and aggregation of data from various System APIs, typically operating within a trusted environment and not directly exposed to external clients.
System Layer: This layer provides access to backend systems and databases, often within the organization's secure environment and not directly accessible to external clients.
Evaluating the Options:
Option A (All layers): While JSON Threat Protection can technically be applied to all layers, it is most commonly applied at the Experience layer, where APIs are exposed to external traffic and are more vulnerable to attacks.
Option B (System layer): The System layer is generally not exposed to external clients directly, so JSON Threat Protection is less critical here.
Option C (Process layer): Similar to the System layer, the Process layer is typically internal and not exposed directly to external clients, so JSON Threat Protection is less commonly applied.
Option D (Correct Answer): The Experience layer is the correct answer because it is the layer that directly interacts with external clients, making it the primary target for malicious payloads. Applying JSON Threat Protection here effectively protects the application network from external threats.
Conclusion:
Option D is the correct answer, as the Experience layer is the most common layer for applying JSON Threat Protection policies to protect against external attacks.
For further reference, consult MuleSoft's documentation on API security policies and best practices for securing APIs at the Experience layer.
NEW QUESTION # 106
An operations team is analyzing the effort needed to set up monitoring of their application network. They are looking at which API invocation metrics can be used to identify and predict trouble without having to write custom scripts or install additional analytics software or tools.
Which type of metrics can satisfy this goal of directly identifying and predicting failures?
Answer: A
Explanation:
To monitor an application network and predict issues without custom scripts, policy violation metrics are critical. They provide insights into potential problems by tracking instances where API usage does not conform to defined policies. Here's why this approach is suitable:
Predictive Monitoring:
Tracking API policy violations (such as rate limits or spike controls being hit) can indicate surges in traffic or misuse, which may lead to throttling or service degradation if not addressed.
By monitoring these violations, teams can proactively adjust limits or optimize API handling to prevent actual failures.
No Custom Scripting Needed:
Policy violation metrics are available within MuleSoft's Anypoint Monitoring, meaning there's no need to implement custom solutions or external tools to gather and interpret this data.
of Incorrect Options:
Option B (effectiveness based on reuse) does not directly predict failures.
Option C (past invocation counts) offers historical usage data but does not inherently identify issues.
Option D (ROI from API invocation) is a business metric and does not provide technical insights for failure prediction.
Reference
For more details on leveraging policy violation metrics for proactive monitoring, refer to MuleSoft documentation on Anypoint Monitoring.
NEW QUESTION # 107
A customer wants to monitor and gain insights about the number of requests coming in a given time period as well as to measure key performance indicators (response times, CPU utilization, number of active APIs).
Which tool provides these data insights?
Answer: D
Explanation:
Understanding Anypoint Monitoring and Its Capabilities:
Anypoint Monitoring provides comprehensive visibility into Mule applications, offering metrics and analytics such as request counts, response times, CPU utilization, memory usage, and other key performance indicators (KPIs). This tool is designed to help teams monitor API usage, troubleshoot issues, and optimize application performance.
Evaluating the Options:
Option A (Correct Answer): Anypoint Monitoring is the ideal tool for this requirement. It provides real-time insights into metrics such as the number of requests, response times, CPU utilization, and active API usage.
Option B (API Manager): API Manager focuses on API lifecycle management, including applying policies, managing contracts, and setting access controls. It does not provide performance monitoring or KPI tracking.
Option C (Runtime Alerts): Runtime Alerts can notify users of specific conditions, like high CPU usage, but they do not provide a full suite of metrics or insights over a given time period.
Option D (Functional Monitoring): Functional Monitoring focuses on functional testing of APIs rather than performance and usage metrics. It does not provide continuous KPI tracking.
Conclusion:
Option A is the correct answer. Anypoint Monitoring is the most suitable tool to track the specified metrics, providing detailed insights into API requests, response times, CPU usage, and active API counts.
For further details, refer to MuleSoft's Anypoint Monitoring documentation on configuring dashboards and tracking performance metrics.
NEW QUESTION # 108
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