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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Architecting and Deploying API Implementations | 11% | - CI/CD and DevOps integration - Runtime architecture and deployment options - Networking and security configuration - High availability and fault tolerance |
| Topic 2: Meeting API Quality Goals | 8% | - Reliability and availability targets - Security and compliance standards - Maintainability and testability - Performance and latency requirements |
| Topic 3: Explaining Application Network Basics | 11% | - Benefits of modern API design - API-led connectivity principles - Core concepts of application networks |
| Topic 4: Designing and Sharing APIs | 11% | - API layering: Experience, Process, System APIs - API specification and documentation - Asset sharing and reuse via Anypoint Exchange - API design standards and best practices |
| Topic 5: Managing APIs | 12% | - API policies and security enforcement - Rate limiting and throttling - API lifecycle management - Versioning and deprecation strategies |
| Topic 6: Establishing Organizational and Platform Foundations | 17% | - Center for Enablement (C4E) operating model - Anypoint Platform architecture and components - Governance and organizational structure - Platform strategy and roadmap definition |
| Topic 7: Monitoring and Analyzing Application Networks | 8% | - Logging and alerting configuration - Analytics and insight generation - Monitoring strategies and tools - Operational visibility and optimization |
| Topic 8: Applying Integration Patterns | 11% | - Event-driven and synchronous integration - Common integration patterns and use cases - Scalability and performance patterns - Error handling and reliability patterns |
| Topic 9: Deploying API Implementations to CloudHub | 11% | - VPC and private space configuration - Worker sizing and resource planning - CloudHub architecture and capabilities - Deployment optimization and scaling |
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NEW QUESTION # 38
Say, there is a legacy CRM system called CRM-Z which is offering below functions:
1. Customer creation
2. Amend details of an existing customer
3. Retrieve details of a customer
4. Suspend a customer
Answer: B
Explanation:
Correct Answe r: Implement different system APIs named createCustomer, amendCustomer, retrieveCustomer and suspendCustomer as they are modular and has seperation of concerns
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>> It is quite normal to have a single API and different Verb + Resource combinations. However, this fits well for an Experience API or a Process API but not a best architecture style for System APIs. So, option with just one customerManagement API is not the best choice here.
>> The option with APIs in createCustomerInCRMZ format is next close choice w.r.t modularization and less maintenance but the naming of APIs is directly coupled with the legacy system. A better foreseen approach would be to name your APIs by abstracting the backend system names as it allows seamless replacement/migration of any backend system anytime. So, this is not the correct choice too.
>> createCustomer, amendCustomer, retrieveCustomer and suspendCustomer is the right approach and is the best fit compared to other options as they are both modular and same time got the names decoupled from backend system and it has covered all requirements a System API needs.
NEW QUESTION # 39
A company is using an on-prem cluster in the data center as a runtime plane and MuleSoft-hosted control plane.
How can the company monitor the detailed performance metrics on the Mule applications deployed to the cluster from the control plane?
Answer: D
Explanation:
Monitoring On-Premise Mule Applications:
For Mule applications deployed on an on-premises cluster, monitoring detailed performance metrics requires communication with the MuleSoft-hosted control plane. The control plane, when used with on-premises runtimes, relies on Anypoint Monitoring and requires a Monitoring Agent to gather and send detailed performance metrics.
Setting Up Monitoring:
To enable detailed metrics, the Monitoring Agent must be installed on each node in the cluster where Mule applications are deployed. This agent collects data on memory usage, CPU load, response times, and other metrics, and sends it to the control plane for aggregation and visualization.
Evaluating the Options:
Option A: Updating settings in the control plane alone does not enable detailed monitoring; the agent must be installed on each node to capture detailed metrics.
Option B (Correct Answer): Installing the Monitoring Agent on each node ensures that each runtime node in the cluster can send its metrics to the control plane, enabling detailed monitoring.
Option C: Installing the agent on a separate server would not be effective, as each node in the cluster needs to independently report its metrics to ensure full visibility.
Option D: The on-prem runtime does not automatically send detailed metrics to the control plane without the Monitoring Agent installed.
Conclusion:
Option B is the correct answer, as installing the Monitoring Agent on each node is essential for detailed performance monitoring of on-prem applications in a cluster.
Refer to MuleSoft's documentation on configuring Anypoint Monitoring for on-premises deployments and using the Monitoring Agent.
NEW QUESTION # 40
A System API is designed to retrieve data from a backend system that has scalability challenges. What API policy can best safeguard the backend system?
Answer: D
Explanation:
Correct Answe r: SLA-based rate limiting
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>> Client Id enforement policy is a "Compliance" related NFR and does not help in maintaining the "Quality of Service (QoS)". It CANNOT and NOT meant for protecting the backend systems from scalability challenges.
>> IP Whitelisting and OAuth 2.0 token enforcement are "Security" related NFRs and again does not help in maintaining the "Quality of Service (QoS)". They CANNOT and are NOT meant for protecting the backend systems from scalability challenges.
Rate Limiting, Rate Limiting-SLA, Throttling, Spike Control are the policies that are "Quality of Service (QOS)" related NFRs and are meant to help in protecting the backend systems from getting overloaded.
https://dzone.com/articles/how-to-secure-apis
NEW QUESTION # 41
An organization is deploying their new implementation of the OrderStatus System API to multiple workers in CloudHub. This API fronts the organization's on-premises Order Management System, which is accessed by the API implementation over an IPsec tunnel.
What type of error typically does NOT result in a service outage of the OrderStatus System API?
Answer: C
Explanation:
Correct Answe r: A CloudHub worker fails with an out-of-memory exception.
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>> An AWS Region itself going down will definitely result in an outage as it does not matter how many workers are assigned to the Mule App as all of those in that region will go down. This is a complete downtime and outage.
>> Extended outage of API manager during initial deployment of API implementation will of course cause issues in proper application startup itself as the API Autodiscovery might fail or API policy templates and polices may not be downloaded to embed at the time of applicaiton startup etc... there are many reasons that could cause issues.
>> A network outage onpremises would of course cause the Order Management System not accessible and it does not matter how many workers are assigned to the app they all will fail and cause outage for sure.
The only option that does NOT result in a service outage is if a cloudhub worker fails with an out-of-memory exception. Even if a worker fails and goes down, there are still other workers to handle the requests and keep the API UP and Running. So, this is the right answer.
NEW QUESTION # 42
An organization has created an API-led architecture that uses various API layers to integrate mobile clients with a backend system. The backend system consists of a number of specialized components and can be accessed via a REST API. The process and experience APIs share the same bounded-context model that is different from the backend data model. What additional canonical models, bounded-context models, or anti-corruption layers are best added to this architecture to help process data consumed from the backend system?
Answer: D
Explanation:
Correct Answe r: Create a bounded-context model for the system layer to closely match the backend data model, and add an anti-corruption layer to let the different bounded contexts cooperate across the system and process layers
*****************************************
>> Canonical models are not an option here as the organization has already put in efforts and created bounded-context models for Experience and Process APIs.
>> Anti-corruption layers for ALL APIs is unnecessary and invalid because it is mentioned that experience and process APIs share same bounded-context model. It is just the System layer APIs that need to choose their approach now.
>> So, having an anti-corruption layer just between the process and system layers will work well. Also to speed up the approach, system APIs can mimic the backend system data model.
NEW QUESTION # 43
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