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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Applying Integration Patterns | 11% | - Error handling and reliability patterns - Common integration patterns and use cases - Event-driven and synchronous integration - Scalability and performance patterns |
| Topic 2: Establishing Organizational and Platform Foundations | 17% | - Center for Enablement (C4E) operating model - Governance and organizational structure - Anypoint Platform architecture and components - Platform strategy and roadmap definition |
| Topic 3: Managing APIs | 12% | - Versioning and deprecation strategies - API policies and security enforcement - Rate limiting and throttling - API lifecycle management |
| Topic 4: Architecting and Deploying API Implementations | 11% | - Runtime architecture and deployment options - High availability and fault tolerance - CI/CD and DevOps integration - Networking and security configuration |
| Topic 5: Deploying API Implementations to CloudHub | 11% | - Worker sizing and resource planning - VPC and private space configuration - CloudHub architecture and capabilities - Deployment optimization and scaling |
| Topic 6: Explaining Application Network Basics | 11% | - API-led connectivity principles - Benefits of modern API design - Core concepts of application networks |
| Topic 7: Monitoring and Analyzing Application Networks | 8% | - Logging and alerting configuration - Monitoring strategies and tools - Operational visibility and optimization - Analytics and insight generation |
| Topic 8: Meeting API Quality Goals | 8% | - Maintainability and testability - Reliability and availability targets - Security and compliance standards - Performance and latency requirements |
| Topic 9: 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 # 55
A system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. A process API is a client to the system API and is being rate limited by the system API, with different limits in each of the environments. The system API's DR environment provides only 20% of the rate limiting offered by the primary environment. What is the best API fault-tolerant invocation strategy to reduce overall errors in the process API, given these conditions and constraints?
Answer: B
Explanation:
Correct Answe r: Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the system API deployed to the DR environment
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There is one important consideration to be noted in the question which is - System API in DR environment provides only 20% of the rate limiting offered by the primary environment. So, comparitively, very less calls will be allowed into the DR environment API opposed to its primary environment. With this in mind, lets analyse what is the right and best fault-tolerant invocation strategy.
1. Invoking both the system APIs in parallel is definitely NOT a feasible approach because of the 20% limitation we have on DR environment. Calling in parallel every time would easily and quickly exhaust the rate limits on DR environment and may not give chance to genuine intermittent error scenarios to let in during the time of need.
2. Another option given is suggesting to add timeout and retry logic to process API while invoking primary environment's system API. This is good so far. However, when all retries failed, the option is suggesting to invoke the copy of process API on DR environment which is not right or recommended. Only system API is the one to be considered for fallback and not the whole process API. Process APIs usually have lot of heavy orchestration calling many other APIs which we do not want to repeat again by calling DR's process API. So this option is NOT right.
3. One more option given is suggesting to add the retry (no timeout) logic to process API to directly retry on DR environment's system API instead of retrying the primary environment system API first. This is not at all a proper fallback. A proper fallback should occur only after all retries are performed and exhausted on Primary environment first. But here, the option is suggesting to directly retry fallback API on first failure itself without trying main API. So, this option is NOT right too.
This leaves us one option which is right and best fit.
- Invoke the system API deployed to the primary environment
- Add Timeout and Retry logic on it in process API
- If it fails even after all retries, then invoke the system API deployed to the DR environment.
NEW QUESTION # 56
Which three tools automate the deployment of Mule applications?
Choose 3 answers
Answer: A,B,F
Explanation:
MuleSoft offers various tools to automate the deployment of Mule applications, which can streamline deployment and management processes. Here's how each tool supports automated deployment:
Runtime Manager:
Anypoint Runtime Manager is MuleSoft's web-based interface that allows users to deploy, manage, and monitor applications directly. It provides deployment automation through its user-friendly interface.
Anypoint Platform CLI:
The Anypoint CLI enables scripting of deployment and management tasks, making it possible to automate deployments via command-line scripts. This tool is ideal for CI/CD pipelines as it integrates with automated processes.
Platform APIs:
MuleSoft's Platform APIs allow programmatic access to deployment functions, enabling integration with external automation tools and CI/CD systems. These APIs facilitate deployment through RESTful calls, which can be automated for continuous delivery.
of Incorrect Options:
Option D (Anypoint Studio) is primarily for development and does not support deployment automation.
Option E (Maven Plugin) can be used for building and deploying Mule applications but isn't classified as a platform tool for deployment.
Option F (API Community Manager) is unrelated to deployment and instead focuses on managing API communities.
Reference
For detailed steps on automating deployments with these tools, refer to MuleSoft documentation on Runtime Manager, CLI, and Platform APIs.
NEW QUESTION # 57
An API has been updated in Anypoint Exchange by its API producer from version 3.1.1 to 3.2.0 following accepted semantic versioning practices and the changes have been communicated via the API's public portal.
The API endpoint does NOT change in the new version.
How should the developer of an API client respond to this change?
Answer: B
NEW QUESTION # 58
What condition requires using a CloudHub Dedicated Load Balancer?
Answer: B
Explanation:
Correct Answe r: When server-side load-balanced TLS mutual authentication is required between API implementations and API clients
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Fact/ Memory Tip: Although there are many benefits of CloudHub Dedicated Load balancer, TWO important things that should come to ones mind for considering it are:
>> Having URL endpoints with Custom DNS names on CloudHub deployed apps
>> Configuring custom certificates for both HTTPS and Two-way (Mutual) authentication.
Coming to the options provided for this question:
>> We CANNOT use DLB to perform cross-region load balancing between separate deployments of the same Mule application.
>> We can have mapping rules to have more than one DLB URL pointing to same Mule app. But vicevera (More than one Mule app having same DLB URL) is NOT POSSIBLE
>> It is true that DLB helps to setup custom DNS names for Cloudhub deployed Mule apps but NOT true for apps deployed to Customer-hosted Mule Runtimes.
>> It is true to that we can load balance API invocations across multiple CloudHub workers using DLB but it is NOT A MUST. We can achieve the same (load balancing) using SLB (Shared Load Balancer) too. We DO NOT necessarily require DLB for achieve it.
So the only right option that fits the scenario and requires us to use DLB is when TLS mutual authentication is required between API implementations and API clients.
NEW QUESTION # 59
A company wants to move its Mule API implementations into production as quickly as possible. To protect access to all Mule application data and metadata, the company requires that all Mule applications be deployed to the company's customer-hosted infrastructure within the corporate firewall. What combination of runtime plane and control plane options meets these project lifecycle goals?
Answer: D
Explanation:
Correct Answe r: Manually provisioned customer-hosted runtime plane and customer-hosted control plane
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There are two key factors that are to be taken into consideration from the scenario given in the question.
>> Company requires both data and metadata to be resided within the corporate firewall
>> Company would like to go with customer-hosted infrastructure.
Any deployment model that is to deal with the cloud directly or indirectly (Mulesoft-hosted or Customer's own cloud like Azure, AWS) will have to share atleast the metadata.
Application data can be controlled inside firewall by having Mule Runtimes on customer hosted runtime plane. But if we go with Mulsoft-hosted/ Cloud-based control plane, the control plane required atleast some minimum level of metadata to be sent outside the corporate firewall.
As the customer requirement is pretty clear about the data and metadata both to be within the corporate firewall, even though customer wants to move to production as quickly as possible, unfortunately due to the nature of their security requirements, they have no other option but to go with manually provisioned customer-hosted runtime plane and customer-hosted control plane.
NEW QUESTION # 60
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Before starting the Salesforce Mule-Arch-201 preparation, plan the amount of time you will allot to each topic, determine the topics that demand more effort and prioritize the components that possess more weightage in the Salesforce Mule-Arch-201 Exam. This kind of polished approach is beneficial for a commendable grade in the Salesforce Mule-Arch-201 Exam.
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