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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Applying Integration Patterns | 11% | - Common integration patterns and use cases - Scalability and performance patterns - Event-driven and synchronous integration - Error handling and reliability patterns |
| Topic 2: Establishing Organizational and Platform Foundations | 17% | - Anypoint Platform architecture and components - Platform strategy and roadmap definition - Governance and organizational structure - Center for Enablement (C4E) operating model |
| Topic 3: Managing APIs | 12% | - API policies and security enforcement - Versioning and deprecation strategies - Rate limiting and throttling - API lifecycle management |
| Topic 4: Architecting and Deploying API Implementations | 11% | - Networking and security configuration - High availability and fault tolerance - Runtime architecture and deployment options - CI/CD and DevOps integration |
| Topic 5: Deploying API Implementations to CloudHub | 11% | - Deployment optimization and scaling - VPC and private space configuration - CloudHub architecture and capabilities - Worker sizing and resource planning |
| 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: Designing and Sharing APIs | 11% | - API layering: Experience, Process, System APIs - API specification and documentation - API design standards and best practices - Asset sharing and reuse via Anypoint Exchange |
| Topic 9: Meeting API Quality Goals | 8% | - Performance and latency requirements - Security and compliance standards - Reliability and availability targets - Maintainability and testability |
>> Mule-Arch-201 Test Papers <<
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NEW QUESTION # 128
A Mule application exposes an HTTPS endpoint and is deployed to three CloudHub workers that do not use static IP addresses. The Mule application expects a high volume of client requests in short time periods. What is the most cost-effective infrastructure component that should be used to serve the high volume of client requests?
Answer: D
Explanation:
Correct Answe r: The CloudHub shared load balancer
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The scenario in this question can be split as below:
>> There are 3 CloudHub workers (So, there are already good number of workers to handle high volume of requests)
>> The workers are not using static IP addresses (So, one CANNOT use customer load-balancing solutions without static IPs)
>> Looking for most cost-effective component to load balance the client requests among the workers.
Based on the above details given in the scenario:
>> Runtime autoscaling is NOT at all cost-effective as it incurs extra cost. Most over, there are already 3 workers running which is a good number.
>> We cannot go for a customer-hosted load balancer as it is also NOT most cost-effective (needs custom load balancer to maintain and licensing) and same time the Mule App is not having Static IP Addresses which limits from going with custom load balancing.
>> An API Proxy is irrelevant there as it has no role to play w.r.t handling high volumes or load balancing.
So, the only right option to go with and fits the purpose of scenario being most cost-effective is - using a CloudHub Shared Load Balancer.
NEW QUESTION # 129
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 # 130
An Order API triggers a sequence of other API calls to look up details of an order's items in a back-end inventory database. The Order API calls the OrderItems process API, which calls the Inventory system API. The Inventory system API performs database operations in the back-end inventory database.
The network connection between the Inventory system API and the database is known to be unreliable and hang at unpredictable times.
Where should a two-second timeout be configured in the API processing sequence so that the Order API never waits more than two seconds for a response from the Orderltems process API?
Answer: C
Explanation:
Understanding the API Flow and Timeout Requirement:
The Order API initiates a call to the OrderItems process API, which in turn calls the Inventory system API to fetch details from the inventory database.
The requirement specifies that the Order API should not wait more than two seconds for a response from the OrderItems process API, even if there are delays further down the chain (between Inventory system API and the database).
Choosing the Appropriate Timeout Location:
Setting the timeout at the OrderItems process API level ensures that if the Inventory system API takes longer than two seconds to respond, the OrderItems process API will terminate the request and send a timeout response back to the Order API. This prevents the Order API from waiting indefinitely due to the unreliable connection to the database.
If the timeout were set in the Inventory system API or database, it would not help the Order API directly, as the OrderItems process API would still be waiting for a response.
Detailed Analysis of Each Option:
Option A (Correct Answer): Setting the timeout in the OrderItems process API allows it to control how long it waits for a response from the Inventory system API. If the Inventory system API does not respond within two seconds, the OrderItems process API can terminate the call and return a timeout response to the Order API, meeting the requirement.
Option B: Setting the timeout in the Order API would not limit the wait time at the OrderItems process API level, meaning the OrderItems process API could still wait indefinitely for the Inventory system API, leading to a longer delay.
Option C: Setting the timeout in the Inventory system API only affects the connection to the database and does not influence how long the OrderItems process API waits for the Inventory system API's response.
Option D: Setting a timeout in the database is not feasible in this context since database timeouts are typically configured for database operations and would not directly control the API response times in the overall API chain.
Conclusion:
Option A is the best choice, as it ensures that the OrderItems process API does not hold the Order API longer than the required two seconds, even if the downstream connection to the database hangs. This configuration aligns with MuleSoft best practices for setting timeouts in API orchestration to manage dependencies and prevent delays across a chain of API calls.
For additional information on timeout settings, refer to MuleSoft documentation on handling timeouts and API orchestration best practices.
NEW QUESTION # 131
An organization wants to make sure only known partners can invoke the organization's APIs. To achieve this security goal, the organization wants to enforce a Client ID Enforcement policy in API Manager so that only registered partner applications can invoke the organization's APIs. In what type of API implementation does MuleSoft recommend adding an API proxy to enforce the Client ID Enforcement policy, rather than embedding the policy directly in the application's JVM?
Answer: D
Explanation:
Correct Answe r: A Non-Mule application
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>> All type of Mule applications (Mule 3/ Mule 4/ with APIkit/ with Custom Java Code etc) running on Mule Runtimes support the Embedded Policy Enforcement on them.
>> The only option that cannot have or does not support embedded policy enforcement and must have API Proxy is for Non-Mule Applications.
So, Non-Mule application is the right answer.
NEW QUESTION # 132
A system API has a guaranteed SLA of 100 ms per request. The system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. An upstream process API invokes the system API and the main goal of this process API is to respond to client requests in the least possible time. In what order should the system APIs be invoked, and what changes should be made in order to speed up the response time for requests from the process API?
Answer: D
Explanation:
Correct Answe r: In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment, and ONLY use the first response.
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>> The API requirement in the given scenario is to respond in least possible time.
>> The option that is suggesting to first try the API in primary environment and then fallback to API in DR environment would result in successful response but NOT in least possible time. So, this is NOT a right choice of implementation for given requirement.
>> Another option that is suggesting to ONLY invoke API in primary environment and to add timeout and retries may also result in successful response upon retries but NOT in least possible time. So, this is also NOT a right choice of implementation for given requirement.
>> One more option that is suggesting to invoke API in primary environment and API in DR environment in parallel using Scatter-Gather would result in wrong API response as it would return merged results and moreover, Scatter-Gather does things in parallel which is true but still completes its scope only on finishing all routes inside it. So again, NOT a right choice of implementation for given requirement The Correct choice is to invoke the API in primary environment and the API in DR environment parallelly, and using ONLY the first response received from one of them.
NEW QUESTION # 133
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