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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Applying Integration Patterns | 11% | - Event-Driven Architecture (EDA) - Integration Scenarios & Patterns - Batch Processing |
| Topic 2: Architecting and Deploying API Implementations | 11% | - Mule Runtime Architecture - Disaster Recovery (DR) Strategies - High Availability (HA) Design |
| Topic 3: Meeting API Quality Goals | 8% | - API Performance Optimization - Resilience & Reliability Patterns - Unit & Integration Testing |
| Topic 4: Establishing Organizational and Platform Foundations | 17% | - Governance and Compliance Framework - IT Delivery & C4E Operating Model - Platform Foundation Setup |
| Topic 5: Understanding the MuleSoft Platform & Application Networks | 11% | - Application Network Fundamentals - C4E (Center for Enablement) Definition - MuleSoft Anypoint Platform Core Concepts |
| Topic 6: Deploying API Implementations to CloudHub | 11% | - Deployment Strategies - CloudHub Architecture - CloudHub 2.0 & Runtime Fabric |
| Topic 7: Monitoring and Analyzing Application Networks | 8% | - Analytics & Business Insights - Alerting & Auditing - Anypoint Monitoring Tools |
| Topic 8: Managing APIs | 12% | - API Security (Policies, SLAs) - API Versioning - API Lifecycle Management |
| Topic 9: Designing and Sharing APIs | 11% | - Anypoint Exchange for Sharing Assets - API Design Best Practices - API-Led Connectivity Approach |
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NEW QUESTION # 75
A set of tests must be performed prior to deploying API implementations to a staging environment. Due to data security and access restrictions, untested APIs cannot be granted access to the backend systems, so instead mocked data must be used for these tests. The amount of available mocked data and its contents is sufficient to entirely test the API implementations with no active connections to the backend systems. What type of tests should be used to incorporate this mocked data?
Answer: A
Explanation:
Correct Answe r: Unit tests (Whitebox)
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Reference:
As per general IT testing practice and MuleSoft recommended practice, Integration and Performance tests should be done on full end to end setup for right evaluation. Which means all end systems should be connected while doing the tests. So, these options are OUT and we are left with Unit Tests and Functional Tests.
As per attached reference documentation from MuleSoft:
Unit Tests - are limited to the code that can be realistically exercised without the need to run it inside Mule itself. So good candidates are Small pieces of modular code, Sub Flows, Custom transformers, Custom components, Custom expression evaluators etc.
Functional Tests - are those that most extensively exercise your application configuration. In these tests, you have the freedom and tools for simulating happy and unhappy paths. You also have the possibility to create stubs for target services and make them success or fail to easily simulate happy and unhappy paths respectively.
As the scenario in the question demands for API implementation to be tested before deployment to Staging and also clearly indicates that there is enough/ sufficient amount of mock data to test the various components of API implementations with no active connections to the backend systems, Unit Tests are the one to be used to incorporate this mocked data.
NEW QUESTION # 76
What is a best practice when building System APIs?
Answer: B
Explanation:
Correct Answe r: Model all API resources and methods to closely mimic the operations of the backend system.
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>> There are NO fixed and straight best practices while opting data models for APIs. They are completly contextual and depends on number of factors. Based upon those factors, an enterprise can choose if they have to go with Enterprise Canonical Data Model or Bounded Context Model etc.
>> One should NEVER expose the technical details of API implementation to their API clients. Only the API interface/ RAML is exposed to API clients.
>> It is true that the RAML definitions of APIs should be as detailed as possible and should reflect most of the documentation. However, just that is NOT enough to call your API as best documented API. There should be even more documentation on Anypoint Exchange with API Notebooks etc. to make and create a developer friendly API and repository..
>> The best practice always when creating System APIs is to create their API interfaces by modeling their resources and methods to closely reflect the operations and functionalities of that backend system.
NEW QUESTION # 77
A company requires Mule applications deployed to CloudHub to be isolated between non-production and production environments. This is so Mule applications deployed to non-production environments can only access backend systems running in their customer-hosted non-production environment, and so Mule applications deployed to production environments can only access backend systems running in their customer-hosted production environment. How does MuleSoft recommend modifying Mule applications, configuring environments, or changing infrastructure to support this type of per-environment isolation between Mule applications and backend systems?
Answer: D
Explanation:
Correct Answe r: Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hosted environments.
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>> Creating different Business Groups does NOT make any difference w.r.t accessing the non-prod and prod customer-hosted environments. Still they will be accessing from both Business Groups unless process network restrictions are put in place.
>> We need to modify or couple the Mule Application Implementations with the environment. In fact, we should never implements application coupled with environments by binding them in the properties. Only basic things like endpoint URL etc should be bundled in properties but not environment level access restrictions.
>> IP addresses on CloudHub are dynamic until unless a special static addresses are assigned. So it is not possible to setup firewall rules in customer-hosted infrastrcture. More over, even if static IP addresses are assigned, there could be 100s of applications running on cloudhub and setting up rules for all of them would be a hectic task, non-maintainable and definitely got a good practice.
>> The best practice recommended by Mulesoft (In fact any cloud provider), is to have your Anypoint VPCs seperated for Prod and Non-Prod and perform the VPC peering or VPN tunneling for these Anypoint VPCs to respective Prod and Non-Prod customer-hosted environment networks.
Reference:
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NEW QUESTION # 78
Once an API Implementation is ready and the API is registered on API Manager, who should request the access to the API on Anypoint Exchange?
Answer: D
Explanation:
Correct Answe r: API Consumer
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>> API clients are piece of code or programs that use the client credentials of API consumer but does not directly interact with Anypoint Exchange to get the access
>> API consumer is the one who should get registered and request access to API and then API client needs to use those client credentials to hit the APIs So, API consumer is the one who needs to request access on the API from Anypoint Exchange
NEW QUESTION # 79
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: D
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 # 80
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