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>> MuleSoft-Integration-Architect-I PDF VCE <<
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NEW QUESTION # 205
What metrics about API invocations are available for visualization in custom charts using Anypoint Analytics?
Answer: B
Explanation:
Correct answer is Request size, number of requests, response size, response time Analytics API Analytics can provide insight into how your APIs are being used and how they are performing. From API Manager, you can access the Analytics dashboard, create a custom dashboard, create and manage charts, and create reports.
From API Manager, you can get following types of analytics: - API viewing analytics - API events analytics - Charted metrics in API Manager It can be accessed using: http://anypoint.mulesoft.com/analytics API Analytics provides a summary in chart form of requests, top apps, and latency for a particular duration.
The custom dashboard in Anypoint Analytics contains a set of charts for a single API or for all APIs Each chart displays various API characteristics
- Requests size: Line chart representing size of requests in KBs
- Requests : Line chart representing number of requests over a period
- Response size : Line chart representing size of response in KBs
- Response time :Line chart representing response time in ms
* To check this, You can go to API Manager > Analytics > Custom Dashboard > Edit Dashboard > Create Chart > Metric Graphical user interface, chart Description automatically generated
NEW QUESTION # 206
Refer to the exhibit.
A shopping cart checkout process consists of a web store backend sending a sequence of API invocations to an Experience API, which in turn invokes a Process API. All API invocations are over HTTPS POST. The Java web store backend executes in a Java EE application server, while all API implementations are Mule applications executing in a customer -hosted Mule runtime.
End-to-end correlation of all HTTP requests and responses belonging to each individual checkout Instance is required. This is to be done through a common correlation ID, so that all log entries written by the web store backend, Experience API implementation, and Process API implementation include the same correlation ID for all requests and responses belonging to the same checkout instance.
What is the most efficient way (using the least amount of custom coding or configuration) for the web store backend and the implementations of the Experience API and Process API to participate in end-to-end correlation of the API invocations for each checkout instance?
A)
The web store backend, being a Java EE application, automatically makes use of the thread-local correlation ID generated by the Java EE application server and automatically transmits that to the Experience API using HTTP-standard headers No special code or configuration is included in the web store backend, Experience API, and Process API implementations to generate and manage the correlation ID
B)
The web store backend generates a new correlation ID value at the start of checkout and sets it on the X- CORRELATlON-lt HTTP request header In each API invocation belonging to that checkout No special code or configuration is included in the Experience API and Process API implementations to generate and manage the correlation ID
C)
The Experience API implementation generates a correlation ID for each incoming HTTP request and passes it to the web store backend in the HTTP response, which includes it in all subsequent API invocations to the Experience API.
The Experience API implementation must be coded to also propagate the correlation ID to the Process API in a suitable HTTP request header
D)
The web store backend sends a correlation ID value in the HTTP request body In the way required by the Experience API The Experience API and Process API implementations must be coded to receive the custom correlation ID In the HTTP requests and propagate It in suitable HTTP request headers
Answer: D
Explanation:
Correct answer is "The web store backend generates a new correlation ID value at the start of checkout and sets it on the X-CORRELATION-ID HTTP request header in each API invocation belonging to that checkout No special code or configuration is included in the Experience API and Process API implementations to generate and manage the correlation ID" Explanation : By design, Correlation Ids cannot be changed within a flow in Mule 4 applications and can be set only at source. This ID is part of the Event Context and is generated as soon as the message is received by the application. When a HTTP Request is received, the request is inspected for "X-Correlation-Id" header. If "X-Correlation-Id" header is present, HTTP connector uses this as the Correlation Id. If "X-Correlation-Id" header is NOT present, a Correlation Id is randomly generated. For Incoming HTTP Requests: In order to set a custom Correlation Id, the client invoking the HTTP request must set "X-Correlation-Id" header. This will ensure that the Mule Flow uses this Correlation Id. For Outgoing HTTP Requests: You can also propagate the existing Correlation Id to downstream APIs. By default, all outgoing HTTP Requests send "X-Correlation-Id" header. However, you can choose to set a different value to "X-Correlation-Id" header or set "Send Correlation Id" to NEVER.
Mulesoft Reference: https://help.mulesoft.com/s/article/How-to-Set-Custom-Correlation-Id-for-Flows-with- HTTP-Endpoint-in-Mule-4 Graphical user interface, application, Word Description automatically generated
NEW QUESTION # 207
Refer to the exhibit.
An organization is sizing an Anypoint VPC for the non-production deployments of those Mule applications that connect to the organization's on-premises systems. This applies to approx. 60 Mule applications. Each application is deployed to two CloudHub i workers. The organization currently has three non-production environments (DEV, SIT and UAT) that share this VPC. The AWS region of the VPC has two AZs.
The organization has a very mature DevOps approach which automatically progresses each application through all non-production environments before automatically deploying to production. This process results in several Mule application deployments per hour, using CloudHub's normal zero-downtime deployment feature.
What is a CIDR block for this VPC that results in the smallest usable private IP address range?
Answer: D
Explanation:
Mule applications are deployed in CloudHub workers and each worker is assigned with a dedicated IP * For zero downtime deployment, each worker in CloudHub needs additional IP addresses * A few IPs in a VPC are reserved for infrastructure (generally 2 IPs) * The IP addresses are usually in a private range with a subnet block specifier, such as 10.0.0.1/24 * The smallest CIDR network subnet block you can assign for your VPC is /24 (256 IP addresses) (60*3 env * 2 worker per application ) + 50% of (total) for zero downtime = 540 In this case correct answer is 10.0.0.0/22 as this provided 1024 IP's .
Other IP's are insufficient.
NEW QUESTION # 208
An organization has strict unit test requirement that mandate every mule application must have an MUnit test suit with a test case defined for each flow and a minimum test coverage of 80%.
A developer is building Munit test suit for a newly developed mule application that sends API request to an external rest API.
What is the effective approach for successfully executing the Munit tests of this new application while still achieving the required test coverage for the Munit tests?
Answer: B
Explanation:
* Mocking REST API Invocations:
* To ensure the unit tests do not make actual calls to external REST APIs, which can be unreliable and slow, it is best to mock these invocations. Mocking allows you to simulate the behavior of the external API and provide predefined responses.
* Achieving Test Coverage:
* By mocking the REST API invocations in your MUnit tests, you can focus on testing the logic within the Mule application itself. This ensures high test coverage and isolates your tests from external dependencies.
* Execution of MUnit Tests:
* Configure MUnit to return mock responses for the API calls. This enables the MUnit tests to run quickly and consistently, as they are not dependent on the external system's availability or performance.
References:
* MuleSoft Documentation on MUnit Testing
* Best practices for Mocking in MUnit
NEW QUESTION # 209
An organization has various integrations implemented as Mule applications. Some of these Mule applications are deployed to custom hosted Mule runtimes (on-premises) while others execute in the MuleSoft-hosted runtime plane (CloudHub). To perform the Integra functionality, these Mule applications connect to various backend systems, with multiple applications typically needing to access the backend systems.
How can the organization most effectively avoid creating duplicates in each Mule application of the credentials required to access the backend systems?
Answer: B
Explanation:
* "Create a Mule domain project that maintains the credentials as Mule domain-shared resources" is wrong as domain project is not supported in Cloudhub * We should Avoid Creating duplicates in each Mule application but below two options cause duplication of credentials - Store the credentials in properties files in a shared folder within the organization's data center. Have the Mule applications load properties files from this shared location at startup - Segregate the credentials for each backend system into environment-specific properties files. Package these properties files in each Mule application, from where they are loaded at startup So these are also wrong choices * Credentials service is the best approach in this scenario. Mule domain projects are not supported on CloudHub. Also its is not recommended to have multiple copies of configuration values as this makes difficult to maintain Use the Mule Credentials Vault to encrypt data in a .properties file. (In the context of this document, we refer to the .properties file simply as the properties file.) The properties file in Mule stores data as key-value pairs which may contain information such as usernames, first and last names, and credit card numbers. A Mule application may access this data as it processes messages, for example, to acquire login credentials for an external Web service. However, though this sensitive, private data must be stored in a properties file for Mule to access, it must also be protected against unauthorized - and potentially malicious - use by anyone with access to the Mule application
NEW QUESTION # 210
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