Question 46
An organization currently uses a multi-node Mule runtime deployment model within their datacenter, so each Mule runtime hosts several Mule applications. The organization is planning to transition to a deployment model based on Docker containers in a Kubernetes cluster. The organization has already created a standard Docker image containing a Mule runtime and all required dependencies (including a JVM), but excluding the Mule application itself.
What is an expected outcome of this transition to container-based Mule application deployments?
What is an expected outcome of this transition to container-based Mule application deployments?
Question 47
Refer to the exhibit.
A Mule application is being designed to be deployed to several CIoudHub workers. The Mule application's integration logic is to replicate changed Accounts from Satesforce to a backend system every 5 minutes.
A watermark will be used to only retrieve those Satesforce Accounts that have been modified since the last time the integration logic ran.
What is the most appropriate way to implement persistence for the watermark in order to support the required data replication integration logic?
A Mule application is being designed to be deployed to several CIoudHub workers. The Mule application's integration logic is to replicate changed Accounts from Satesforce to a backend system every 5 minutes.
A watermark will be used to only retrieve those Satesforce Accounts that have been modified since the last time the integration logic ran.
What is the most appropriate way to implement persistence for the watermark in order to support the required data replication integration logic?
Question 48
Refer to the exhibit.
One of the backend systems invoked by an API implementation enforces rate limits on the number of requests a particular client can make. Both the backend system and the API implementation are deployed to several non-production environments in addition to production.
Rate limiting of the backend system applies to all non-production environments. The production environment, however, does NOT have any rate limiting.
What is the most effective approach to conduct performance tests of the API implementation in astaging (non-production) environment?
One of the backend systems invoked by an API implementation enforces rate limits on the number of requests a particular client can make. Both the backend system and the API implementation are deployed to several non-production environments in addition to production.
Rate limiting of the backend system applies to all non-production environments. The production environment, however, does NOT have any rate limiting.
What is the most effective approach to conduct performance tests of the API implementation in astaging (non-production) environment?
Question 49
A stock broking company makes use of CloudHub VPC to deploy Mule applications. Mule application needs to connect to a database application in the customers on-premises corporate data center and also to a Kafka cluster running in AWS VPC.
How is access enabled for the API to connect to the database application and Kafka cluster securely?
How is access enabled for the API to connect to the database application and Kafka cluster securely?
Question 50
An automation engineer needs to write scripts to automate the steps of the API lifecycle, including steps to create, publish, deploy and manage APIs and their implementations in Anypoint Platform.
What Anypoint Platform feature can be used to automate the execution of all these actions in scripts in the easiest way without needing to directly invoke the Anypoint Platform REST APIs?
What Anypoint Platform feature can be used to automate the execution of all these actions in scripts in the easiest way without needing to directly invoke the Anypoint Platform REST APIs?