Salesforce MuleSoft-Integration-Architect-I Exam With Confidence Using Practice Dumps

Requirement Analysis: The Mule application needs secure access to both an on-premises database and a Kafka cluster in AWS VPC.

Solution: Setting up Anypoint VPN for the on-premises corporate data center and VPC peering with AWS VPC ensures secure and seamless connectivity.

Implementation Steps:

Anypoint VPN Setup:

In the Anypoint Platform, navigate to the VPN configuration.

Create a new VPN connection between the CloudHub VPC and the on-premises corporate data center.

Configure the necessary VPN parameters such as IP address, shared secret, and routing information.

Establish the VPN tunnel and verify connectivity.

VPC Peering Setup:

In the AWS Management Console, navigate to the VPC dashboard.

Create a VPC peering connection between the AWS VPC (where Kafka is hosted) and the CloudHub VPC.

Configure the necessary route tables to allow traffic between the peered VPCs.

Verify the peering connection and ensure that the routing is correctly set up to allow communication between the Mule application and the Kafka cluster.

Testing: Conduct thorough testing to ensure the Mule application can securely connect to both the on-premises database and the Kafka cluster in AWS.

Advantages:

Security: Ensures secure communication channels between CloudHub VPC, on-premises data center, and AWS VPC.

Reliability: Provides a robust and reliable network setup for accessing critical infrastructure components.

References

MuleSoft Documentation on Anypoint VPN

AWS Documentation on VPC Peering

Explanation

Before we answer this question , we need to understand what median (50th percentile) and 80th percentile means. If the 50th percentile (median) of a response time is 500ms that means that 50% of my transactions are either as fast or faster than 500ms.

If the 90th percentile of the same transaction is at 1000ms it means that 90% are as fast or faster and only 10% are slower. Now as per upstream SLA , 99th percentile is 800 ms which means 99% of the incoming requests should have response time less than or equal to 800 ms. But as per one of the backend API , their 95th percentile is 1000 ms which means that backend API will take 1000 ms or less than that for 95% of. requests. As there are three API invocation from upstream API , we can not conclude a timeout that can be set to meet the desired SLA as backend SLA's do not support it.

Let see why other answers are not correct.

1) Do not set a timeout --> This can potentially violate SLA's of upstream API

2) Set a timeout of 100 ms; ---> This will not work as backend API has 100 ms as median meaning only 50% requests will be answered in this time and we will get timeout for 50% of the requests. Important thing to note here is, All APIs need to be executed sequentially, so if you get timeout in first API, there is no use of going to second and third API. As a service provider you wouldn't want to keep 50% of your consumers dissatisfied. So not the best option to go with.

*To quote an example: Let's assume you have built an API to update customer contact details.

- First API is fetching customer number based on login credentials

- Second API is fetching Info in 1 table and returning unique key

- Third API, using unique key provided in second API as primary key, updating remaining details

* Now consider, if API times out in first API and can't fetch customer number, in this case, it's useless to call API 2 and 3 and that is why question mentions specifically that all APIs need to be executed sequentially.

3) Set a timeout of 50 ms --> Again not possible due to the same reason as above Hence correct answer is No timeout is possible to meet the upstream API's desired SLA; a different SLA must be negotiated with the first downstream API or invoke an alternative API

Explanation

* To send message or receive JMS (Java Message Service) message no separate network connection need to be established. So option A, C and D are ruled out.

Correct Answer: The JMS connector supports both sending and receiving of JMS messages over the protocol determined by the JMS provider.

* JMS Connector enables sending and receiving messages to queues and topics for any message service that implements the JMS specification.

* JMS is a widely used API for message-oriented middleware.

* It enables the communication between different components of a distributed application to be loosely coupled, reliable, and asynchronous.

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