Salesforce Certified MuleSoft Developer I Practice Test - Questions Answers, Page 7

Anypoint Runtime Fabric. >> When a customer is already having an Azure environment, It is not at all an ideal approach to go with hybrid model having some Mule Runtimes hosted on Azure and some on MuleSoft. This is unnecessary and useless.>> CloudHub is a Mulesoft-hosted Runtime plane and is on AWS. We cannot customize to point CloudHub to customer's Azure environment.>> Anypoint Platform for Pivotal Cloud Foundry is specifically for infrastructure provided by Pivotal Cloud Foundry>> Anypoint Runtime Fabric is right answer as it is a container service that automates the deployment and orchestration of Mule applications and API gateways. Runtime Fabric runs within a customer-managed infrastructure on AWS, Azure, virtual machines (VMs), and bare-metal servers.-Some of the capabilities of Anypoint Runtime Fabric include:-Isolation between applications by running a separate Mule runtime per application.-Ability to run multiple versions of Mule runtime on the same set of resources.-Scaling applications across multiple replicas.-Automated application fail-over.-Application management with Anypoint Runtime Manager.

Implement different system APIs named createCustomer, amendCustomer, retrieveCustomer and suspendCustomer as they are modular and has seperation of concerns. >> It is quite normal to have a single API and different Verb + Resource combinations. However, this fits well for an Experience API or a Process API but not a best architecture style for System APIs. So, option with just one customerManagement API is not the best choice here.>> The option with APIs in createCustomerInCRMZ format is next close choice w.r.t modularization and less maintenance but the naming of APIs is directly coupled with the legacy system. A better foreseen approach would be to name your APIs by abstracting the backend system names as it allows seamless replacement/migration of any backend system anytime. So, this is not the correct choice too.>> createCustomer, amendCustomer, retrieveCustomer and suspendCustomer is the right approach and is the best fit compared to other options as they are both modular and same time got the names decoupled from backend system and it has covered all requirements a System API needs.

The credentials provided by the IdP for identity management. >> There is no support for OAuth 2.0 tokens from client/identity providers to authenticate via Anypoint CLI. Only possible tokens are 'bearer tokens' that too only generated using Anypoint Organization/Environment Client Id and Secret from https://anypoint.mulesoft.com/accounts/login. Not the client credentials of client provider. So, OAuth 2.0 is not possible. More over, the token is mainly for API Manager purposes and not associated with a user. You can NOT use it to call most APIs (for example Cloudhub and etc) as per this Mulesoft Knowledge article.>> The other option allowed by Anypoint CLI is to use client credentials. It is possible to use client credentials of a client provider but requires setting up Connected Apps in client management but such details are not given in the scenario explained in the question.>> So only option left is to use user credentials from identify provider

Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hosted environments.. >>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.>>Thebest practice recommendedby 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.Bottom of FormTop of Form

The remaining capacity allowed by the API implementation.. >>

Reference: https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling-sla-based-policies#response-headers

Increase the size of the CloudHub worker(s). The key details that we can take out from the given scenario are:>> API implementation uses a database bulk insert command to submit all the purchase data to a database>> JDBC driver processes the data into a set of several temporary disk files on the CloudHub worker>> Sometimes a request fails and the logs show a message indicating an out-of-file-space messageBased on above details:>> Both auto-scaling options does NOT help because we cannot set auto-scaling rules based on error messages. Auto-scaling rules are kicked-off based on CPU/Memory usages and not due to some given error or disk space issues.>> Increasing the number of CloudHub workers also does NOT help here because the reason for the failure is not due to performance aspects w.r.t CPU or Memory. It is due to disk-space.>> Moreover, the API is doing bulk insert to submit the received batch data. Which means, all data is handled by ONE worker only at a time. So, the disk space issue should be tackled on 'per worker' basis. Having multiple workers does not help as the batch may still fail on any worker when disk is out of space on that particular worker.Therefore, the right way to deal this issue and resolve this is to increase the vCore size of the worker so that a new worker with more disk space will be provisioned.

Spike control. >> First things first, HTTP Caching policy is for purposes different than avoiding the backend system from overloading. So this is OUT.>> Rate Limiting and Throttling/ Spike Control policies are designed to limit API access, but have different intentions.>> Rate limiting protects an API by applying a hard limit on its access.>> Throttling/ Spike Control shapes API access by smoothing spikes in traffic.That is why, Spike Control is the right option.