A client has several applications running on the Salesforce service cloud. The business requirement for integration is to get daily data changes from Account and Case Objects. Data needs to be moved to the client's private cloud AWS DynamoDB instance as a single JSON and the business foresees only wanting five attributes from the Account object, which has 219 attributes (some custom) and eight attributes from the Case Object. What design should be used to support the API/ Application data model?
A. Create separate entities for Account and Case Objects by mimicking all the attributes in SAPI, which are combined by the PAPI and filtered to provide JSON output containing 13 attributes.
B. Request client’s AWS project team to replicate all the attributes and create Account and Case JSON table in DynamoDB. Then create separate entities for Account and Case Objects by mimicking all the attributes in SAPI to transfer ISON data to DynamoD for respective Objects
C. Start implementing an Enterprise Data Model by defining enterprise Account and Case Objects and implement SAPI and DynamoDB tables based on the Enterprise Data Model,
D. Create separate entities for Account with five attributes and Case with eight attributes in SAPI, which are combined by the PAPI to provide JSON output containing 13 attributes.
A customer wants to monitor and gain insights about the number of requests coming in a
given time period as well as to measure key performance indicators
(response times, CPU utilization, number of active APIs).
Which tool provides these data insights?
A. Anypoint Monitoring
B. APT Manager
C. Runtime Alerts
D. Functional Monitoring
When designing an upstream API and its implementation, the development team has been
advised to NOT set timeouts when invoking a downstream API, because that downstream
API has no SLA that can be relied upon. This is the only downstream API dependency of
that upstream API.
Assume the downstream API runs uninterrupted without crashing. What is the impact of
this advice?
A.
An SLA for the upstream API CANNOT be provided
B.
The invocation of the downstream API will run to completion without timing out
C.
A default timeout of 500 ms will automatically be applied by the Mule runtime in which the upstream API implementation executes
D.
A toad-dependent timeout of less than 1000 ms will be applied by the Mule runtime in
which the downstream API implementation executes
An SLA for the upstream API CANNOT be provided
Explanation: Explanation
Correct Answer: An SLA for the upstream API CANNOT be provided.
*****************************************
>> First thing first, the default HTTP response timeout for HTTP connector is 10000 ms (10
seconds). NOT 500 ms.
>> Mule runtime does NOT apply any such "load-dependent" timeouts. There is no such
behavior currently in Mule.
>> As there is default 10000 ms time out for HTTP connector, we CANNOT always
guarantee that the invocation of the downstream API will run to completion without timing
out due to its unreliable SLA times. If the response time crosses 10 seconds then the
request may time out.
The main impact due to this is that a proper SLA for the upstream API CANNOT be
provided.
Reference: https://docs.mulesoft.com/http-connector/1.5/http-documentation#parameters-3
The Line of Business (LoB) of an eCommerce company is requesting a process that sends automated notifications via email every time a new order is processed through the customer's mobile application or through the internal company's web application. In the future, multiple notification channels may be added: for example, text messages and push notifications. What is the most effective API-led connectivity approach for the scenario described above?
A. Create one Experience API for the web application and one for the mobile application.
Create a Process API to orchestrate and retrieve the email template from = database.
Create a System API that sends the email using the Anypoint Connector for Email.
Create one Experience API for the web application and one for the mobile application.
Create a Process API to orchestrate and retrieve the email template from = database.
Create a System API that sends the email using the Anypoint Connector for Email.
B. Create one Experience API for the web application and one for the mobile application
Create a Process API to orchestrate, retrieve the email template from a database, and
send the email using the Anypoint Connector for Email.
C. Create Experience APIs for both the web application and mobile application.
Create a Process API ta orchestrate, retrieve the email template from e database, and
send the email using the Anypoint Connector for Email.
D. Create Experience APIs for both the web application and mobile application.
(Create 3 Process API to orchestrate and retrieve the email template from 2 database.
Create a System API that sends the email using the Anypoint Connector for Email.
Explanation:
In this scenario, the best approach to satisfy the API-led connectivity
principles and support future scalability is:
A company requires Mule applications deployed to CloudHub to be isolated between nonproduction
and production environments. This is so Mule applications deployed to nonproduction
environments can only access backend systems running in their customerhosted
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 perenvironment
isolation between Mule applications and backend systems?
A.
Modify properties of Mule applications deployed to the production Anypoint Platform
environments to prevent access from non-production Mule applications
B.
Configure firewall rules in the infrastructure inside each customer-hosted environment so
that only IP addresses from the corresponding Anypoint Platform environments are allowed
to communicate with corresponding backend systems
C.
Create non-production and production environments in different Anypoint Platform
business groups
D.
Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hosted
environments
Create separate Anypoint VPCs for non-production and production environments, then configure connections to the backend systems in the corresponding customer-hosted
environments
Explanation: Explanation
Correct Answer: 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.
>> 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.
: https://docs.mulesoft.com/runtime-manager/virtual-private-cloud
Bottom of Form
Top of Form
A REST API is being designed to implement a Mule application.
What standard interface definition language can be used to define REST APIs?
A.
Web Service Definition Language(WSDL)
B.
OpenAPI Specification (OAS)
C.
YAML
D.
AsyncAPI Specification
OpenAPI Specification (OAS)
What is true about automating interactions with Anypoint Platform using tools such as Anypoint Platform REST APIs, Anypoint CU, or the Mule Maven plugin?
A.
Access to Anypoint Platform APIs and Anypoint CU can be controlled separately through the roles and permissions in Anypoint Platform, so that specific users can get access to Anypoint CLI white others get access to the platform APIs
B.
Anypoint Platform APIs can ONLY automate interactions with CloudHub, while the Mule Maven plugin is required for deployment to customer-hosted Mule runtimes
C.
By default, the Anypoint CLI and Mule Maven plugin are NOT included in the Mule runtime, so are NOT available to be used by deployed Mule applications
D.
API policies can be applied to the Anypoint Platform APIs so that ONLY certain LOBs have access to specific functions
By default, the Anypoint CLI and Mule Maven plugin are NOT included in the Mule runtime, so are NOT available to be used by deployed Mule applications
Explanation: Explanation
Correct Answer: By default, the Anypoint CLI and Mule Maven plugin are NOT included in
the Mule runtime, so are NOT available to be used by deployed Mule applications
*****************************************
>> We CANNOT apply API policies to the Anypoint Platform APIs like we can do on our
custom written API instances. So, option suggesting this is FALSE.
>> Anypoint Platform APIs can be used for automating interactions with both CloudHub
and customer-hosted Mule runtimes. Not JUST the CloudHub. So, option opposing this is
FALSE.
>> Mule Maven plugin is NOT mandatory for deployment to customer-hosted Mule
runtimes. It just helps your CI/CD to have smoother automation. But not a compulsory
requirement to deploy. So, option opposing this is FALSE.
>> We DO NOT have any such special roles and permissions on the platform to separately
control access for some users to have Anypoint CLI and others to have Anypoint Platform
APIs. With proper general roles/permissions (API Owner, Cloudhub Admin etc..), one can
use any of the options (Anypoint CLI or Platform APIs). So, option suggesting this is
FALSE.
Only TRUE statement given in the choices is that - Anypoint CLI and Mule Maven plugin
are NOT included in the Mule runtime, so are NOT available to be used by deployed Mule
applications.
Maven is part of Studio or you can use other Maven installation for development.
CLI is convenience only. It is one of many ways how to install app to the runtime.
These are definitely NOT part of anything except your process of deployment or
automation.
A retail company with thousands of stores has an API to receive data about purchases and
insert it into a single database. Each individual store sends a batch of purchase data to the
API about every 30 minutes. The API implementation uses a database bulk insert
command to submit all the purchase data to a database using a custom JDBC driver
provided by a data analytics solution provider. The API implementation is deployed to a
single CloudHub worker. The JDBC driver processes the data into a set of several
temporary disk files on the CloudHub worker, and then the data is sent to an analytics
engine using a proprietary protocol. This process usually takes less than a few minutes.
Sometimes a request fails. In this case, the logs show a message from the JDBC driver
indicating an out-of-file-space message. When the request is resubmitted, it is successful.
What is the best way to try to resolve this throughput issue?
A.
se a CloudHub autoscaling policy to add CloudHub workers
B.
Use a CloudHub autoscaling policy to increase the size of the CloudHub worker
C.
Increase the size of the CloudHub worker(s)
D.
Increase the number of CloudHub workers
Increase the number of CloudHub workers
Explanation: Explanation
Correct Answer: 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
message
Based 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.
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