What is typically NOT a function of the APIs created within the framework called API-led connectivity?
A.
They provide an additional layer of resilience on top of the underlying backend system,
thereby insulating clients from extended failure of these systems.
B.
They allow for innovation at the user Interface level by consuming the underlying assets
without being aware of how data Is being extracted from backend systems.
C.
They reduce the dependency on the underlying backend systems by helping unlock data
from backend systems In a reusable and consumable way.
D.
They can compose data from various sources and combine them with orchestration logic to create higher level value.
They provide an additional layer of resilience on top of the underlying backend system,
thereby insulating clients from extended failure of these systems.
Explanation: Explanation
Correct Answer: They provide an additional layer of resilience on top of the underlying
backend system, thereby insulating clients from extended failure of these systems.
*****************************************
In API-led connectivity,
>> Experience APIs - allow for innovation at the user interface level by consuming the
underlying assets without being aware of how data is being extracted from backend
systems.
>> Process APIs - compose data from various sources and combine them with
orchestration logic to create higher level value
>> System APIs - reduce the dependency on the underlying backend systems by helping
unlock data from backend systems in a reusable and consumable way.
However, they NEVER promise that they provide an additional layer of resilience on top of
the underlying backend system, thereby insulating clients from extended failure of these
systems.
https://dzone.com/articles/api-led-connectivity-with-mule
Version 3.0.1 of a REST API implementation represents time values in PST time using ISO 8601 hh:mm:ss format. The API implementation needs to be changed to instead represent time values in CEST time using ISO 8601 hh:mm:ss format. When following the semver.org semantic versioning specification, what version should be assigned to the updated API implementation?
A.
3.0.2
B.
4.0.0
C.
3.1.0
D.
3.0.1
4.0.0
Explanation: Explanation
Correct Answer: 4.0.0
*****************************************
As per semver.org semantic versioning specification:
Given a version number MAJOR.MINOR.PATCH, increment the:
- MAJOR version when you make incompatible API changes.
- MINOR version when you add functionality in a backwards compatible manner.
- PATCH version when you make backwards compatible bug fixes.
As per the scenario given in the question, the API implementation is completely changing
its behavior. Although the format of the time is still being maintained as hh:mm:ss and there
is no change in schema w.r.t format, the API will start functioning different after this change
as the times are going to come completely different.
Example: Before the change, say, time is going as 09:00:00 representing the PST. Now on,
after the change, the same time will go as 18:00:00 as Central European Summer Time is
9 hours ahead of Pacific Time.
>> This may lead to some uncertain behavior on API clients depending on how they are
handling the times in the API response. All the API clients need to be informed that the API
functionality is going to change and will return in CEST format. So, this considered as a
MAJOR change and the version of API for this new change would be 4.0.0
A European company has customers all across Europe, and the IT department is migrating from an older platform to MuleSoft. The main requirements are that the new platform should allow redeployments with zero downtime and deployment of applications to multiple runtime versions, provide security and speed, and utilize Anypoint MQ as the message service. Which runtime plane should the company select based on the requirements without additional network configuration?
A. Runtime Fabric on VMs / Bare Metal for the runtime plane
B. Customer-hosted runtime plane
C. MuleSoft-hosted runtime plane (CloudHub)
D. Anypoint Runtime Fabric on Self-Managed Kubernetes for the runtime plane
Explanation:
For a European company with requirements such as zero-downtime
redeployment, deployment to multiple runtime versions, secure and fast
performance, and the use of Anypoint MQ without additional network configuration,
CloudHub is the best choice for the following reasons:
A Mule application exposes an HTTPS endpoint and is deployed to the CloudHub Shared Worker Cloud. All traffic to that Mule application must stay inside the AWS VPC. To what TCP port do API invocations to that Mule application need to be sent?
A.
443
B.
8081
C.
8091
D.
8082
8082
Explanation: Explanation
Correct Answer: 8082
*****************************************
>> 8091 and 8092 ports are to be used when keeping your HTTP and HTTPS app private
to the LOCAL VPC respectively.
>> Above TWO ports are not for Shared AWS VPC/ Shared Worker Cloud.
>> 8081 is to be used when exposing your HTTP endpoint app to the internet through
Shared LB
>> 8082 is to be used when exposing your HTTPS endpoint app to the internet through
Shared LB
So, API invocations should be sent to port 8082 when calling this HTTPS based app.
References:
https://docs.mulesoft.com/runtime-manager/cloudhub-networking-guide
https://help.mulesoft.com/s/article/Configure-Cloudhub-Application-to-Send-a-HTTPSRequest-
Directly-to-Another-Cloudhub-Application
https://help.mulesoft.com/s/question/0D52T00004mXXULSA4/multiple-http-listerners-oncloudhub-
one-with-port-9090
A retail company is using an Order API to accept new orders. The Order API uses a JMS
queue to submit orders to a backend order management service. The normal load for
orders is being handled using two (2) CloudHub workers, each configured with 0.2 vCore.
The CPU load of each CloudHub worker normally runs well below 70%. However, several
times during the year the Order API gets four times (4x) the average number of orders.
This causes the CloudHub worker CPU load to exceed 90% and the order submission time
to exceed 30 seconds. The cause, however, is NOT the backend order management
service, which still responds fast enough to meet the response SLA for the Order API.
What is the MOST resource-efficient way to configure the Mule application's CloudHub
deployment to help the company cope with this performance challenge?
A.
Permanently increase the size of each of the two (2) CloudHub workers by at least four
times (4x) to one (1) vCore
B.
Use a vertical CloudHub autoscaling policy that triggers on CPU utilization greater than
70%
C.
Permanently increase the number of CloudHub workers by four times (4x) to eight (8)
CloudHub workers
D.
Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater
than 70%
Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater
than 70%
Explanation: Explanation
Correct Answer: Use a horizontal CloudHub autoscaling policy that triggers on CPU
utilization greater than 70%
*****************************************
The scenario in the question is very clearly stating that the usual traffic in the year is pretty
well handled by the existing worker configuration with CPU running well below 70%. The
problem occurs only "sometimes" occasionally when there is spike in the number of orders
coming in.
So, based on above, We neither need to permanently increase the size of each worker nor
need to permanently increase the number of workers. This is unnecessary as other than
those "occasional" times the resources are idle and wasted.
We have two options left now. Either to use horizontal Cloudhub autoscaling policy to
automatically increase the number of workers or to use vertical Cloudhub autoscaling
policy to automatically increase the vCore size of each worker.
Here, we need to take two things into consideration:
1. CPU
2. Order Submission Rate to JMS Queue
>> From CPU perspective, both the options (horizontal and vertical scaling) solves the
issue. Both helps to bring down the usage below 90%.
>> However, If we go with Vertical Scaling, then from Order Submission Rate perspective,
as the application is still being load balanced with two workers only, there may not be much
improvement in the incoming request processing rate and order submission rate to JMS
queue. The throughput would be same as before. Only CPU utilization comes down.
>> But, if we go with Horizontal Scaling, it will spawn new workers and adds extra hand to
increase the throughput as more workers are being load balanced now. This way we can
address both CPU and Order Submission rate.
Hence, Horizontal CloudHub Autoscaling policy is the right and best answer.
What are the major benefits of MuleSoft proposed IT Operating Model?
A.
1. Decrease the IT delivery gap
2. Meet various business demands without increasing the IT capacity
3. Focus on creation of reusable assets first. Upon finishing creation of all the possible
assets then inform the LOBs in the organization to start using them
B.
1. Decrease the IT delivery gap
2. Meet various business demands by increasing the IT capacity and forming various IT
departments
3. Make consumption of assets at the rate of production
C.
1. Decrease the IT delivery gap
2. Meet various business demands without increasing the IT capacity
3. Make consumption of assets at the rate of production
1. Decrease the IT delivery gap
2. Meet various business demands without increasing the IT capacity
3. Make consumption of assets at the rate of production
Explanation: Explanation
Correct Answer:
1. Decrease the IT delivery gap
2. Meet various business demands without increasing the IT capacity
3. Make consumption of assets at the rate of production.
*****************************************
Reference: https://www.youtube.com/watch?v=U0FpYMnMjmM
What Mule application deployment scenario requires using Anypoint Platform Private Cloud Edition or Anypoint Platform for Pivotal Cloud Foundry?
A.
When it Is required to make ALL applications highly available across multiple data centers
B.
When it is required that ALL APIs are private and NOT exposed to the public cloud
C.
When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data
D.
When ALL backend systems in the application network are deployed in the
organization's intranet
When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data
Explanation: Explanation
Correct Answer: When regulatory requirements mandate on-premises processing of EVERY data item, including meta-data.
*****************************************
We need NOT require to use Anypoint Platform PCE or PCF for the below. So these
options are OUT.
>> We can make ALL applications highly available across multiple data centers using
CloudHub too.
>> We can use Anypoint VPN and tunneling from CloudHub to connect to ALL backend
systems in the application network that are deployed in the organization's intranet.
>> We can use Anypoint VPC and Firewall Rules to make ALL APIs private and NOT
exposed to the public cloud.
Only valid reason in the given options that requires to use Anypoint Platform PCE/ PCF is -
When regulatory requirements mandate on-premises processing of EVERY data item,
including meta-data
What CANNOT be effectively enforced using an API policy in Anypoint Platform?
A.
Guarding against Denial of Service attacks
B.
Maintaining tamper-proof credentials between APIs
C.
Logging HTTP requests and responses
D.
Backend system overloading
Guarding against Denial of Service attacks
Explanation: Explanation
Correct Answer: Guarding against Denial of Service attacks
*****************************************
>> Backend system overloading can be handled by enforcing "Spike Control Policy"
>> Logging HTTP requests and responses can be done by enforcing "Message Logging
Policy"
>> Credentials can be tamper-proofed using "Security" and "Compliance" Policies
However, unfortunately, there is no proper way currently on Anypoint Platform to guard
against DOS attacks.
Reference: https://help.mulesoft.com/s/article/DDos-Dos-at
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