A Mule 4 API has been deployed to CloudHub and a Basic Authentication - Simple policy has been applied to all API methods and resources. However, the API is still accessible by clients without using authentication. How is this possible?
A. The APE Router component is pointing to the incorrect Exchange version of the APT
B. The Autodiscovery element is not present, in the deployed Mule application
C. No… for client applications have been created of this API
D. One of the application’s CloudHub workers restarted
Explanation:
When a Basic Authentication policy is applied to an API on CloudHub but
clients can still access the API without authentication, the likely cause is a missing
Autodiscovery element. Here’s how this affects API security:
Which of the following best fits the definition of API-led connectivity?
A.
API-led connectivity is not just an architecture or technology but also a way to organize people and processes for efficient IT delivery in the organization
B.
API-led connectivity is a 3-layered architecture covering Experience, Process and System layers
C.
API-led connectivity is a technology which enabled us to implement Experience, Process and System layer based APIs
API-led connectivity is not just an architecture or technology but also a way to organize people and processes for efficient IT delivery in the organization
Explanation: Explanation
Correct Answer: API-led connectivity is not just an architecture or technology but also a
way to organize people and processes for efficient IT delivery in the organization.
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Reference: https://blogs.mulesoft.com/dev/api-dev/what-is-api-led-connectivity/
An organization requires several APIs to be secured with OAuth 2.0, and PingFederate has been identified as the identity provider for API client authorization, The PingFederate Client Provider is configured in access management, and the PingFederate OAuth 2.0 Token Enforcement policy is configured for the API instances required by the organization. The API instances reside in two business groups (Group A and Group B) within the Master Organization (Master Org). What should be done to allow API consumers to access the API instances?
A. The API administrator should configure the correct client discovery URL in both child business groups, and the API consumer should request access to the API in Ping Identity
B. The API administrator should grant access to the API consumers by creating contracts in the relevant API instances in API Manager
C. The APL consumer should create a client application and request access to the APT in Anypoint Exchange, and the API administrator should approve the request
D. The APT consumer should create a client application and request access to the API in Ping Identity, and the organization's Ping Identity workflow will grant access
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%
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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.
Which layer in the API-led connectivity focuses on unlocking key systems, legacy systems, data sources etc and exposes the functionality?
A.
Experience Layer
B.
Process Layer
C.
System Layer
System Layer
Explanation: Explanation
Correct Answer: System Layer
An organization wants MuleSoft-hosted runtime plane features (such as HTTP load balancing, zero downtime, and horizontal and vertical scaling) in its Azure environment. What runtime plane minimizes the organization's effort to achieve these features?
A.
Anypoint Runtime Fabric
B.
Anypoint Platform for Pivotal Cloud Foundry
C.
CloudHub
D.
A hybrid combination of customer-hosted and MuleSoft-hosted Mule runtimes
Anypoint Runtime Fabric
Explanation: Explanation
Correct Answer: Anypoint Runtime Fabric
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>> 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.
Reference: https://docs.mulesoft.com/runtime-fabric/1.7/
A new upstream API Is being designed to offer an SLA of 500 ms median and 800 ms
maximum (99th percentile) response time. The corresponding API implementation needs to
sequentially invoke 3 downstream APIs of very similar complexity.
The first of these downstream APIs offers the following SLA for its response time: median:
100 ms, 80th percentile: 500 ms, 95th percentile: 1000 ms.
If possible, how can a timeout be set in the upstream API for the invocation of the first
downstream API to meet the new upstream API's desired SLA?
A.
Set a timeout of 50 ms; this times out more invocations of that API but gives additional
room for retries
B.
Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to complete
C.
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
D.
Do not set a timeout; the Invocation of this API Is mandatory and so we must wait until it
responds
Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to complete
Explanation:
Explanation
Correct Answer: Set a timeout of 100ms; that leaves 400ms for other two downstream APIs
to complete
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Key details to take from the given scenario:
>> Upstream API's designed SLA is 500ms (median). Lets ignore maximum SLA response
times.
>> This API calls 3 downstream APIs sequentially and all these are of similar complexity.
>> The first downstream API is offering median SLA of 100ms, 80th percentile: 500ms;
95th percentile: 1000ms.
Based on the above details:
>> We can rule out the option which is suggesting to set 50ms timeout. Because, if the
median SLA itself being offered is 100ms then most of the calls are going to timeout and
time gets wasted in retried them and eventually gets exhausted with all retries. Even if
some retries gets successful, the remaining time wont leave enough room for 2nd and 3rd
downstream APIs to respond within time.
>> The option suggesting to NOT set a timeout as the invocation of this API is mandatory
and so we must wait until it responds is silly. As not setting time out would go against the
good implementation pattern and moreover if the first API is not responding within its
offered median SLA 100ms then most probably it would either respond in 500ms (80th
percentile) or 1000ms (95th percentile). In BOTH cases, getting a successful response
from 1st downstream API does NO GOOD because already by this time the Upstream API
SLA of 500 ms is breached. There is no time left to call 2nd and 3rd downstream APIs.
>> It is NOT true that no timeout is possible to meet the upstream APIs desired SLA.
As 1st downstream API is offering its median SLA of 100ms, it means MOST of the time we
would get the responses within that time. So, setting a timeout of 100ms would be ideal for
MOST calls as it leaves enough room of 400ms for remaining 2 downstream API calls.
An eCommerce company is adding a new Product Details feature to their website, A customer will launch the product catalog page, a new Product Details link will appear by product where they can click to retrieve the product detail description. Product detail data is updated with product update releases, once or twice a year, Presently the database response time has been very slow due to high volume. What action retrieves the product details with the lowest response time, fault tolerant, and consistent data?
A. Select the product details from a database in a Cache scope and return them within the API response
B. Select the product details from a database and put them in Anypoint MQ; the Anypoint MO subseriber will receive the product details and return them within the API response
C. Use an object store to store and retrieve the product details originally read from a database and return them within the API response
D. Select the product details from a database and return them within the API response
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