A company has started to create an application network and is now planning to implement a Center for Enablement (C4E) organizational model. What key factor would lead the company to decide upon a federated rather than a centralized C4E?
A.
When there are a large number of existing common assets shared by development teams
B.
When various teams responsible for creating APIs are new to integration and hence need extensive training
C.
When development is already organized into several independent initiatives or groups
D.
When the majority of the applications in the application network are cloud based
When development is already organized into several independent initiatives or groups
Explanation: Explanation
Correct Answer: When development is already organized into several independent
initiatives or groups
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>> It would require lot of process effort in an organization to have a single C4E team
coordinating with multiple already organized development teams which are into several
independent initiatives. A single C4E works well with different teams having at least a
common initiative. So, in this scenario, federated C4E works well instead of centralized
C4E.
The responses to some HTTP requests can be cached depending on the HTTP verb used
in the request. According to the HTTP specification, for what HTTP verbs is this safe to do?
A.
PUT, POST, DELETE
B.
GET, HEAD, POST
C.
GET, PUT, OPTIONS
D.
GET, OPTIONS, HEAD
GET, OPTIONS, HEAD
An API implementation is deployed to CloudHub. What conditions can be alerted on using the default Anypoint Platform functionality, where the alert conditions depend on the API invocations to an API implementation?
A. When the API invocations are sent directly to the internal DNS record of the API implementation
B. When the API invocations are not over-a- secure TLS/SSL communication channel
C. When the APL invecations originate from a geography different than the API
D. When the number of API invocations are below a threshold
A developer from the Central IT team has created an initial version of the RAML definition in Design Center for an OAuth 2.0-protected System API and published it to Exchange. Another developer from LoB IT discovered the System API in Exchange and would like to leverage it in the Process API. What is the MuleSoft-recommended approach for Process API to invoke the System API?
A. The Process API needs to import an CAuth 2.0 module from Exchange first and update it with OAuth 2.0 credentials before the System API can be invoked
B. The Process API uses property YAML files to store the System API URLs and uses the HTTP Request Connector to invoke the Systerm API
C. The Process APL uses the REST Connect Connector autogenerated in Exchange for the System API
D. The Process API manually updates the Process API POM file to include the System API as a dependency
Explanation:
In MuleSoft’s ecosystem, when a Process API needs to consume a System
API (published to Exchange and protected by OAuth 2.0), the recommended approach is to
utilize the REST Connect Connector. Here’s how it aligns with best practices:
A Mule application implements an API. The Mule application has an HTTP Listener whose connector configuration sets the HTTPS protocol and hard-codes the port value. The Mule application is deployed to an Anypoint VPC and uses the CloudHub 1.0 Shared Load Balancer (SLB) for all incoming traffic. Which port number must be assigned to the HTTP Listener's connector configuration so that the Mule application properly receives HTTPS API invocations routed through the SLB?
A. 8082
B. 8092
C. 80
D. 443
Explanation:
When using CloudHub 1.0’s Shared Load Balancer (SLB) for a Mule
application configured with HTTPS in an Anypoint VPC, specific ports must be configured
for the application to correctly route incoming traffic:
What is true about the technology architecture of Anypoint VPCs?
A.
The private IP address range of an Anypoint VPC is automatically chosen by CloudHub
B.
Traffic between Mule applications deployed to an Anypoint VPC and on-premises
systems can stay within a private network
C.
Each CloudHub environment requires a separate Anypoint VPC
D.
VPC peering can be used to link the underlying AWS VPC to an on-premises (non
AWS) private network
Traffic between Mule applications deployed to an Anypoint VPC and on-premises
systems can stay within a private network
Explanation: Explanation
Correct Answer: Traffic between Mule applications deployed to an Anypoint VPC and onpremises
systems can stay within a private network
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>> The private IP address range of an Anypoint VPC is NOT automatically chosen by
CloudHub. It is chosen by us at the time of creating VPC using thr CIDR blocks.
CIDR Block: The size of the Anypoint VPC in Classless Inter-Domain Routing (CIDR)
notation.
For example, if you set it to 10.111.0.0/24, the Anypoint VPC is granted 256 IP addresses
from 10.111.0.0 to 10.111.0.255.
Ideally, the CIDR Blocks you choose for the Anypoint VPC come from a private IP space,
and should not overlap with any other Anypoint VPC’s CIDR Blocks, or any CIDR Blocks in
use in your corporate network.
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)
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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.
An Order API must be designed that contains significant amounts of integration logic and
involves the invocation of the Product API.
The power relationship between Order API and Product API is one of "Customer/Supplier",
because the Product API is used heavily throughout the organization and is developed by a
dedicated development team located in the office of the CTO.
What strategy should be used to deal with the API data model of the Product API within the
Order API?
A.
Convince the development team of the Product API to adopt the API data model of the Order API such that the integration logic of the Order API can work with one consistent internal data model
B.
Work with the API data types of the Product API directly when implementing the integration logic of the Order API such that the Order API uses the same (unchanged) data types as the Product API
C.
Implement an anti-corruption layer in the Order API that transforms the Product API data
model into internal data types of the Order API
D.
Start an organization-wide data modeling initiative that will result in an Enterprise Data
Model that will then be used in both the Product API and the Order API
Implement an anti-corruption layer in the Order API that transforms the Product API data
model into internal data types of the Order API
Explanation: Explanation
Correct Answer: Convince the development team of the product API to adopt the API data
model of the Order API such that integration logic of the Order API can work with one
consistent internal data model
*****************************************
Key details to note from the given scenario:
>> Power relationship between Order API and Product API is customer/supplier
So, as per below rules of "Power Relationships", the caller (in this case Order API) would
request for features to the called (Product API team) and the Product API team would need
to accomodate those requests.
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