Refer to the exhibit. An organization is running a Mule standalone runtime and has
configured Active Directory as the Anypoint Platform external Identity Provider. The organization does not have budget for other system components.
What policy should be applied to all instances of APIs in the organization to most
effecuvelyKestrict access to a specific group of internal users?
A.
Apply a basic authentication - LDAP policy; the internal Active Directory will be
configured as the LDAP source for authenticating users
B.
Apply a client ID enforcement policy; the specific group of users will configure their client applications to use their specific client credentials
C.
Apply an IP whitelist policy; only the specific users' workstations will be in the whitelist
D.
Apply an OAuth 2.0 access token enforcement policy; the internal Active Directory will be configured as the OAuth server
Apply a basic authentication - LDAP policy; the internal Active Directory will be
configured as the LDAP source for authenticating users
Explanation: Explanation
Correct Answer: Apply a basic authentication - LDAP policy; the internal Active Directory
will be configured as the LDAP source for authenticating users.
*****************************************
>> IP Whitelisting does NOT fit for this purpose. Moreover, the users workstations may not
necessarily have static IPs in the network.
>> OAuth 2.0 enforcement requires a client provider which isn't in the organizations system
components.
>> It is not an effective approach to let every user create separate client credentials and
configure those for their usage.
The effective way it to apply a basic authentication - LDAP policy and the internal Active
Directory will be configured as the LDAP source for authenticating users.
Reference: https://docs.mulesoft.com/api-manager/2.x/basic-authentication-ldap-concept
When could the API data model of a System API reasonably mimic the data model
exposed by the corresponding backend system, with minimal improvements over the
backend system's data model?
A.
When there is an existing Enterprise Data Model widely used across the organization
B.
When the System API can be assigned to a bounded context with a corresponding data
model
C.
When a pragmatic approach with only limited isolation from the backend system is deemed appropriate
D.
When the corresponding backend system is expected to be replaced in the near future
When a pragmatic approach with only limited isolation from the backend system is deemed appropriate
Explanation: Explanation
Correct Answer: When a pragmatic approach with only limited isolation from the backend
system is deemed appropriate.
*****************************************
General guidance w.r.t choosing Data Models:
>> If an Enterprise Data Model is in use then the API data model of System APIs should
make use of data types from that Enterprise Data Model and the corresponding API
implementation should translate between these data types from the Enterprise Data Model
and the native data model of the backend system.
>> If no Enterprise Data Model is in use then each System API should be assigned to a
Bounded Context, the API data model of System APIs should make use of data types from
the corresponding Bounded Context Data Model and the corresponding API
implementation should translate between these data types from the Bounded Context Data
Model and the native data model of the backend system. In this scenario, the data types in
the Bounded Context Data Model are defined purely in terms of their business
characteristics and are typically not related to the native data model of the backend system.
In other words, the translation effort may be significant.
>> If no Enterprise Data Model is in use, and the definition of a clean Bounded Context
Data Model is considered too much effort, then the API data model of System APIs should
make use of data types that approximately mirror those from the backend system, same
semantics and naming as backend system, lightly sanitized, expose all fields needed for
the given System API’s functionality, but not significantly more and making good use of
REST conventions.
The latter approach, i.e., exposing in System APIs an API data model that basically mirrors
that of the backend system, does not provide satisfactory isolation from backend systems
through the System API tier on its own. In particular, it will typically not be possible to
"swap out" a backend system without significantly changing all System APIs in front of that
backend system and therefore the API implementations of all Process APIs that depend on
those System APIs! This is so because it is not desirable to prolong the life of a previous
backend system’s data model in the form of the API data model of System APIs that now
front a new backend system. The API data models of System APIs following this approach
must therefore change when the backend system is replaced.
On the other hand:
>> It is a very pragmatic approach that adds comparatively little overhead over accessing
the backend system directly
>> Isolates API clients from intricacies of the backend system outside the data model
(protocol, authentication, connection pooling, network address, …)
>> Allows the usual API policies to be applied to System APIs
>> Makes the API data model for interacting with the backend system explicit and visible,
by exposing it in the RAML definitions of the System APIs
>> Further isolation from the backend system data model does occur in the API
An Order API triggers a sequence of other API calls to look up details of an order's items in
a back-end inventory database. The Order API calls the OrderItems process API, which
calls the Inventory system API. The Inventory system API performs database operations in
the back-end inventory database.
The network connection between the Inventory system API and the database is known to
be unreliable and hang at unpredictable times.
Where should a two-second timeout be configured in the API processing sequence so that
the Order API never waits more than two seconds for a response from the Orderltems
process API?
A. In the Orderltems process API implementation
B. In the Order API implementation
C. In the Inventory system API implementation
D. In the inventory database
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
*****************************************
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.
To minimize operation costs, a customer wants to use a CloudHub 1.0 solution. The
customer's requirements are:
A. One production and one non-production Virtual Private Cloud (VPC).
Use availability zones to differentiate between Business groups.
Allocate maximum CIDR per VPCs to ensure HA across availability zones
B. One production and one non-production Virtual Private Cloud (VPC) per Business
group.
Minimize CIDR aligning with projected application total.
Choose a MuleSoft CloudHub 1.0 region with multiple availability zones.
Deploy multiple workers for HA,
C. One production and one non-production Virtual Private Cloud (VPC) per Business
group.
Minimize CIDR aligning with projected application total.
Divide availability zones during deployment of APIs for HA.
D. One production and one non-production Virtual Private Claud (VPC).
Configure subnet to differentiate between business groups.
Allocate maximum CIDR per VPCs to make it easier to add Child groups.
Span VPC to cover three availability zones.
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)
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.
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
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