Free MuleSoft-Integration-Architect-I Exam Braindumps (page: 25)

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An organization is implementing a Quote of the Day API that caches today's quote.
What scenario can use the CloudHub Object Store connector to persist the cache's state?

  1. When there is one deployment of the API implementation to CloudHub and another one to customer hosted mule runtime that must share the cache state.
  2. When there are two CloudHub deployments of the API implementation by two Anypoint Platform business groups to the same CloudHub region that must share the cache state.
  3. When there is one CloudHub deployment of the API implementation to three workers that must share the cache state.
  4. When there are three CloudHub deployments of the API implementation to three separate
    CloudHub regions that must share the cache state.

Answer(s): C

Explanation:

Object Store Connector is a Mule component that allows for simple key-value storage. Although it can serve a wide variety of use cases, it is mainly design for: - Storing synchronization information, such as watermarks. - Storing temporal information such as access tokens. - Storing user information. Additionally, Mule Runtime uses Object Stores to support some of its own components, for example:
- The Cache module uses an Object Store to maintain all of the cached data. - The OAuth module (and every OAuth enabled connector) uses Object Stores to store the access and refresh tokens. Object Store data is in the same region as the worker where the app is initially deployed. For example, if you deploy to the Singapore region, the object store persists in the Singapore region. MuleSoft Reference : https://docs.mulesoft.com/object-store-connector/1.1/ Data can be shared between different instances of the Mule application. This is not recommended for Inter Mule app communication. Coming to the question, object store cannot be used to share cached data if it is deployed as separate Mule applications or deployed under separate Business Groups. Hence correct answer is When there is one CloudHub deployment of the API implementation to three workers that must share the cache state.



An organization has several APIs that accept JSON data over HTTP POST. The APIs are all publicly available and are associated with several mobile applications and web applications. The organization does NOT want to use any authentication or compliance policies for these APIs, but at the same time, is worried that some bad actor could send payloads that could somehow compromise the applications or servers running the API implementations.
What out-of-the-box Anypoint Platform policy can address exposure to this threat?

  1. Apply a Header injection and removal policy that detects the malicious data before it is used
  2. Apply an IP blacklist policy to all APIs; the blacklist will Include all bad actors
  3. Shut out bad actors by using HTTPS mutual authentication for all API invocations
  4. Apply a JSON threat protection policy to all APIs to detect potential threat vectors

Answer(s): D

Explanation:

We need to note few things about the scenario which will help us in reaching the correct solution. Point 1 : The APIs are all publicly available and are associated with several mobile applications and web applications. This means Apply an IP blacklist policy is not viable option. as blacklisting IPs is limited to partial web traffic. It can't be useful for traffic from mobile application Point 2 : The organization does NOT want to use any authentication or compliance policies for these APIs. This means we can not apply HTTPS mutual authentication scheme.
Header injection or removal will not help the purpose.
By its nature, JSON is vulnerable to JavaScript injection.
When you parse the JSON object, the malicious code inflicts its damages. An inordinate increase in the size and depth of the JSON payload can indicate injection. Applying the JSON threat protection policy can limit the size of your JSON

payload and thwart recursive additions to the JSON hierarchy.
Hence correct answer is Apply a JSON threat protection policy to all APIs to detect potential threat vectors



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?

  1. Set a timeout of 100 ms; that leaves 400 ms for the other two downstream APIs to complete
  2. Do not set a timeout; the Invocation of this API Is mandatory and so we must wait until it responds
  3. Set a timeout of 50 ms; this times out more invocations of that API but gives additional room for retries
  4. 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

Answer(s): D

Explanation:

Before we answer this question , we need to understand what median (50th percentile) and 80th percentile means. If the 50th percentile (median) of a response time is 500ms that means that 50% of my transactions are either as fast or faster than 500ms.
If the 90th percentile of the same transaction is at 1000ms it means that 90% are as fast or faster and only 10% are slower. Now as per upstream SLA , 99th percentile is 800 ms which means 99% of the incoming requests should have response time less than or equal to 800 ms. But as per one of the backend API , their 95th percentile is 1000 ms which means that backend API will take 1000 ms or less than that for 95% of. requests. As there are three API invocation from upstream API , we can not conclude a timeout that can be set to meet the desired SLA as backend SLA's do not support it.
Let see why other answers are not correct.
1) Do not set a timeout --> This can potentially violate SLA's of upstream API
2) Set a timeout of 100 ms; ---> This will not work as backend API has 100 ms as median meaning only 50% requests will be answered in this time and we will get timeout for 50% of the requests.

Important thing to note here is, All APIs need to be executed sequentially, so if you get timeout in first API, there is no use of going to second and third API. As a service provider you wouldn't want to keep 50% of your consumers dissatisfied. So not the best option to go with. *To quote an example: Let's assume you have built an API to update customer contact details.
- First API is fetching customer number based on login credentials
- Second API is fetching Info in 1 table and returning unique key
- Third API, using unique key provided in second API as primary key, updating remaining details
* Now consider, if API times out in first API and can't fetch customer number, in this case, it's useless to call API 2 and 3 and that is why question mentions specifically that all APIs need to be executed sequentially.
3) Set a timeout of 50 ms --> Again not possible due to the same reason as above Hence correct answer is 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



An API has been updated in Anypoint Exchange by its API producer from version 3.1.1 to 3.2.0 following accepted semantic versioning practices and the changes have been communicated via the API's public portal. The API endpoint does NOT change in the new version. How should the developer of an API client respond to this change?

  1. The update should be identified as a project risk and full regression testing of the functionality that uses this API should be run.
  2. The API producer should be contacted to understand the change to existing functionality.
  3. The API producer should be requested to run the old version in parallel with the new one.
  4. The API client code ONLY needs to be changed if it needs to take advantage of new features.

Answer(s): D

Explanation:

* Semantic Versioning is a 3-component number in the format of X.Y.Z, where :
X stands for a major version.
Y stands for a minor version:
Z stands for a patch.
So, SemVer is of the form Major.Minor.Patch Coming to our question , minor version of the API has been changed which is backward compatible. Hence there is no change required on API client end. If they want to make use of new featured that have been added as a part of minor version change they may need to change code at their end. Hence correct answer is The API client code ONLY needs to be changed if it needs to take advantage of new features.



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