What is a key difference between synchronous and asynchronous logging from Mule applications?
Answer(s): B
Types of logging:A) Synchronous: The execution of thread that is processing messages is interrupted to wait for the log message to be fully handled before it can continue.The execution of the thread that is processing your message is interrupted to wait for the log message to be fully output before it can continuePerformance degrades because of synchronous loggingUsed when the log is used as an audit trail or when logging ERROR/CRITICAL messages If the logger fails to write to disk, the exception would raise on the same thread that's currently processing the Mule event. If logging is critical for you, then you can rollback the transaction.B) Asynchronous:The logging operation occurs in a separate thread, so the actual processing of your message won't be delayed to wait for the logging to completeSubstantial improvement in throughput and latency of message processing Mule runtime engine (Mule) 4 uses Log4j 2 asynchronous logging by default The disadvantage of asynchronous logging is error handling. If the logger fails to write to disk, the thread doing the processing won't be aware of any issues writing to the disk, so you won't be able to rollback anything. Because the actual writing of the log gets differed, there's a chance that log messages might never make it to disk and get lost, if Mule were to crash before the buffers are flushed.-----------------------------------------------------------------------------------------------------------------So Correct answer is: Asynchronous logging can improve Mule event processing throughput while also reducing the processing time for each Mule event
A global, high-volume shopping Mule application is being built and will be deployed to CloudHub. To improve performance, the Mule application uses a Cache scope that maintains cache state in a CloudHub object store. Web clients will access the Mule application over HTTP from all around the world, with peak volume coinciding with business hours in the web client's geographic location. To achieve optimal performance, what Anypoint Platform region should be chosen for the CloudHub object store?
Answer(s): A
CloudHub object store should be in same region where the Mule application is deployed. This will give optimal performance.Before learning about Cache scope and object store in Mule 4 we understand what is in general Caching is and other related things.WHAT DOES "CACHING" MEAN?Caching is the process of storing frequently used data in memory, file system or database which saves processing time and load if it would have to be accessed from original source location every time.In computing, a cache is a high-speed data storage layer which stores a subset of data, so that future requests for that data are served up faster than is possible by accessing the data's primary storage location. Caching allows you to efficiently reuse previously retrieved or computed data.How does Caching work?The data in a cache is generally stored in fast access hardware such as RAM (Random-access memory) and may also be used in correlation with a software component. A cache's primary purpose is to increase data retrieval performance by reducing the need to access the underlying slower storage layer.Caching in MULE 4In Mule 4 caching can be achieved in mule using cache scope and/or object-store. Cache scope internally uses Object Store to store the data.What is Object StoreObject Store lets applications store data and states across batch processes, Mule components, and applications, from within an application. If used on cloud hub, the object store is shared between applications deployed on Cluster.Cache Scope is used in below-mentioned cases:Need to store the whole response from the outbound processor Data returned from the outbound processor does not change very frequently As Cache scope internally handle the cache hit and cache miss scenarios it is more readable Object Store is used in below-mentioned cases:Need to store custom/intermediary dataTo store watermarksSharing the data/stage across applications, schedulers, batch.If CloudHub object store is in same region where the Mule application is deployed it will aid in fast access of data and give optimal performance.
An organization is evaluating using the CloudHub shared Load Balancer (SLB) vs creating a CloudHub dedicated load balancer (DLB). They are evaluating how this choice affects the various types of certificates used by CloudHub deployed Mule applications, including MuleSoft-provided, customerprovided, or Mule application-provided certificates. What type of restrictions exist on the types of certificates for the service that can be exposed by the CloudHub Shared Load Balancer (SLB) to external web clients over the public internet?
Correct answer is Only MuleSoft provided certificates can be used for server side certificate* The CloudHub Shared Load Balancer terminates TLS connections and uses its own server-side certificate.* You would need to use dedicated load balancer which can enable you to define SSL configurations to provide custom certificates and optionally enforce two-way SSL client authentication.* To use a dedicated load balancer in your environment, you must first create an Anypoint VPC. Because you can associate multiple environments with the same Anypoint VPC, you can use the same dedicated load balancer for your different environments.Additional Info on SLB Vs DLB:
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?
Answer(s): C
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?
Answer(s): D
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
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