Adobe AD0-E722 Practice Test - Questions Answers, Page 3

The carrier model class can implement caching methods to store and retrieve the quotes from the API based on the request parameters. This can reduce the number of API calls and improve the performance of the shipping rate calculation. The _setCachedQuotes() method can save the response from the API to a cache storage, and the _getCachedQuotes() method can check if there is a cached response for the current request and return it if it exists.Reference:Caching in carrier model,Carrier model interface

To make sure the vcl_hash function of Varnish considers the newly created attribute, the Architect needs to do the following steps:

Create a new class that implements the Magento\GraphQlCache\Model\CacheId\CacheIdFactorProviderInterface interface. This interface defines two methods: getFactorName and getFactorValue. The getFactorName method should return the name of the attribute, in this case, my_attribute.The getFactorValue method should return the value of the attribute for the current customer, which can be obtained from the customer session or customer repository1.

Add this class to the idFactorProviders array of Magento\GraphQlCache\Model\CacheId\CacheIdCalculator through dependency injection. The CacheIdCalculator is responsible for generating a cache ID for each GraphQL request based on the factors provided by the idFactorProviders.By adding the new class to this array, the Architect ensures that the cache ID will include the value of my_attribute1.

The cache ID is then used by Varnish to hash and lookup the cached response for each request.By including my_attribute in the cache ID, the Architect ensures that Varnish will serve different responses based on the attribute value of the customer2.Reference:

Magento_GraphQlCache module | Magento 2 Developer Documentation

Varnish caching | Adobe Commerce 2.4 User Guide - Magento

To create an integration test that executes different logic in different store views, the Architect needs to do the following steps:

Create one test class that extends \Magento\TestFramework\TestCase\AbstractController or \Magento\TestFramework\TestCase\AbstractBackendController, depending on the type of controller being tested1.

Create one test method that uses the @magentoDataFixture annotation to specify the data fixture file that creates the product2.

Use the \Magento\TestFramework\Store\ExecuteInStoreContext class to execute the fixture and the tested logic in different store views. This class has a method called executeInStoreContext, which takes two parameters: the store ID and a callable function.The callable function will be executed in the context of the given store ID, and then the original store ID will be restored3. For example:

PHPAI-generated code. Review and use carefully.More info on FAQ.

public function testSomeLogic()

{

// Get the product from the fixture

$product = $this->getProduct();

// Get the ExecuteInStoreContext instance from the object manager

$executeInStoreContext = $this->_objectManager->get(\Magento\TestFramework\Store\ExecuteInStoreContext::class);

// Execute the fixture in store view 3

$executeInStoreContext->executeInStoreContext(3, function () use ($product) {

// Do some operations on the product in store view 3

});

// Execute the tested logic in store view 4

$result = $executeInStoreContext->executeInStoreContext(4, function () use ($product) {

// Call the tested logic on the product in store view 4

return $this->someLogic->execute($product);

});

// Assert that the result is true

$this->assertTrue($result);

}

Integration tests | Magento 2 Developer Documentation

Data fixtures | Magento 2 Developer Documentation

Magento\TestFramework\Store\ExecuteInStoreContext | Magento 2 Developer Documentation

The product price index can be optimized by using parallel mode and customer group merging. Parallel mode allows the indexer to run multiple threads simultaneously, which can speed up the indexing process. Customer group merging reduces the number of rows in the price index table by merging customer groups that have the same product prices. This can improve the performance of the price index queries and reduce the index size.Reference:Indexing optimization,Price index customer group merging

The Architect should recommend replacing all Vendor\PaymentModule\Gateway\Config\Config Classes with virtualType of Magento\Payment\Gateway\Config\Config and setting <user_secret backend_Model=''Magento\Config\Model\Config\Backend\Encrypted'' /> under config.xml. This will avoid redundant dependency and duplicate code among the methods. The virtualType of Magento\Payment\Gateway\Config\Config will inherit the functionality of the base class and allow the customization of the constructor arguments, such as the pathPattern and valueHandlerPool.The backend_Model attribute of the user_secret field will specify that the value of this field should be encrypted and decrypted by the Magento\Config\Model\Config\Backend\Encrypted class, which implements the \Magento\Framework\App\Config\ValueInterface interface and uses the \Magento\Framework\Encryption\EncryptorInterface internally12.This way, the payment modules do not need to depend on the \Magento\Framework\Encryption\EncryptorInterface or the \Magento\Framework\App\Config\ScopeConfigInterface directly, and can use the getValue method of the Magento\Payment\Gateway\Config\Config class to get the decrypted value of the user_secret field3.Reference:

How to encrypt system configuration fields in Magento 2 - Mageplaza

Magento 2: How to Encrypt/Decrypt System Configuration Fields - Webkul Blog

Magento 2: How to create custom payment method - BelVG Blog

The issue is being caused by the high coupling between objects (CBO) value of the class MyService.CBO is a metric that measures the number of classes that are coupled to a given class, either by method calls, property or parameter references, inheritance, or constants1.A high CBO value indicates that the class is too tightly coupled with other classes, which makes it more difficult to maintain, test, and reuse2. To reduce the CBO value, the Architect should introduce a new class that encapsulates the five scalar parameters that configure the behavior of MyService. This way, the constructor of MyService will only have one parameter of the new class type, instead of five scalar parameters. This will also make the code more readable and maintainable, as the new class can provide methods to access and manipulate the configuration data.The constants referencing other classes should not be consolidated into a string representation, as this would not reduce the CBO value and would make the code less clear and type-safe3.The number of different classes and interfaces referenced anywhere inside the class is not relevant for the CBO metric, as it only counts the classes that are coupled to the given class1.Reference:CBO coupling between object,Coupling Between Object classes (CBO),Cohesion and coupling of an object in OO programming

Option A is correct because enabling asynchronous indexing can improve the checkout performance by reducing the database load and avoiding locking issues. Asynchronous indexing allows the indexers to run in the background without affecting the frontend operations.The commandbin/magento config:set dev/grid/async_indexing 1can be used to enable this option in the production mode1.

Option C is correct because creating a new database and splitting the sales tables can also improve the checkout performance by distributing the database load and avoiding contention. Splitting the database allows the checkout and order management operations to use a separate master database from the rest of the Magento application tables.The commandbin/magento setup:db-schema:split-sales --host='<checkout db host or ip>' --dbname='<name>' --username='<checkout db username>' --password=''can be used to configure this feature2.

Option B is incorrect because enabling asynchronous email notifications does not affect the checkout performance directly. Asynchronous email notifications allow the order confirmation emails to be sent in batches by a cron job instead of immediately after placing an order.This option can reduce the server load and improve the customer experience, but it does not impact the checkout process itself3.

Option D is incorrect because there is no such deploy mode as siege in Magento 2. The available deploy modes are default, developer, and production.Changing the deploy mode can affect the performance, caching, and error handling of the Magento application, but it does not directly affect the checkout performance4.

Option E is incorrect because there is no such admin panel setting as multithreaded checkout processing in Magento 2. The number of PHP threads used for checkout is determined by the web server configuration and the PHP-FPM settings, not by the Magento application settings.Increasing the number of PHP threads may improve the checkout performance, but it also requires more server resources and may cause other issues5.

1: Asynchronous indexing | Adobe Commerce Developer Guide

2: Split database performance solution | Adobe Commerce Developer Guide

3: Sales Emails | Adobe Commerce User Guide

4: Set up Magento modes | Adobe Commerce Developer Guide

5: PHP-FPM configuration settings | Adobe Commerce Developer Guide

The issue is being caused by the use of @magentoDataFixture annotation, which creates a temporary data fixture that is rolled back after each test execution1. This means that the customer address created by the fixture is not persisted in the database and cannot be retrieved by subsequent tests.To fix this, the Architect should use @magentoPersistDataFixture annotation, which creates a permanent data fixture that is not rolled back after each test execution2. This way, the customer address created by the fixture will be persisted in the database and can be accessed by subsequent tests.Changing the annotation to use @magentoApiDataFixture or specifying address_id in the annotation will not solve the issue, as they are not related to the persistence of the data fixture3.Reference:Data fixtures,Persistent data fixtures,API-functional tests