Pass the Salesforce Developer Development-Lifecycle-and-Deployment-Architect Questions and answers with ValidTests

Change sets provide an easy way to deploy related components, as they allow the user to select the components from a list and add them to the change set. They also provide a simple and declarative method for deployment, as they do not require any coding or scripting. Change sets do not provide the ability to deploy a very large number of components easily, as they have a limit of 10,000 components per change set. They also do not provide the ability to track changes to components, as they do not have any version control or history features.

Deploying metadata to production orgs using package development model is the best option for the multi-org deployment strategy, as it allows you to create modular and reusable packages that can be easily installed and updated across different orgs. Deploying metadata to production orgs using managed packages is not suitable for this scenario, as managed packages are typically used by ISVs to distribute their applications to customers, and they have some limitations and restrictions that may not fit the requirements of UC. Deploying metadata to production orgs using unmanaged packages is also not a good option, as unmanaged packages are mainly used for one-time distribution of components, and they do not support upgrades or dependencies. Deploying metadata to production orgs using change sets is not feasible for this scenario, as change sets can only be used to deploy metadata between connected orgs in the same Salesforce instance, and UC has separate orgs for each region. See [Package Development Model] for more details.

A source control tool provides the ability for distributed teams to work in isolation, as they can create branches and merge their changes later. It also provides the ability to backup code/configuration changes, as they can be stored in a remote repository and retrieved if needed.

User fields are preserved during metadata deployments and Salesforce attempts to locate a matching user in the target org during deployment. If the username in the source org doesn’t exist in the target org, the deployment will stop until the usernames are resolved or removed.

Creating design standards focused on integration and providing training to all teams is the best way to address the challenges of having various integration patterns and a lack of common understanding of the integration landscape. Design standards can help to establish consistent and best practices for integrating Salesforce with other systems, such as choosing the appropriate integration style, pattern, tool, and protocol. Training can help to educate and align the teams on the design standards and the integration architecture.

The problem is that UAT is on a preview release and SIT is not. A preview release is a version of Salesforce that contains the features and enhancements that will be available in the next major release. Preview releases are usually available a few weeks before the official release date, and they are assigned to a subset of instances. If UAT and SIT are on different instances, they may have different release versions, which can cause deployment issues. For example, if UAT has a preview release that contains some new metadata types that are not available in SIT, then deploying those metadata types from SIT to UAT will fail. To avoid this problem, the architect should check the Sandbox Preview Guide1 and the Release Notes2 to see if there are any changes that affect the deployment, and refresh and redeploy the sandboxes accordingly. There is a problem, and it is not expected behavior. Using the DX command line instead will not solve the problem, as it will still encounter the same version mismatch. SIT is not on a preview release and UAT is not, as that would not cause any deployment issues.

Implementing the change in the sandbox, validating, and releasing to production and considering that the integration with the ERP system may not function as expected are two considerations when addressing the requirement. The change should be performed in the sandbox first, as it is a best practice to test any changes in a non-production environment before deploying them to production. The change may also affect the integration with the ERP system, as it may require updating the mappings, validations, or transformations between the two systems.

This is the correct answer because having developers work in separate branches and merge their changes in a common branch for testing can reduce the risk of overwriting others’ changes and ensure code quality and consistency. Having all developers work in the same branch or in the HEAD may cause conflicts and errors. Not using source control is not a good practice and may result in data loss and lack of version control.

 Sandboxes should be refreshed based on the needs of the project and the development lifecycle. Production is the only pristine environment, so it is a good practice to refresh sandboxes from production regularly to ensure data and metadata consistency. Integration sandboxes should be refreshed frequently, not rarely, to avoid conflicts and errors when integrating code from multiple developers. Development environments should generally be refreshed after each working feature has been successfully migrated, to avoid accumulating unnecessary changes and to start fresh for the next feature.

 The best way to address the issue of hitting governor limits while testing Apex classes is to use test.startTest() and test.stopTest() methods to reset governor limits. These methods mark the start and end of the test code, and allow you to run your test code with a separate set of governor limits. There is no AppExchange product that can temporarily increase the governor limits, and there is no auto reset property or test.setLimit() and test.resetLimit() methods that can reset governor limits.

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