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Appian Certified Lead Developer ACD300 Prüfungsfragen mit Lösungen (Q23-Q28):

23. Frage
You are reviewing the Engine Performance Logs in Production for a single application thathas been live for six months. This application experiences concurrent user activity and has a fairly sustained load during business hours. The client has reported performance issues with the application during business hours.
During your investigation, you notice a high Work Queue - Java Work Queue Size value in the logs You also notice unattended process activities, including timer events and sending notifications emails, are taking far longer to execute than normal.
The client Increased the number of CPU cores prior to the application going live What is the next recommendation?

A. Add more application servers.
B. Add execution and analytics shards
C. Optimize slow-performing user interfaces.
D. Add more engine replicas.

Antwort: D

Begründung:
Explanation
Adding more engine replicas will increase the number of threads available to execute unattended process activities, such as timer events and sending notification emails. This will reduce the Java Work Queue Size and improve the performance of the application. Verified References: Appian Engine Performance Logs, Appian Engine Configuration

24. Frage
You are planning a strategy around data volume testing for an Appian application that queries and writes to MySQL database.
You have administrator access to the Appian application and to the database.
What are two key considerations when designing a data volume testing strategy?

A. Data model changes must wait until towards the end of the protect.
B. large datasets must be loaded via Applan processes
C. Data from previous tests needs to remain in the testing environment prior to loading prepopulated data
D. Testing with the correct amount of data should be in the definition of done as part of each sprint.
E. The amount of data that needs to be populated should be determined by the project sponsor and the stakeholders based on their estimation

Antwort: A,D

Begründung:
Explanation
When designing a data volume testing strategy for an Appian application that queries and writes to MySQL database, you should consider two key considerations:
* Testing with the correct amount of data should be in the definition of done as part of each sprint. Data volume testing is a type of testing that verifies how well an application performs when handling large amounts of data. Data volume testing is important to ensure that the application meets the performance and quality requirements of the users and stakeholders. By including data volume testing in the definition of done as part of each sprint, you can ensure that each feature or functionality of your application is tested with realistic data volumes before being delivered to production. This way, you can identify and resolve any potential issues or bottlenecks early in the development cycle, and avoid any surprises or delays later on.
* Data model changes must wait until towards the end of the project. Data model changes are changes that affect the structure or schema of your database, such as adding, modifying, or deleting tables, columns, indexes, or constraints. Data model changes are risky and costly to make, especially when dealing with large amounts of data. Data model changes can affect the performance, functionality, or integrity of your
* application and database. Therefore, data model changes must wait until towards the end of the project, when you have finalized your requirements and design decisions, and have minimized your data volume testing efforts. By waiting until towards the end of the project to make data model changes, you can reduce the impact and complexity of those changes, and avoid any unnecessary rework or regression.
The other options are not as effective. Option A, data from previous tests needs to remain in the testing environment prior to loading prepopulated data, is not a key consideration for designing a data volume testing strategy, but rather a best practice for preparing your testing environment. Option B, large datasets must be loaded via Appian processes, is not a key consideration for designing a data volume testing strategy, but rather a technical implementation detail that may or may not be suitable for your application. Option C, the amount of data that needs to be populated should be determined by the project sponsor and the stakeholders based on their estimation, is not a key consideration for designing a data volume testing strategy, but rather an input or assumption that you need to validate before conducting your data volume testing.

25. Frage
You are on a protect with an application that has been deployed to Production and is live with users. The client wishes to increase the number of active users.
You need to conduct load testing to ensure Production can handle the increased usage Review the specs for four environments in the following image.

Which environment should you use for load testing7

A. acme
B. acmedev
C. acmeuat
D. acmetest

Antwort: A

Begründung:
Explanation
The best environment to use for load testing is acme, which is the production environment. This is because load testing should be performed on an environment that is as close as possible to the actual production environment, in terms of hardware, software, configuration, data, and user behavior. This way, the results of the load testing will be more realistic and reliable, and can help to identify and resolve any performance issues or bottlenecks before increasing the number of active users. Verified References: Appian Documentation, section "Load Testing".

26. Frage
You are asked to design a case management system for a client in addition to storing some basic metadata about a case, one of the client s requirements Is the ability for users to update a case The client would like any user in their organization of 500 people to be able to make these updates The users are all based in the company's headquarters, and there will be frequent cases where users are attempting to edit the same case. The client wants to ensure no information Is lost when these edits occur and does not want the solution to burden their process administrators with any additional effort.
Which data locking approach should you recommend?

A. Add an Version annotation to the case COT to manage Vie locking
B. Allow edits without locking the case GDI
C. Use the database lo implement tow lewd pessimistic locking.
D. Design a process report and query to determine who opened the edit form first

Antwort: A

Begründung:
Explanation
The @Version annotation is a feature of Appian that allows for optimistic locking of CDTs. Optimistic locking assumes that concurrent updates to the same data are rare and does not lock the data until it is saved. If two users try to save changes to the same data, the user who saves first will succeed, while the user who saves second will get an error message and will have to resolve the conflict manually. This approach is suitable for the client's requirement, as itallows any user to update a case without locking it, ensures no information is lost when concurrent edits occur, and does not require any additional effort from the process administrators.
Verified References: [Appian Documentation], section "Optimistic Locking".

27. Frage
You are selling up a new cloud environment. The customer already has a system of record for Its employees and doesn't want to re-create them in Appian. so you are going to Implement LDAP authentication.
What are the next steps to configure LDAP authentication?
To answer, move the appropriate steps from the Option list to the Answer List area, and arrange them in the correct order. You may or may not use all the steps.

Antwort:

Begründung:

* Navigate to the Admin console > Authentication > LDAP. This is the first step, as it allows you to access the settings and options for LDAP authentication in Appian.
* Work with the customer LDAP point of contact to obtain the LDAP authentication xsd. Import the xsd file in the Admin console. This is the second step, as it allows you to define the schema and structure of the LDAP data that will be used for authentication in Appian. You will need to work with the customer LDAP point of contact to obtain the xsd file that matches their LDAP server configuration and data model. You will then need to import the xsd file in the Admin console using the Import Schema button.
* Enable LDAP and enter the LDAP parameters, such as the URL of the LDAP server and plaintext credentials. This is the third step, as it allows you to enable and configure the LDAP authentication in Appian. You will need to check the Enable LDAP checkbox and enter the required parameters, such as the URL of the LDAP server, the plaintext credentials for connecting to the LDAP server, and the base DN for searching for users in the LDAP server.
* Test the LDAP integration and see if it succeeds. This is the fourth and final step, as it allows you to verify and validate that the LDAP authentication is working properly in Appian. You will need
* to use the Test Connection button to test if Appian can connect to the LDAP server successfully.
You will also need to use the Test User Lookup button to test if Appian can find and authenticate a user from the LDAP server using their username and password.

28. Frage
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