Appian ACD200 Exam With Confidence Using Practice Dumps

The question is about the recommendations for Appian environment to address the performance risk of a large increase in users. The following are two recommendations for this purpose:

• Add more process execution engines. This means adding more servers or nodes that can execute process instances in parallel, which can improve the scalability and availability of Appian. This can help handle the increased workload and demand from more users without affecting the response time or reliability of Appian.
• Add more application server memory. This means increasing the amount of memory allocated to each server or node that runs Appian components, such as web servers, engines, or analytics servers. This can help improve the performance and stability of Appian by reducing memory pressure and garbage collection.

The following are not recommendations for Appian environment to address the performance risk of a large increase in users:

• Add more design engines. This means adding more servers or nodes that can execute expression rules or interface components in parallel, which can improve the performance and scalability of Appian. However, this is not directly related to the number of users, but rather to the complexity and frequency of expression rules or interface components in the application.
• Switch from a records-centric to a process-centric design. This means changing the application design to focus more on process models and tasks, rather than records and reports. This does not affect the Appian environment, but rather the application logic and functionality. This may or may not improve the performance of the application, depending on the requirements and use cases.

References:

• Process Execution Engines
• Memory Recommendations
• Design Engines
• Records-Centric vs Process-Centric Design

 The metric from the data_store_details.csv file that will help you understand the number of operations against data store is Total Count. This metric represents the total number of queries, inserts, updates, deletes, and executes performed against the data store during the specified time period. You can use this metric to identify which data stores are heavily used and may need performance tuning or scaling. References: [Data Store Details Report], [Data Store Metrics]

The question is about referencing and using arrays of a CDT (Custom Data Type). The following statements are true:

• There is no difference between using “dot notation” and the index() function. Both methods can be used to access elements of an array by their position. For example, if a is an array of CDTs, then a[1] and index(a, 1) will return the same element.
• An array of integers can be passed as the second parameter to the index() function to return the data at those positions in the array. For example, if a is an array of CDTs, then index(a, {1, 3, 5}) will return an array of CDTs containing the elements at positions 1, 3, and 5 in a.

The following statements are false:

• Other Appian functions can be used within the square brackets “[]” when using dot notation to return specific data from the array. This is not possible, as dot notation only accepts integers or integer arrays as indices. For example, if a is an array of CDTs, then a[length(a)] will cause an error, as length(a) is not a valid index.
• The function wherecontains can act on operands of different types. This is not true, as wherecontains only works on operands of the same type. For example, if a is an array of CDTs and b is an array of integers, then wherecontains(a, b) will cause an error, as a and b are not of the same type.

References:

• Dot Notation
• index()
• wherecontains()