ACD200 Sample Questions Answers

 Two places to get information on process model memory usage are:

• Process monitoring tab. The process monitoring tab is a feature in the Appian Designer that allows you to monitor and manage the performance and status of process models and instances. You can use the process monitoring tab to view various metrics and statistics about your processes, such as memory usage, execution time, node count, error count, etc. You can also filter, sort, and export the data for further analysis. The process monitoring tab can help you identify which processes have the highest memory footprint and potential performance issues.
• Appian Health Check report. The Appian Health Check report is a tool that provides insights into application design patterns and performance risks in your environment. The report covers four areas of your environment: design, user experience, infrastructure, and configuration. The report also includes graphs highlighting historical trends, such as user activity, average response times, and resource utilization. The Appian Health Check report can help you identify which processes have the highest memory consumption and suggestions for mitigating them. References: Process Monitoring Tab, Understanding the Health Check Report

Two valid suggestions regarding this process are:

• We should consider adding a timer exception which skips the “Edit/Credit Invoice” node after 24 hours. This suggestion would improve the user experience by preventing users from editing or crediting an invoice that is too old or has been already processed by another system. A timer exception can be added to any activity node to specify a deadline for completing the task. If the deadline is reached, the process flow will follow the exception path instead of the normal path.
• We should add this process model as a related action on the Invoices record called “Edit Invoice.” This suggestion would make it easier for users to access and execute this process from the context of a specific invoice record. A related action is a process model that can be initiated from a record or a record list in Tempo or sites. A related action can use record data as inputs and update record data as outputs. References: Timer Exception, Create Record Actions

 The question is about troubleshooting slow response times on a SAIL interface. The following are two potential causes of the performance issues:

• Multiple a!save operations: This means that the interface has multiple expressions that use a!save to store data in variables or update components. This can cause performance issues, as each a!save operation triggers a server round-trip and refreshes all dependent components on the interface. You should minimize the use of a!save operations and use local variables or component parameters instead.
• Configuration of refresh variables: This means that the interface has components that use refresh variables to control when they should be refreshed based on changes in other components or variables. This can cause performance issues, as some components may be refreshed unnecessarily or too frequently due to incorrect or excessive refresh variables. You should optimize the refresh variables and use them only when needed.

The following are not likely causes of slow response times on a SAIL interface:

• Multiple rule inputs: This means that the interface has expressions that use rule inputs to pass data or parameters to expression rules. This does not affect the performance of the interface, as rule inputs are evaluated on the server and do not cause additional server round-trips or refreshes.
• Stacked button layout: This means that the interface has a layout component that arranges buttons in a vertical stack. This does not affect the performance of the interface, as it is a simple layout component that does not require any server interaction or refresh logic.

References:

• a!save()
• Refresh Variables
• Rule Inputs
• Stacked Button Layout

The most likely root cause of the error is that the view contains a large number of rows, requiring more time to fetch the data. This can result in a timeout or an out-of-memory error. To avoid this, you can use pagination or filters to limit the number of rows returned by the view. You can also optimize the view performance by using indexes, avoiding unnecessary joins, and reducing the number of columns. References: [Views], [View Performance]

According to Appian best practices, environment-specific constants should be used to define values that vary from one Appian environment to another. For example, if you want to generate an email body that contains the environment name, you can create a constant named ENVIRONMENT_NAME and assign it different values for DEV and TEST environments. This way, you can avoid hard-coding values in your expressions or rules, and simplify your deployment process by using automatic constant value mapping.

The question is about allowing external systems to invoke Appian web APIs. A service account is the user role that should be used for this purpose, as it is a special type of basic user that can be configured to authenticate with web APIs using an API key. A service account can also be assigned to specific groups or roles to control the access to web APIs. The other options are not user roles, but rather groups or user types that are not suitable for this purpose. References:

• Service Accounts
• Web API Security

A connected system is an Appian object that is designed to allow you to share base URL and authentication details across multiple integrations4. A connected system represents an external system that is integrated with Appian. Connected systems allow you to easily connect to external integrations and data sources. They also allow you to deploy connection information across environments and use different connection information for each environment. You can choose from different types of connected systems, such as HTTP, SQL, or pre-built connected systems for common services like Google Drive or Salesforce5.

Three possible reasons for high memory consumption of a process model are:

• Too many process variables. Process variables are used to store data that is needed throughout the process execution. However, having too many process variables can increase the memory usage of the process engine, especially if the variables store large or complex data types, such as documents or CDTs. It is recommended to use local variables whenever possible, and to delete or nullify process variables that are no longer needed.
• Nested CDTs with large numbers of fields. CDTs are custom data types that define the structure and validation of business data in Appian. CDTs can be nested within other CDTs to create complex data models. However, nesting CDTs with large numbers of fields can result in high memory consumption and performance degradation, as each field requires additional memory allocation and processing. It is recommended to limit the number of fields and nesting levels of CDTs, and to use references instead of embedding whenever possible.
• Too many nodes. Nodes are the graphical elements that represent the activities and events in a process model. Having too many nodes in a process model can increase the memory usage and complexity of the process execution. It can also make the process model harder to read and maintain. It is recommended to simplify the process model by using subprocesses, smart services, or expression rules to encapsulate common or reusable logic. References: Process Variables, Custom Data Types, Process Model Best Practices

 The type of plug-in that should be created to perform a job in the background and not be available under an expression rule, connected system, or the process model is a servlet plug-in. A servlet plug-in is a plug-in that allows you to create custom servlets that can be accessed through a URL. Servlets are Java classes that run on a web server and handle requests and responses. Servlet plug-ins can be used to perform background tasks, such as sending notifications, logging events, or integrating with external systems, without exposing them to the end users or developers. References: Servlet Plug-ins, Appian Suite Plug-ins

 The question is about AMUs (Appian Memory Units), which is a metric that measures the memory usage of a process model. The following statement is correct regarding this metric:

• Memory usage is considered low when it is below 100,000 AMUs. This is based on the Appian recommendation that each process model should use less than 100,000 AMUs on average, as higher memory usage can affect the performance or stability of Appian.

The following statements are not correct regarding this metric:

• Memory usage is considered low when it is below 10,000 AMUs. This is too low, as most process models will use more than 10,000 AMUs on average, depending on their complexity and data size.
• Memory usage is considered low when it is below 1,000 AMUs. This is too low, as even simple process models will use more than 1,000 AMUs on average, depending on their configuration and parameters.
• AMUs is not a good measurement for process memory usage. This is not true, as AMUs is a standardized and consistent measurement that reflects the relative memory usage of different process models in Appian.

References:

• AMUs (Appian Memory Units)

The @Version annotation is used to avoid the collision of data from an application when more than one user is editing the same record in a database. The @Version annotation enables optimistic locking, which is a mechanism to detect and prevent concurrent updates on the same record. Optimistic locking assumes that multiple transactions can complete without affecting each other, and that therefore transactions do not need to lock data resources until they are ready to commit. However, if a transaction tries to commit changes to a record that has been modified by another transaction since it was last read, an OptimisticLockException is thrown and the transaction is rolled back. The @Version annotation can be applied to a field or property of a CDT that stores a numeric value. This value is used as a version number that is automatically incremented by Appian every time the record is updated. References: Does Appian support @Version JPA Annotation?, JPA - Optimistic Locking and Use of @Version annotation

 Creating a trigger on the database table to capture the audit trail to a table is the most efficient and has the least impact on the Appian application, because it avoids adding extra logic or calls to the Appian application, which could affect its performance and scalability. A trigger is a database object that automatically executes when a specified event occurs on a table or view. A trigger can be used to insert, update, or delete data from another table based on the changes made to the original table. References: [Triggers], [Audit Trail]

 The best way to restrict the uploading of documents without extensions at the environment level is to enable the File Upload > Block files without an extension option under the Administration Console. This option will prevent users from uploading files that do not have a valid file extension, such as .docx, .pdf, or .png. This can help to avoid security risks and compatibility issues with unsupported file types. Therefore, the correct answer is A.

References:

• [File Upload Settings]
• [File Extensions]

 Activity chaining is a feature that allows users to complete multiple tasks in a row without returning to their task list. However, activity chaining can also have some drawbacks, such as increased memory consumption, longer transaction times, and reduced user feedback. Therefore, some practices are strongly discouraged for activity chaining, such as having more than 50 node instances or more than 5 seconds between attended activities. These practices can cause performance issues, user frustration, or process failures. Therefore, the correct answers are B and C.

References:

• Activity Chaining
• Performance Best Practices

An index is a data structure that allows for faster retrieval of data from a table based on one or more columns. Indexes increase the performance of read operations, such as select queries, by reducing the number of records that need to be scanned. However, indexes decrease the performance of write operations, such as insert, update, and delete queries, by requiring additional work to maintain the index structure and ensure its consistency with the table data. Therefore, indexes should be used judiciously and only on columns that are frequently used in queries and have high selectivity (i.e., low number of duplicate values). 

In Scrum, the product owner is the person who represents the voice of the customer and the stakeholders. The product owner is responsible for defining and prioritizing the product backlog, which is a list of features, requirements, enhancements, and fixes that need to be delivered by the team. The product owner collaborates with the team and the scrum master to ensure that the product backlog is clear, valuable, and aligned with the product vision and goals.

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

A joining table can be used to hold instances of Student/Class relationships, so that it can be supported in Appian and remain in at least First Normal Form. A joining table is a table that contains only foreign keys that reference the primary keys of other tables. A joining table can be used to model a Many-to-Many relationship between two entities, such as Student and Class. For example, a joining table called Enrollment could have two columns: Student_ID and Class_ID, which reference the primary keys of the Student and Class tables respectively. Each row in the Enrollment table represents an instance of a student enrolled in a class. References: [Joining Tables], [Many-to-Many Relationships], [First Normal Form]

The most efficient method to insert the deleted row of a table into a history table for audit purposes is Trigger. This is because a trigger is a database object that automatically executes a specified SQL statement when a certain event occurs on a table or view. A trigger can be defined to run before or after a delete operation on a table, and can access the deleted row using a special table called deleted. A trigger can perform the insertion of the deleted row into the history table without any additional logic or overhead from Appian. References: Triggers