Free Appian ACD300 Practice Exam with Questions & Answers

The three required steps that will allow you to connect both systems are:

• A. Create a Web API object and set up the correct security. This will allow you to define an endpoint in Appian that can receive requests from Jira via webhook. You will also need to configure the security settings for the Web API object, such as authentication method, allowed origins, and access control.
• B. Configure the connection in Jira specifying the URL and credentials. This will allow you to set up a webhook in Jira that can send requests to Appian when specific tickets change. You will need to specify the URL of the Web API object in Appian, as well as any credentials required for authentication.
• C. Create a new API Key and associate a service account. This will allow you to generate a unique token that can be used for authentication between Jira and Appian. You will also need to create a service account in Appian that has permissions to access or update data related to Jira tickets.

The other options are incorrect for the following reasons:

• D. Give the service account system administrator privileges. This is not required and could pose a security risk, as giving system administrator privileges to a service account could allow it to perform actions that are not related to Jira tickets, such as modifying system settings or accessing sensitive data.
• E. Create an integration object from Appian to Jira to periodically check the ticket status. This is not required and could cause unnecessary overhead, as creating an integration object from Appian to Jira would involve polling Jira for ticket status changes, which could consume more resources than using webhook notifications. Verified References: Appian Documentation, section “Web API” and “API Keys”.

The three things that might help to address the findings of the Health Check report are:

• B. Optimize the database execution using standard database performance troubleshooting methods and tools (such as query execution plans). This can help to identify and eliminate any bottlenecks or inefficiencies in the database queries that are causing slow query rules or slow write to data store nodes.
• C. Reduce the size and complexity of the inputs. If you are passing in a list, consider whether the data model can be redesigned to pass single values instead. This can help to reduce the amount of data that needs to be transferred or processed by the database, which can improve the performance and speed of the queries or writes.
• E. Use smaller CDTs or limit the fields selected in a!queryEntity(). This can help to reduce the amount of data that is returned by the queries, which can improve the performance and speed of the rules that use them.

The other options are incorrect for the following reasons:

• A. Reduce the batch size for database queues to 10. This might not help to address the findings, as reducing the batch size could increase the number of transactions and overhead for the database, which could worsen the performance and speed of the queries or writes.
• D. Optimize the database execution. Replace the new with a materialized view. This might not help to address the findings, as replacing a view with a materialized view could increase the storage space and maintenance cost for the database, which could affect the performance and speed of the queries or writes. Verified References: Appian Documentation, section “Performance Tuning”.

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”.

Functional acceptance criteria are the conditions that a user story must satisfy to be accepted by the user or stakeholder. They should be specific, measurable, achievable, relevant, and testable. In this case, two functional acceptance criteria that would be considered ‘good’ are:

• The user will receive an email notification when their order is completed. This is a specific, measurable, achievable, relevant, and testable criterion that describes a feature that the user needs to be informed of their order status.
• The user cannot submit the form without filling out all required fields. This is a specific, measurable, achievable, relevant, and testable criterion that describes afeature that the user needs to provide valid and complete information for their order.

The other options are not as good. Option A, the user will click Save, and the order information will be saved in the ORDER table and have audit history, is not a functional acceptance criterion, but rather a technical implementation detail that is not relevant or visible to the user. Option C, the system must handle up to 500 unique orders per day, is not a functional acceptance criterion, but rather a non-functional requirement that describes a performance or quality attribute of the system.

Indexing columns can improve the performance of queries that use those columns in filters, joins, or order by clauses. In this case, the columns that should be indexed are site_id, status, and priority, because they are used for filtering or joining the tables. Site_id is used to join the case and site tables, so indexing it will speed up the join operation. Status and priority are used to filter the cases by the user’s input, so indexing them will reduce the number of rows that need to be scanned. Name, modified_date, and case_id do not need to be indexed, because they are not used for filtering or joining. Name and modified_date are only used for displaying information in the record grid, and case_id is only used as a unique identifier for each record. Verified References: Appian Records Tutorial, Appian Best Practices

The two formats that are available for data generation using an out-of-the-box Appian smart service are:

• A. CSV. This is a comma-separated values format that can be used to export data in a tabular form, such as records, reports, or grids. CSV files can be easily opened and manipulated by spreadsheet applications such as Excel or Google Sheets.
• C. Excel. This is a format that can be used to export data in a spreadsheet form, with multiple worksheets, formatting, formulas, charts, and other features. Excel files can be opened by Excel or other compatible applications.

The other options are incorrect for the following reasons:

• B. XML. This is a format that can be used to export data in a hierarchical form, using tags and attributes to define the structure and content of the data. XML files can be opened by text editors or XML parsers, but they are not supported by the out-of-the-box Appian smart service for data generation.
• D. JSON. This is a format that can be used to export data in a structured form, using objects and arrays to represent the data. JSON files can be opened by text editors or JSON parsers, but they are not supported by the out-of-the-box Appian smart service for data generation. Verified References: Appian Documentation, section “Write to Data Store Entity” and “Write to Multiple Data Store Entities”.

The best way to divide the work between the teams, avoiding issues caused by cross-dependency, is to group epics and stories by feature, and allocate work between each team by feature. This way, each team can focus on a specific feature and minimize the need for coordination or integration with the other team. This also reduces the risk of conflicts or errors when merging the code from both teams. Verified References: Appian Documentation, section “Agile Development”.

To build a large scale acquisition application for a prominent customer, you should design for multiple processes and forms, while minimizing repeated code. One way to do this is to create a common objects application, which is a shared application that contains reusable components, such as rules, constants, interfaces, integrations, or data types, that can be used by multiple applications. This way, you can avoid duplication and inconsistency of code, and make it easier to maintain and update your applications. You can also use the common objects application to define common standards and best practices for your application development teams, such as naming conventions, coding styles, or documentation guidelines. Verified References: [Appian Best Practices], [Appian Design Guidance]

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

To create an integration from your Appian cloud instance to an application hosted within a customer’s self-managed environment, you need to ensure that there is a secure and reliable connection between the two systems. One way to do this is to set up a VPN tunnel, which is a virtual private network that encrypts and transports data over the internet. A VPN tunnel allows you to access the customer’s internal network and API endpoint from your Appian cloud instance, without exposing them to the public internet. This way, you can ensure the security and privacy of the data that is exchanged between the two systems. Verified References: [Appian Cloud VPN], [Appian Integration Guide]