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Title: ACD301 Test Guide Online & ACD301 Valid Test Review [Print This Page]
Author: rickdav409    Time: 1/22/2026 15:57
Title: ACD301 Test Guide Online & ACD301 Valid Test Review
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Appian ACD301 Exam Syllabus Topics:
TopicDetails
Topic 1
  • Data Management: This section of the exam measures skills of Data Architects and covers analyzing, designing, and securing data models. Candidates must demonstrate an understanding of how to use Appian¡¯s data fabric and manage data migrations. The focus is on ensuring performance in high-volume data environments, solving data-related issues, and implementing advanced database features effectively.
Topic 2
  • Application Design and Development: This section of the exam measures skills of Lead Appian Developers and covers the design and development of applications that meet user needs using Appian functionality. It includes designing for consistency, reusability, and collaboration across teams. Emphasis is placed on applying best practices for building multiple, scalable applications in complex environments.
Topic 3
  • Project and Resource Management: This section of the exam measures skills of Agile Project Leads and covers interpreting business requirements, recommending design options, and leading Agile teams through technical delivery. It also involves governance, and process standardization.
Topic 4
  • Platform Management: This section of the exam measures skills of Appian System Administrators and covers the ability to manage platform operations such as deploying applications across environments, troubleshooting platform-level issues, configuring environment settings, and understanding platform architecture. Candidates are also expected to know when to involve Appian Support and how to adjust admin console configurations to maintain stability and performance.

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Appian Lead Developer Sample Questions (Q27-Q32):NEW QUESTION # 27
An existing integration is implemented in Appian. Its role is to send data for the main case and its related objects in a complex JSON to a REST API, to insert new information into an existing application. This integration was working well for a while. However, the customer highlighted one specific scenario where the integration failed in Production, and the API responded with a 500 Internal Error code. The project is in Post- Production Maintenance, and the customer needs your assistance. Which three steps should you take to troubleshoot the issue?
Answer: A,C,E
Explanation:
Comprehensive and Detailed In-Depth Explanation:As an Appian Lead Developer in a Post-Production Maintenance phase, troubleshooting a failed integration (HTTP 500 Internal Server Error) requires a systematic approach to isolate the root cause-whether it's Appian-side, API-side, or environmental. A 500 error typically indicates an issue on the server (API) side, but the developer must confirm Appian's contribution and collaborate with the customer. The goal is to select three steps that efficiently diagnose the specific scenario while adhering to Appian's best practices. Let's evaluate each option:
* A. Send the same payload to the test API to ensure the issue is not related to the API environment:This is a critical step. Replicating the failure by sending the exact payload (from the failed Production call) to a test API environment helps determine if the issue is environment-specific (e.g., Production-only configuration) or inherent to the payload/API logic. Appian's Integration troubleshooting guidelines recommend testing in a non-Production environment first to isolate variables. If the test API succeeds, the Production environment or API state is implicated; if it fails, the payload or API logic is suspect.
This step leverages Appian's Integration object logging (e.g., request/response capture) and is a standard diagnostic practice.
* B. Send a test case to the Production API to ensure the service is still up and running:While verifying Production API availability is useful, sending an arbitrary test case risks further Production disruption during maintenance and may not replicate the specific scenario. A generic test might succeed (e.g., with simpler data), masking the issue tied to the complex JSON. Appian's Post-Production guidelines discourage unnecessary Production interactions unless replicating the exact failure is controlled and justified. This step is less precise than analyzing existing behavior (C) and is not among the top three priorities.
* C. Analyze the behavior of subsequent calls to the Production API to ensure there is no global issue, and ask the customer to analyze the API logs to understand the nature of the issue:This is essential.
Reviewing subsequent Production calls (via Appian's Integration logs or monitoring tools) checks if the
500 error is isolated or systemic (e.g., API outage). Since Appiancan't access API server logs, collaborating with the customer to review their logs is critical for a 500 error, which often stems from server-side exceptions (e.g., unhandled data). Appian Lead Developer training emphasizes partnership with API owners and using Appian's Process History or Application Monitoring to correlate failures- making this a key troubleshooting step.
* D. Obtain the JSON sent to the API and validate that there is no difference between the expected JSON format and the sent one:This is a foundational step. The complex JSON payload is central to the integration, and a 500 error could result from malformed data (e.g., missing fields, invalid types) that the API can't process. In Appian, you can retrieve the sent JSON from the Integration object's execution logs (if enabled) or Process Instance details. Comparing it against the API's documented schema (e.g., via Postman or API specs) ensures Appian's output aligns with expectations. Appian's documentation stresses validating payloads as a first-line check for integration failures, especially in specific scenarios.
* E. Ensure there were no network issues when the integration was sent:While network issues (e.g., timeouts, DNS failures) can cause integration errors, a 500 Internal Server Error indicates the request reached the API and triggered a server-side failure-not a network issue (which typically yields 503 or timeout errors). Appian's Connected System logs can confirm HTTP status codes, and network checks (e.g., via IT teams) are secondary unless connectivity is suspected. This step is less relevant to the 500 error and lower priority than A, C, and D.
Conclusion: The three best steps are A (test API with same payload), C (analyze subsequent calls and customer logs), and D (validate JSON payload). These steps systematically isolate the issue-testing Appian' s output (D), ruling out environment-specific problems (A), and leveraging customer insights into the API failure (C). This aligns with Appian's Post-Production Maintenance strategies: replicate safely, analyze logs, and validate data.
References:
* Appian Documentation: "Troubleshooting Integrations" (Integration Object Logging and Debugging).
* Appian Lead Developer Certification: Integration Module (Post-Production Troubleshooting).
* Appian Best Practices: "Handling REST API Errors in Appian" (500 Error Diagnostics).

NEW QUESTION # 28
You are required to configure a connection so that Jira can inform Appian when specific tickets change (using a webhook). Which three required steps will allow you to connect both systems?
Answer: A,D,E
Explanation:
Comprehensive and Detailed In-Depth Explanation:Configuring a webhook connection from Jira to Appian requires setting up a mechanism for Jira to push ticket change notifications to Appian in real-time.
This involves creating an endpoint in Appian to receive the webhook and configuring Jira to send the data.
Appian's Integration Best Practices and Web API documentation provide the framework for this process.
* Option A (Create a Web API object and set up the correct security):This is a required step. In Appian, a Web API object serves as the endpoint to receive incoming webhook requests from Jira. You must define the API structure (e.g., HTTP method, input parameters) and configure security (e.g., basic authentication, API key, or OAuth) to validate incoming requests. Appian recommends using a service account with appropriate permissions to ensure secure access, aligning with the need for a controlled webhook receiver.
* Option B (Configure the connection in Jira specifying the URL and credentials):This is essential.
In Jira, you need to set up a webhook by providing the Appian Web API's URL (e.g., https://<appian- site>/suite/webapi/<web-api-name>) and the credentials or authentication method (e.g., API key or basic auth) that match the security setup in Appian. This ensures Jira can successfully send ticket change events to Appian.
* Option C (Create a new API Key and associate a service account):This is necessary for secure authentication. Appian recommends using an API key tied to a service account for webhook integrations. The service account should have permissions to process the incoming data (e.g., write to a process or data store) but not excessive privileges. This step complements the Web API security setup and Jira configuration.
* Option D (Give the service account system administrator privileges):This is unnecessary and insecure. System administrator privileges grant broad access, which is overkill for a webhook integration. Appian's security best practices advocate for least-privilege principles, limiting the service account to the specific objects or actions needed (e.g., executing the Web API).
* Option E (Create an integration object from Appian to Jira to periodically check the ticket status):This is incorrect for a webhook scenario. Webhooks are push-based, where Jira notifies Appian of changes. Creating an integration object for periodic polling (pull-based) is a different approach and not required for the stated requirement of Jira informing Appian via webhook.
These three steps (A, B, C) establish a secure, functional webhook connection without introducing unnecessary complexity or security risks.
References:Appian Documentation - Web API Configuration, Appian Integration Best Practices - Webhooks, Appian Lead Developer Training - External System Integration.
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".

NEW QUESTION # 29
An Appian application contains an integration used to send a JSON, called at the end of a form submission, returning the created code of the user request as the response. To be able to efficiently follow their case, the user needs to be informed of that code at the end of the process. The JSON contains case fields (such as text, dates, and numeric fields) to a customer's API. What should be your two primary considerations when building this integration?
Answer: B,C
Explanation:
Comprehensive and Detailed In-Depth Explanation:
As an Appian Lead Developer, building an integration to send JSON to a customer's API and return a code to the user involves balancing usability, performance, and reliability. The integration is triggered at form submission, and the user must see the response (case code) efficiently. The JSON includes standard fields (text, dates, numbers), and the focus is on primary considerations for the integration itself. Let's evaluate each option based on Appian's official documentation and best practices:
A . A process must be built to retrieve the API response afterwards so that the user experience is not impacted:
This suggests making the integration asynchronous by calling it in a process model (e.g., via a Start Process smart service) and retrieving the response later, avoiding delays in the UI. While this improves user experience for slow APIs (e.g., by showing a "Processing" message), it contradicts the requirement that the user is "informed of that code at the end of the process." Asynchronous processing would delay the code display, requiring additional steps (e.g., a follow-up task), which isn't efficient for this use case. Appian's default integration pattern (synchronous call in an Integration object) is suitable unless latency is a known issue, making this a secondary-not primary-consideration.
B . The request must be a multi-part POST:
A multi-part POST (e.g., multipart/form-data) is used for sending mixed content, like files and text, in a single request. Here, the payload is a JSON containing case fields (text, dates, numbers)-no files are mentioned. Appian's HTTP Connected System and Integration objects default to application/json for JSON payloads via a standard POST, which aligns with REST API norms. Forcing a multi-part POST adds unnecessary complexity and is incompatible with most APIs expecting JSON. Appian documentation confirms this isn't required for JSON-only data, ruling it out as a primary consideration.
C . The size limit of the body needs to be carefully followed to avoid an error:
This is a primary consideration. Appian's Integration object has a payload size limit (approximately 10 MB, though exact limits depend on the environment and API), and exceeding it causes errors (e.g., 413 Payload Too Large). The JSON includes multiple case fields, and while "hundreds of thousands" isn't specified, large datasets could approach this limit. Additionally, the customer's API may impose its own size restrictions (common in REST APIs). Appian Lead Developer training emphasizes validating payload size during design-e.g., testing with maximum expected data-to prevent runtime failures. This ensures reliability and is critical for production success.
D . A dictionary that matches the expected request body must be manually constructed:
This is also a primary consideration. The integration sends a JSON payload to the customer's API, which expects a specific structure (e.g., { "field1": "text", "field2": "date" }). In Appian, the Integration object requires a dictionary (key-value pairs) to construct the JSON body, manually built to match the API's schema. Mismatches (e.g., wrong field names, types) cause errors (e.g., 400 Bad Request) or silent failures. Appian's documentation stresses defining the request body accurately-e.g., mapping form data to a CDT or dictionary-ensuring the API accepts the payload and returns the case code correctly. This is foundational to the integration's functionality.
Conclusion: The two primary considerations are C (size limit of the body) and D (constructing a matching dictionary). These ensure the integration works reliably (C) and meets the API's expectations (D), directly enabling the user to receive the case code at submission end. Size limits prevent technical failures, while the dictionary ensures data integrity-both are critical for a synchronous JSON POST in Appian. Option A could be relevant for performance but isn't primary given the requirement, and B is irrelevant to the scenario.
Reference:
Appian Documentation: "Integration Object" (Request Body Configuration and Size Limits).
Appian Lead Developer Certification: Integration Module (Building REST API Integrations).
Appian Best Practices: "Designing Reliable Integrations" (Payload Validation and Error Handling).

NEW QUESTION # 30
You need to export data using an out-of-the-box Appian smart service. Which two formats are available (or data generation?
Answer: B,D
Explanation:
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".

NEW QUESTION # 31
You have an active development team (Team A) building enhancements for an application (App X) and are currently using the TEST environment for User Acceptance Testing (UAT).
A separate operations team (Team B) discovers a critical error in the Production instance of App X that they must remediate. However, Team B does not have a hotfix stream for which to accomplish this. The available environments are DEV, TEST, and PROD.
Which risk mitigation effort should both teams employ to ensure Team A's capital project is only minorly interrupted, and Team B's critical fix can be completed and deployed quickly to end users?
Answer: C
Explanation:
Comprehensive and Detailed In-Depth Explanation:
As an Appian Lead Developer, managing concurrent development and operations (hotfix) activities across limited environments (DEV, TEST, PROD) requires minimizing disruption to Team A's enhancements while ensuring Team B's critical fix reaches PROD quickly. The scenario highlights no hotfix stream, active UAT in TEST, and a critical PROD issue, necessitating a strategic approach. Let's evaluate each option:
A . Team B must communicate to Team A which component will be addressed in the hotfix to avoid overlap of changes. If overlap exists, the component must be versioned to its PROD state before being remediated and deployed, and then versioned back to its latest development state. If overlap does not exist, the component may be remediated and deployed without any version changes:
This is the best approach. It ensures collaboration between teams to prevent conflicts, leveraging Appian's version control (e.g., object versioning in Appian Designer). Team B identifies the critical component, checks for overlap with Team A's work, and uses versioning to isolate changes. If no overlap exists, the hotfix deploys directly; if overlap occurs, versioning preserves Team A's work, allowing the hotfix to deploy and then reverting the component for Team A's continuation. This minimizes interruption to Team A's UAT, enables rapid PROD deployment, and aligns with Appian's change management best practices.
B . Team A must analyze their current codebase in DEV to merge the hotfix changes into their latest enhancements. Team B is then required to wait for the hotfix to follow regular deployment protocols from DEV to the PROD environment:
This delays Team B's critical fix, as regular deployment (DEV ¡ú TEST ¡ú PROD) could take weeks, violating the need for "quick deployment to end users." It also risks introducing Team A's untested enhancements into the hotfix, potentially destabilizing PROD. Appian's documentation discourages mixing development and hotfix workflows, favoring isolated changes for urgent fixes, making this inefficient and risky.
C . Team B must address changes in the TEST environment. These changes can then be tested and deployed directly to PROD. Once the deployment is complete, Team B can then communicate their changes to Team A to ensure they are incorporated as part of the next release:
Using TEST for hotfix development disrupts Team A's UAT, as TEST is already in use for their enhancements. Direct deployment from TEST to PROD skips DEV validation, increasing risk, and doesn't address overlap with Team A's work. Appian's deployment guidelines emphasize separate streams (e.g., hotfix streams) to avoid such conflicts, making this disruptive and unsafe.
D . Team B must address the changes directly in PROD. As there is no hotfix stream, and DEV and TEST are being utilized for active development, it is best to avoid a conflict of components. Once Team A has completed their enhancements work, Team B can update DEV and TEST accordingly:
Making changes directly in PROD is highly discouraged in Appian due to lack of testing, version control, and rollback capabilities, risking further instability. This violates Appian's Production governance and security policies, and delays Team B's updates until Team A finishes, contradicting the need for a "quick deployment." Appian's best practices mandate using lower environments for changes, ruling this out.
Conclusion: Team B communicating with Team A, versioning components if needed, and deploying the hotfix (A) is the risk mitigation effort. It ensures minimal interruption to Team A's work, rapid PROD deployment for Team B's fix, and leverages Appian's versioning for safe, controlled changes-aligning with Lead Developer standards for multi-team coordination.
Reference:
Appian Documentation: "Managing Production Hotfixes" (Versioning and Change Management).
Appian Lead Developer Certification: Application Management Module (Hotfix Strategies).
Appian Best Practices: "Concurrent Development and Operations" (Minimizing Risk in Limited Environments).

NEW QUESTION # 32
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