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| Section | Weight | Objectives |
|---|---|---|
| Scalability and Performance Design | 20% | - Design and build high-performance components - Plan and execute load testing and monitoring - Troubleshoot application-level performance bottlenecks |
| Extending Appian & Integrations | 15% | - Design advanced APIs and connected systems - Troubleshoot integration and API errors - Implement authentication and secure integrations |
| Application Design and Development | 25% | - Apply best practices for multi-application development - Evaluate how Appian meets user requirements - Design applications with reusability and consistency |
| Data Management | 25% | - Leverage Data Fabric, data types, and migration strategies - Troubleshoot complex data and database performance issues - Design secure and efficient data models |
| Platform & Solution Architecture | 15% | - Manage deployments and environment configurations - Make architecture decisions for maintainability and scalability - Understand enterprise platform architecture |
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質問 # 20
You are on a call with a new client, and their program lead is concerned about how their legacy systems will integrate with Appian. The lead wants to know what authentication methods are supported by Appian. Which three authentication methods are supported?
正解：A、B、E
解説：
Comprehensive and Detailed In-Depth Explanation:
As an Appian Lead Developer, addressing a client's concerns about integrating legacy systems with Appian requires accurately identifying supported authentication methods for system-to-system communication or user access. The question focuses on Appian's integration capabilities, likely for both user authentication (e.g., SSO) and API authentication, as legacy system integration often involves both. Appian's documentation outlines supported methods in its Connected Systems and security configurations. Let's evaluate each option:
A . API Keys:
API Key authentication involves a static key sent in requests (e.g., via headers). Appian supports this for outbound integrations in Connected Systems (e.g., HTTP Authentication with an API key), allowing legacy systems to authenticate Appian calls. However, it's not a user authentication method for Appian's platform login-it's for system-to-system integration. While supported, it's less common for legacy system SSO or enterprise use cases compared to other options, making it a lower-priority choice here.
B . Biometrics:
Biometrics (e.g., fingerprint, facial recognition) isn't natively supported by Appian for platform authentication or integration. Appian relies on standard enterprise methods (e.g., username/password, SSO), and biometric authentication would require external identity providers or custom clients, not Appian itself. Documentation confirms no direct biometric support, ruling this out as an Appian-supported method.
C . SAML:
Security Assertion Markup Language (SAML) is fully supported by Appian for user authentication via Single Sign-On (SSO). Appian integrates with SAML 2.0 identity providers (e.g., Okta, PingFederate), allowing users to log in using credentials from legacy systems that support SAML-based SSO. This is a key enterprise method, widely used for integrating with existing identity management systems, and explicitly listed in Appian's security configuration options-making it a top choice.
D . CAC:
Common Access Card (CAC) authentication, often used in government contexts with smart cards, isn't natively supported by Appian as a standalone method. While Appian can integrate with CAC via SAML or PKI (Public Key Infrastructure) through an identity provider, it's not a direct Appian authentication option. Documentation mentions smart card support indirectly via SSO configurations, but CAC itself isn't explicitly listed, making it less definitive than other methods.
E . OAuth:
OAuth (specifically OAuth 2.0) is supported by Appian for both outbound integrations (e.g., Authorization Code Grant, Client Credentials) and inbound API authentication (e.g., securing Appian Web APIs). For legacy system integration, Appian can use OAuth to authenticate with APIs (e.g., Google, Salesforce) or allow legacy systems to call Appian services securely. Appian's Connected System framework includes OAuth configuration, making it a versatile, standards-based method highly relevant to the client's needs.
F . Active Directory:
Active Directory (AD) integration via LDAP (Lightweight Directory Access Protocol) is supported for user authentication in Appian. It allows synchronization of users and groups from AD, enabling SSO or direct login with AD credentials. For legacy systems using AD as an identity store, this is a seamless integration method. Appian's documentation confirms LDAP/AD as a core authentication option, widely adopted in enterprise environments-making it a strong fit.
Conclusion: The three supported authentication methods are C (SAML), E (OAuth), and F (Active Directory). These align with Appian's enterprise-grade capabilities for legacy system integration: SAML for SSO, OAuth for API security, and AD for user management. API Keys (A) are supported but less prominent for user authentication, CAC (D) is indirect, and Biometrics (B) isn't supported natively. This selection reassures the client of Appian's flexibility with common legacy authentication standards.
Appian Documentation: "Authentication for Connected Systems" (OAuth, API Keys).
Appian Documentation: "Configuring Authentication" (SAML, LDAP/Active Directory).
Appian Lead Developer Certification: Integration Module (Authentication Methods).
質問 # 21
You are the lead developer for an Appian project, in a backlog refinement meeting. You are presented with the following user story:
"As a restaurant customer, I need to be able to place my food order online to avoid waiting in line for takeout." Which two functional acceptance criteria would you consider 'good'?
正解：A、B
解説：
Comprehensive and Detailed In-Depth Explanation:
As an Appian Lead Developer, defining "good" functional acceptance criteria for a user story requires ensuring they are specific, testable, and directly tied to the user's need (placing an online food order to avoid waiting in line). Good criteria focus on functionality, usability, and reliability, aligning with Appian's Agile and design best practices. Let's evaluate each option:
A . The user will click Save, and the order information will be saved in the ORDER table and have audit history:
This is a "good" criterion. It directly validates the core functionality of the user story-placing an order online. Saving order data in the ORDER table (likely via a process model or Data Store Entity) ensures persistence, and audit history (e.g., using Appian's audit logs or database triggers) tracks changes, supporting traceability and compliance. This is specific, testable (e.g., verify data in the table and logs), and essential for the user's goal, aligning with Appian's data management and user experience guidelines.
B . The user will receive an email notification when their order is completed:
While useful, this is a "nice-to-have" enhancement, not a core requirement of the user story. The story focuses on placing an order online to avoid waiting, not on completion notifications. Email notifications add value but aren't essential for validating the primary functionality. Appian's user story best practices prioritize criteria tied to the main user need, making this secondary and not "good" in this context.
C . The system must handle up to 500 unique orders per day:
This is a non-functional requirement (performance/scalability), not a functional acceptance criterion. It describes system capacity, not specific user behavior or functionality. While important for design, it's not directly testable for the user story's outcome (placing an order) and isn't tied to the user's experience. Appian's Agile methodologies separate functional and non-functional requirements, making this less relevant as a "good" criterion here.
D . The user cannot submit the form without filling out all required fields:
This is a "good" criterion. It ensures data integrity and usability by preventing incomplete orders, directly supporting the user's ability to place a valid online order. In Appian, this can be implemented using form validation (e.g., required attributes in SAIL interfaces or process model validations), making it specific, testable (e.g., verify form submission fails with missing fields), and critical for a reliable user experience. This aligns with Appian's UI design and user story validation standards.
Conclusion: The two "good" functional acceptance criteria are A (order saved with audit history) and D (required fields enforced). These directly validate the user story's functionality (placing a valid order online), are testable, and ensure a reliable, user-friendly experience-aligning with Appian's Agile and design best practices for user stories.
Appian Documentation: "Writing Effective User Stories and Acceptance Criteria" (Functional Requirements).
Appian Lead Developer Certification: Agile Development Module (Acceptance Criteria Best Practices).
Appian Best Practices: "Designing User Interfaces in Appian" (Form Validation and Data Persistence).
質問 # 22
Your Appian project just went live with the following environment setup: DEV > TEST (SIT/UAT) > PROD. Your client is considering adding a support team to manage production defects and minor enhancements, while the original development team focuses on Phase 2. Your client is asking you for a new environment strategy that will have the least impact on Phase 2 development work. Which option involves the lowest additional server cost and the least code retrofit effort?
正解：D
解説：
Comprehensive and Detailed In-Depth Explanation:
The goal is to design an environment strategy that minimizes additional server costs and code retrofit effort while allowing the support team to manage production defects and minor enhancements without disrupting the Phase 2 development team. The current setup (DEV > TEST (SIT/UAT) > PROD) uses a single development and testing pipeline, and the client wants to segregate support activities from Phase 2 development. Appian's Environment Management Best Practices emphasize scalability, cost efficiency, and minimal refactoring when adjusting environments.
Option C (Phase 2 development work stream: DEV > TEST (SIT/UAT) > PROD; Production support work stream: DEV > TEST2 (SIT/UAT) > PROD):
This option is the most cost-effective and requires the least code retrofit effort. It leverages the existing DEV environment for both teams but introduces a separate TEST2 environment for the support team's SIT/UAT activities. Since DEV is already shared, no new development server is needed, minimizing server costs. The existing code in DEV and TEST can be reused for TEST2 by exporting and importing packages, with minimal adjustments (e.g., updating environment-specific configurations). The Phase 2 team continues using the original TEST environment, avoiding disruption. Appian supports multiple test environments branching from a single DEV, and the PROD environment remains shared, aligning with the client's goal of low impact on Phase 2. The support team can handle defects and enhancements in TEST2 without interfering with development workflows.
Option A (Phase 2 development work stream: DEV > TEST (SIT) > STAGE (UAT) > PROD; Production support work stream: DEV > TEST2 (SIT/UAT) > PROD):
This introduces a STAGE environment for UAT in the Phase 2 stream, adding complexity and potentially requiring code updates to accommodate the new environment (e.g., adjusting deployment scripts). It also requires a new TEST2 server, increasing costs compared to Option C, where TEST2 reuses existing infrastructure.
Option B (Phase 2 development work stream: DEV > TEST (SIT) > STAGE (UAT) > PROD; Production support work stream: DEV2 > STAGE (SIT/UAT) > PROD):
This option adds both a DEV2 server for the support team and a STAGE environment, significantly increasing server costs. It also requires refactoring code to support two development environments (DEV and DEV2), including duplicating or synchronizing objects, which is more effort than reusing a single DEV.
Option D (Phase 2 development work stream: DEV > TEST (SIT/UAT) > PROD; Production support work stream: DEV2 > TEST (SIT/UAT) > PROD):
This introduces a DEV2 server for the support team, adding server costs. Sharing the TEST environment between teams could lead to conflicts (e.g., overwriting test data), potentially disrupting Phase 2 development. Code retrofit effort is higher due to managing two DEV environments and ensuring TEST compatibility.
Cost and Retrofit Analysis:
Server Cost: Option C avoids new DEV or STAGE servers, using only an additional TEST2, which can often be provisioned on existing hardware or cloud resources with minimal cost. Options A, B, and D require additional servers (TEST2, DEV2, or STAGE), increasing expenses.
Code Retrofit: Option C minimizes changes by reusing DEV and PROD, with TEST2 as a simple extension. Options A and B require updates for STAGE, and B and D involve managing multiple DEV environments, necessitating more significant refactoring.
Appian's recommendation for environment strategies in such scenarios is to maximize reuse of existing infrastructure and avoid unnecessary environment proliferation, making Option C the optimal choice.
質問 # 23
You are just starting with a new team that has been working together on an application for months. They ask you to review some of their views that have been degrading in performance. The views are highly complex with hundreds of lines of SQL. What is the first step in troubleshooting the degradation?
正解：D
解説：
Comprehensive and Detailed In-Depth Explanation:
Troubleshooting performance degradation in complex SQL views within an Appian application requires a systematic approach. The views, described as having hundreds of lines of SQL, suggest potential issues with query execution, indexing, or join efficiency. As a new team member, the first step should focus on quickly identifying the root cause without overhauling the system prematurely. Appian's Performance Troubleshooting Guide and database optimization best practices provide the framework for this process.
Option B (Run an explain statement on the views, identify critical areas of improvement that can be remediated without business knowledge):
This is the recommended first step. Running an EXPLAIN statement (or equivalent, such as EXPLAIN PLAN in some databases) analyzes the query execution plan, revealing details like full table scans, missing indices, or inefficient joins. This technical analysis can identify immediate optimization opportunities (e.g., adding indices or rewriting subqueries) without requiring business input, allowing you to address low-hanging fruit quickly. Appian encourages using database tools to diagnose performance issues before involving stakeholders, making this a practical starting point as you familiarize yourself with the application.
Option A (Go through the entire database structure to obtain an overview, ensure you understand the business needs, and then normalize the tables to optimize performance):
This is too broad and time-consuming as a first step. Understanding business needs and normalizing tables are valuable but require collaboration with the team and stakeholders, delaying action. It's better suited for a later phase after initial technical analysis.
Option C (Go through all of the tables one by one to identify which of the grouped by, ordered by, or joined keys are currently indexed):
Manually checking indices is useful but inefficient without first knowing which queries are problematic. The EXPLAIN statement provides targeted insights into index usage, making it a more direct initial step than a manual table-by-table review.
Option D (Browse through the tables, note any tables that contain a large volume of null values, and work with your team to plan for table restructure):
Identifying null values and planning restructures is a long-term optimization strategy, not a first step. It requires team input and may not address the immediate performance degradation, which is better tackled with query-level diagnostics.
Starting with an EXPLAIN statement allows you to gather data-driven insights, align with Appian's performance troubleshooting methodology, and proceed with informed optimizations.
質問 # 24
You have created a Web API in Appian with the following URL to call it: https://exampleappiancloud.com/suite/webapi/user_management/users?username=john.smith. Which is the correct syntax for referring to the username parameter?
正解：B
解説：
Comprehensive and Detailed In-Depth Explanation:
In Appian, when creating a Web API, parameters passed in the URL (e.g., query parameters) are accessed within the Web API expression using the httpRequest object. The URL https://exampleappiancloud.com/suite/webapi/user_management/users?username=john.smith includes a query parameter username with the value john.smith. Appian's Web API documentation specifies how to handle such parameters in the expression rule associated with the Web API.
Option D (httpRequest.queryParameters.username):
This is the correct syntax. The httpRequest.queryParameters object contains all query parameters from the URL. Since username is a single query parameter, you access it directly as httpRequest.queryParameters.username. This returns the value john.smith as a text string, which can then be used in the Web API logic (e.g., to query a user record). Appian's expression language treats query parameters as key-value pairs under queryParameters, making this the standard approach.
Option A (httpRequest.queryParameters.users.username):
This is incorrect. The users part suggests a nested structure (e.g., users as a parameter containing a username subfield), which does not match the URL. The URL only defines username as a top-level query parameter, not a nested object.
Option B (httpRequest.users.username):
This is invalid. The httpRequest object does not have a direct users property. Query parameters are accessed via queryParameters, and there's no indication of a users object in the URL or Appian's Web API model.
Option C (httpRequest.formData.username):
This is incorrect. The httpRequest.formData object is used for parameters passed in the body of a POST or PUT request (e.g., form submissions), not for query parameters in a GET request URL. Since the username is part of the query string (?username=john.smith), formData does not apply.
The correct syntax leverages Appian's standard handling of query parameters, ensuring the Web API can process the username value effectively.
質問 # 25
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