PL-600 cheat sheet

Categorize every requirement in a fit-gap analysis as standard configuration, custom extension, or gap; configuration is preferred over custom code.

Functional requirements define what the solution must do; nonfunctional requirements define quality attributes such as performance, availability, scalability, and compliance.

The solution blueprint documents apps, automation, data model, integrations, security, ALM, environments, and licensing before build starts.

Success criteria must be measurable and agreed with stakeholders during envisioning; they become the baseline for UAT and go-live.

Power Platform Well-Architected pillars are Reliability, Security, Operational Excellence, Performance Efficiency, and Experience Optimization.

A requirement traceability matrix maps each requirement to a solution component, test case, and owner to prevent scope gaps.

Data residency and regulatory compliance requirements determine tenant region and whether certain connectors can be used.

An MVP scope delivers the highest-value requirements first and defers lower-priority items to later iterations.

RACI assigns Responsible, Accountable, Consulted, and Informed roles for each workstream and decision.

Choose model-driven apps for Dataverse-centric complex processes, canvas apps for tailored task experiences, and Power Pages for external audiences.

Business units define data ownership boundaries; security roles grant privileges; teams share access across business units; column security protects individual fields.

Use managed solutions in test and production and unmanaged solutions only in development; maintain a single publisher per solution.

Select native connectors for standard integrations, Azure Functions or Logic Apps for complex orchestration, and Service Bus for asynchronous decoupling.

Power Apps delegation pushes filtering to the data source; non-delegable functions on large tables return incomplete results.

Prefer standard Dataverse tables over custom tables when they fit, and model choices, lookups, and relationships before adding columns.

Dataverse capacity includes database, file, and log storage plus API request and Power Automate request entitlements.

Environment strategy separates development, test/UAT, and production; isolation level is driven by ALM, security, and scale needs.

Use connection references and environment variables in solutions so the same artifact deploys across environments without edits.

Connection references bind flows and apps to environment-specific connections, and environment variables supply environment-specific configuration values.

Power Platform pipelines or Azure DevOps with Power Platform Build Tools automate solution export, import, and deployment across environments.

DLP policies classify connectors as Business, Non-business, or Blocked; connectors in different groups cannot be used in the same app or flow.

Managed environments enable sharing limits, solution checker enforcement, deployment pipelines, and weekly admin digests.

Solution checker performs static analysis on solution components and flags issues by severity before deployment.

Use a deployment settings file to supply connection references and environment variable values during automated import.

Dataverse auditing records create, update, and delete operations on tables and columns enabled for auditing.

Application Insights and Power Platform Admin Center analytics provide telemetry for app usage, errors, and flow runs.

Point-in-time restore and environment backups protect against data loss; test restores before relying on them.