Advanced Power Automate Cloud

Section 1: Enterprise Flow Architecture

• Where team-level flows tend to break when they scale across the organisation
• Separate Dev, Test and Production environments, and an overview of Managed Environments
• Solution-aware flows: building flows inside a solution from the start
• Lab: create a solution and move an existing flow into it

Section 2: Lab: Environment Variables and Connection References

• Environment variable types: Text, Number, JSON, Data source and Secret
• Move environment-specific values such as SharePoint sites and approver emails out of the flow
• Connection references, and switching connections without editing the flow
• Lab: refactor a flow until not a single value is hard-coded

Section 3: Lab: Child Flows and Modular Design

• When to split steps out into a child flow
• The Manually trigger a flow trigger and the Respond to a Power App or flow action
• Design child flow inputs and outputs so they can be reused in many places
• Lab: turn logging and notifications into a shared child flow

Section 4: Lab: Dataverse for Workflows

• When Dataverse beats a SharePoint list for complex data and permissions
• The When a row is added, modified or deleted trigger with Filter rows and Select columns
• List rows with OData filters, expand queries and FetchXML
• Lab: a flow that tracks request status on a Dataverse table

Section 5: Production-Grade Error Handling

• The Try, Catch, Finally pattern with scopes and Configure run after
• Read scope results with result() to find the failed action and build a readable error message
• Exponential retry policies, timeouts and Terminate
• Lab: a central error handler that logs to Dataverse and alerts in Teams

Section 6: Lab: Advanced Approvals

• Multi-stage approvals by amount, with the approver chain read from a table
• Custom responses, delegation and reassigning approvers
• Timeouts, reminders and escalation when nobody responds
• Lab: a multi-stage approval workflow that escalates automatically

Section 7: Lab: HTTP, REST APIs and Webhooks

• The HTTP action: methods, headers and common authentication types
• Parse JSON and generating a schema from sample data
• The When an HTTP request is received trigger for webhooks from other systems
• Lab: pull data from an external REST API and save it to Dataverse

Section 8: Lab: Custom Connectors

• Create a custom connector from an OpenAPI file or define the actions yourself
• API key and OAuth 2.0 authentication
• Test, share and include a custom connector in a solution
• Lab: a custom connector that calls a sample API, used inside a flow

Section 9: Large Data, Pagination and Concurrency

• Pagination and thresholds for List rows and Get items
• Concurrency control for Apply to each and for triggers
• Request limits, throttling and designing within the limits
• Lab: process thousands of records faster and measure before and after

Section 10: Monitoring and Maintaining Flows

• Read run history and the flow checker to catch problems before users do
• Power Automate monitoring and analytics pages
• Alerts when a flow is turned off or a connection expires
• Lab: a run summary dashboard built from the Dataverse log

Section 11: Lab: ALM with Pipelines and Governance

• Managed solutions and Pipelines in Power Platform from Dev to Test and Production
• Set environment variable values and connection references during deployment
• Data policies, standard versus premium connectors and an overview of the CoE Starter Kit
• Lab: deploy a solution through a pipeline and verify it in the target

Section 12: Workshop: Department-Level Capstone Solution

• Pick a case from your own work, such as purchasing, HR or customer requests
• Design a solution with Dataverse, child flows, approvals and a central error handler
• Connect an external system with HTTP or a custom connector
• Deploy across environments, then present the work with a pre-production checklist