
Webinar Playback: Building Intelligent Apps and Smart AI Integration using MCP (Model Context Protocol)
In this video I’m joined by Mark Harrison from Microsoft. We go deep on how to build intelligent applications, including AI Agents vs Agentic AI,
1.Planning and Design
Understand Business Requirements: Clearly define the business process and outcomes expected from the Logic App.
Workflow Design: Sketch the workflow prior to implementation. Utilise flowcharts or diagrams for clarity.
Work within the Cloud Adoption Framework (CAF)[link] guidelines and conduct a well-architected review to ensure a quality result.
2. Development Best Practices
Modular Design: Break down complex workflows into smaller, manageable parts.
Reuse Components: Utilise connectors and templates where possible to avoid reinventing the wheel.
Patterns: Use established integration design patterns to solve your problems – it’s most likely something similar has been solved before.
Error Handling: Implement comprehensive error handling and logging. Use “Scope” for grouping actions and handling errors.
State Management: Be mindful of how state is managed, especially in long-running processes.
3. Security
Secure Data: Use secure inputs/outputs in Logic Apps, especially when handling sensitive data.
Access Control: Implement proper access control and permissions for resources.
Use Managed Identities: For secure access to other Azure services.
Network: Use private endpoints as appropriate to communicate with resources on your private virtual network.
Secure secrets and configuration: ensure you use tools such as Azure Key Vault to keep your passwords, URLs and configuration private.
4. Performance Optimisation
Design with scalability in mind from the outset. Consider the expected load and how the Logic App will manage it.
Efficient Triggers: Choose the right trigger type for your needs. Avoid overly frequent polling where possible.
Parallel Processing: Use parallel branches for actions that can run simultaneously.
Avoid Unnecessary Actions: Each action consumes resources. Be judicious in adding actions to your Logic App.
Consider using stateless Logic Apps if your workflow can be retried in the event of failure.
5. Monitoring and Maintenance
Stateful Logic Apps will, by default, maintain a full run history so you can troubleshoot them later.
Logging: Implement robust logging for troubleshooting and monitoring.
Alerts: Set up alerts for failures or performance issues.
Regular Updates: Keep the Logic App and its components up to date by regularly rebuilding and checking for deprecation warnings.
6. Testing
Unit Testing: Test individual components or actions on your local environment and build server.
Integration Testing: Ensure that the Logic App integrates well with other systems. Create test stubs for the systems you are integrating with to ensure the integration logic is correct.
Performance Testing: Test under load to ensure scalability and performance; this is easily facilitated by tools such as Azure Load Test .
7. Cost Management
Cost Analysis: Regularly review and optimise costs associated with running your Logic Apps. [link to other case study??]
Efficient Resource Utilisation: Optimise the use of connectors and actions to minimise costs.
Tear down unused environments: Development and test environments can be torn down when not in use and rebuilt on demand so you only pay for what you use.
8. Documentation and Knowledge Sharing
Document the Workflow: Keep detailed documentation of the Logic App’s design and functionality.
Share Best Practices: Encourage team members to share insights and improvements.
Knowledge base: keep a searchable knowledge base of patterns, best practices and design documentation across all your projects that developers can use.
9. Compliance and Standards
Adhere to Compliance: Ensure your Logic App meets industry and regulatory standards.
Coding Standards: Follow consistent coding and naming conventions.
10. DevOps and Development
Capture all required features and user stories in a prioritised backlog; use sprints or iterations to deliver units of value working from the most to the least important features.
Ensure Developers have a consistent, productive development environment with all necessary tools pre-installed. Make this available to every team member.
Ensure all aspects of your solution are created as code / scripts so that you have “hands-free” deployment into every environment. This is essential to maintain quality.
Create repeatable, scripted regression tests that are run against your solution every time it changes to ensure you don’t inadvertently introduce quality issues when you make changes.
Implementing these best practices will help ensure that your Azure Logic Apps are efficient, secure, and maintainable. Regularly revisiting and updating your approach based on new learnings and features of Azure Logic Apps is crucial for continuous improvement. The key to a successful Logic App lies not just in its initial development but also in its ongoing management and optimisation. Remember, effective Logic Apps are the result of thoughtful planning, diligent development, and continuous refinement.

In this video I’m joined by Mark Harrison from Microsoft. We go deep on how to build intelligent applications, including AI Agents vs Agentic AI,

If you’re running CI servers or end-to-end acceptance tests in your Azure projects, you’re not alone – and the good news is, testability is getting better. 💡Testing

You won’t want to miss this exciting webinar with hosts Andrew Rivers & Mark Harrison on Wednesday 28th May at 1PM. Andrew & Mark will