Azure API and system integration
Replace fragile integrations with supportable Azure services.
Connect established applications, partners and data flows using clear contracts, dependable failure handling and operational visibility.
The hidden system
Integrations often carry more business risk than the applications
APIs, scheduled jobs, file transfers and queues form the operational paths between systems. When ownership, contracts or failure handling are weak, small changes can cause missing data, duplicate actions and failures that nobody can explain.
The aim is not simply to connect two endpoints. It is to create a flow the organisation can operate, observe and safely change.
Technical capability
Microsoft integration engineering grounded in operations
- C# and ASP.NET Core APIs
- Azure Functions and App Services
- Azure Service Bus and event-driven workflows
- API Management and versioned contracts
- SQL Server, Azure SQL and structured data flows
- Authentication, authorisation and secret management
- Idempotency, retries and dead-letter handling
- Application Insights and actionable monitoring
- OpenAPI documentation and automated testing
- CI/CD, deployment and support documentation
Engagement route
Trace. Design. Deliver. Operate.
- 01
Trace
Map the real data flow, business rules, ownership and failure modes.
- 02
Design
Define contracts, security, resilience, observability and migration boundaries.
- 03
Deliver
Build and migrate in testable stages while protecting existing operations.
- 04
Operate
Leave dashboards, alerts, runbooks and knowledge with the responsible team.
Possible outcomes
An integration estate that can be understood and supported
- Integration and dependency map
- Prioritised remediation plan
- API and event architecture
- Working Azure integration services
- Secure migration from legacy interfaces
- Monitoring, alerts and operational runbooks
- Documentation and knowledge transfer
Diagnostic guidance
Seven signs an integration is becoming a business risk
Recurring manual work and unexplained data differences are often symptoms of a deeper ownership and resilience problem.
Make the data flow dependable