Building secure, scalable APIs and apps doesn’t have to involve complex code. With the right software, you can deploy robust data services that power dashboards, internal tools, and customer-facing applications through configuration alone. In a recent webinar hosted by Safe Software and con terra, we explored how to use FME to scale real-time data services using templates, asynchronous execution, and advanced governance strategies.
See a deep dive on this topic and live demos in the webinar recording: Data Virtualization in Action: Scaling APIs and Apps with FME.
Key takeaways:
- Deliver scalable APIs without writing code using Data Virtualization FME.
- Use OGC API Templates to simplify and standardize geospatial API deployment.
- Security and governance are built-in, with token-based authentication, role-based access control, and usage monitoring.
- New features like complex schema support and callback URLs enhance flexibility, performance, and integration potential for enterprise use.
Building Scalable APIs via Data Virtualization
Data Virtualization in FME allows you to abstract and expose datasets through APIs, enabling real-time access to your organization’s data. Using standard HTTP endpoints, you can connect directly to the source and expose data and transformation logic. FME Flow makes it possible to deliver these services with no-code workflows, supporting real-time integration and on-demand data processing.
To learn more about Data Virtualization in FME, visit the tutorial Getting Started with Data Virtualization.
Simplifying the process with OGC API Templates
Reusable API templates based on OGC standards provide a structured, repeatable way to publish geospatial APIs. This helps simplify deployment, ensure consistency, and enable interoperability across systems.
con terra’s OGC API templates for FME are designed to expose spatial datasets through standardized endpoints. These templates can be customized for various data sources and allow for rapid deployment, standards compliance, and configurability.
The available templates include:
- OGC API Features Template – For accessing vector data. This is a ready-to-use FME template for creating an OGC API – Features compliant API using Data Virtualization. It enables users to fetch, filter, and transform geospatial feature data from any source via a well defined API via FME Flow.
- OGC API Processes Template – For executing processes and managing jobs. This is a ready-to-use FME template for creating an OGC API – Processes compliant API using Data Virtualization in FME.
Organizations can use these templates to support both internal analytics platforms and external public data portals, adapting them to meet different performance and security requirements.
Advanced FME Functionality for Scalable APIs
FME includes several features that support scalable, real-time operations for API-driven systems.
Asynchronous Execution & Callback URLs: For large or long-running jobs, asynchronous execution allows FME to queue and process requests in the background. Using the REST API, clients can submit a job and receive a unique job ID, monitor job progress through polling, and provide a callback URL to receive a notification when the job finishes. This pattern decouples the user interface from processing logic, improving responsiveness and enabling more complex workflows.
Secure and Governed Data Services: Security and governance are essential for deploying APIs in production environments. FME supports Token-Based Authentication to restrict access and Role-Based Access Control (RBAC) for managing permissions across endpoints. There are also monitoring and auditing tools to track usage and access patterns. These features help teams align with organizational security policies while maintaining ease of use for developers and analysts.
Complex Schema Support: New support for nested and complex data structures will allow APIs to return richer, more flexible responses. This includes multi-geometry features, arrays, and deeply nested properties.
Enhanced Performance for Workflow Execution: Asynchronous processing will become more scalable, with improved resource management and job orchestration. These features are critical for organizations running high-throughput services or integrating with automated systems.
Implementation Tips
For those looking to implement scalable APIs with FME, consider the following best practices:
- Start with Templates: Use existing templates to speed up deployment and ensure standardization.
- Plan for Scale: Design workflows to run asynchronously and use callback URLs where appropriate.
- Secure Early: Set up authentication and access controls from the beginning.
- Validate Output: Use schema validation tools to ensure your API responses meet expectations.
Try It
Using FME for API delivery is ideal for:
- Data professionals who want to expose services without writing code.
- Developers implementing geospatial APIs using OGC standards.
- IT and GIS teams looking to streamline data delivery and integration.
Whether you’re building internal tools or external platforms, FME enables you to move from concept to production quickly and securely.
