Identity Orchestration: Building with Open Source

In today's digital landscape, managing identity verification is a complex challenge. Businesses require a flexible, scalable, and secure system to handle diverse verification needs, from basic identity checks to full KYC/AML compliance. Rather than relying on monolithic vendor solutions, many organizations are turning to identity orchestration – the process of coordinating multiple identity services into a unified workflow. This post explores building an identity orchestration engine using powerful open source tools.

Key Takeaway 1: Identity orchestration provides flexibility, allowing you to swap out individual verification components without disrupting the entire system.

Key Takeaway 2: Open-source tools offer cost savings and greater control over your identity infrastructure, but require in-house expertise.

Key Takeaway 3: Microservices architecture is crucial for scalability and resilience in identity orchestration.

Key Takeaway 4: Data streaming with tools like Kafka enables real-time processing and event-driven workflows.

Why Build an Identity Orchestration Engine?

Traditional identity verification solutions often present limitations: rigid workflows, vendor lock-in, and lack of customization. An identity orchestration engine addresses these issues by decoupling identity services and connecting them through a central control plane. This approach offers several benefits:

• Flexibility: Easily integrate new verification methods (e.g., biometric checks, document verification) as needed.
• Scalability: Handle increasing verification volumes without performance bottlenecks.
• Resilience: Isolate failures and maintain system uptime even if individual services experience issues.
• Cost Optimization: Choose best-of-breed services and avoid vendor lock-in.
• Customization: Tailor verification workflows to specific business requirements and risk profiles.

The Open-Source Stack: Core Components

Building an identity orchestration engine requires several key components. Here’s a common open-source stack:

• Apache NiFi: A powerful dataflow system for automating the movement and transformation of data. NiFi acts as the central orchestration engine, defining and executing verification workflows.
• Apache Kafka: A distributed streaming platform for building real-time data pipelines and streaming analytics. Kafka facilitates asynchronous communication between microservices.
• Kubernetes: A container orchestration platform for automating deployment, scaling, and management of containerized applications. Kubernetes provides the infrastructure for running the microservices.
• Microservices: Individual, independently deployable services responsible for specific verification tasks (e.g., document verification, AML screening).
• API Gateway: A central entry point for external applications to access the identity orchestration engine.

Architecture: A Microservices Approach

The foundation of a scalable identity orchestration engine is a microservices architecture. Each verification task is encapsulated within its own service, communicating with other services via APIs or message queues (Kafka). Here's a simplified example:

1. An external application initiates a verification request through the API Gateway.

2. The API Gateway routes the request to Apache NiFi.

3. NiFi orchestrates the workflow, invoking the appropriate microservices (e.g., Document Verification Service, AML Screening Service).

4. Microservices communicate with each other via Kafka (e.g., Document Verification Service publishes an event, AML Screening Service subscribes to the event).

5. NiFi aggregates the results from each microservice and returns a final verification decision to the API Gateway.

Implementing Workflows with Apache NiFi

Apache NiFi excels at defining and executing complex dataflows. You can visually design workflows using NiFi's drag-and-drop interface. Key NiFi processors for identity orchestration include:

• InvokeHTTP: Call external APIs (e.g., document verification services).
• ExecuteStreamCommand: Execute shell commands or scripts.
• PublishKafka: Publish messages to Kafka topics.
• ConsumeKafka: Subscribe to Kafka topics.
• RouteOnAttribute: Route data based on attribute values (e.g., country code, document type).
• MergeContent: Combine data from multiple sources.

For example, a NiFi flow might:

1. Receive a verification request.
2. Extract data from the request.
3. Invoke a Document Verification Service via InvokeHTTP.
4. If the document is valid, publish a “DocumentVerified” event to Kafka.
5. Subscribe to the “DocumentVerified” event and invoke an AML Screening Service.
6. Aggregate the results from both services and return a final verdict.

Data Streaming with Kafka

Kafka acts as the central nervous system of the identity orchestration engine, enabling asynchronous communication and event-driven workflows. Each verification step can publish events to Kafka, allowing other services to react in real-time. For example:

• Document Verification Service publishes “DocumentVerificationCompleted” event.
• AML Screening Service subscribes to this event and initiates AML checks.
• Fraud Detection Service subscribes to both events and analyzes data for suspicious patterns.

How Didit Helps

Didit provides a robust set of APIs and SDKs that seamlessly integrate with your open-source identity orchestration engine. Our core identity primitives (ID Verification, Liveness Detection, AML Screening) can be invoked via NiFi’s InvokeHTTP processor or directly through your microservices. Didit’s developer-first approach, transparent pricing, and high performance make it an ideal building block for your identity infrastructure. With Didit, you can focus on orchestrating the workflow while we handle the complexities of identity verification. We also provide a free tier to get you started!

Ready to Get Started?

Building an identity orchestration engine with open-source tools can be a complex undertaking, but the benefits – flexibility, scalability, and cost savings – are significant. Explore the tools mentioned in this post, and consider leveraging Didit’s APIs to accelerate your development.

Resources:

• Didit API Documentation
• Apache NiFi
• Apache Kafka
• Kubernetes