Data / CDC
CDCExternalIntegration Pattern

Int-CDC-External

Problem

A backend workload requires propagating incremental data changes to an external system or partner efficiently and with minimal impact on the source system's operational integrity.

Solution

Implement a Change Data Capture (CDC) mechanism to monitor a backend workload's data store for incremental changes. These changes are then asynchronously published as events or data streams, or periodically aggregated into files, for secure transmission to an external system. Outbound data transfer leverages robust, controlled egress points, such as an Egress Gateway or secure data transfer service, integrating with external APIs or secure file transfer protocols.

Cloud Paradigm

  • Event-Driven Architecture / Data Streaming
  • Asynchronous Integration Patterns
  • Secure Managed Data Transfer
  • Data Observability

Implementation Guidelines

Solution Flow

Data Change Capture and Staging Flow:

  1. Backend Workload Data Store: An internal backend workload generates or modifies data within its persistent data store (e.g., relational database, NoSQL data store).
  2. Change Data Capture (CDC) Component: A dedicated CDC component, deployed within the Private Subnet (Workloads), continuously monitors the data store (e.g., via transaction logs, triggers, or logical replication) for changes.
  3. Data Transformation & Event Generation: The CDC component captures changes, optionally transforms them (e.g., filtering, light schema mapping), and publishes them as structured events (e.g., JSON, Avro) to a durable message broker or an object storage bucket.
  4. Durable Event/Data Store: Changes are temporarily stored in a highly available, scalable message broker (e.g., managed message queue, event streaming platform) or object storage (e.g., for batch file staging).

External Data Delivery Flow:

  1. Data Processing & Aggregation (Optional): If publishing in batches, a dedicated processing workload retrieves events/files from the durable store, aggregates them, and prepares the final data payload for external delivery.
  2. Outbound Connection Initiation: The data processing workload (or the CDC component directly, for real-time streaming) initiates a secure connection to the external system.
  3. Egress Gateway / Secure Data Transfer Service: All outbound traffic is routed through a Managed NAT / Egress Gateway or a specialized Secure File Transfer Gateway in the Public Subnet (Perimeter). This gateway enforces egress policies (whitelisting FQDNs/IPs), performs NAT, and ensures secure transport.
  4. External Target System: The external partner system receives the data via its designated API endpoint (synchronous or asynchronous), message queue, or secure file transfer protocol (e.g., SFTP, HTTPS).

Additional Details

  • CDC Implementation: Choose a CDC mechanism appropriate for the source data store and desired latency. Options include log-based CDC, trigger-based CDC, or periodic polling with change detection.
  • Event/File Format: Define a consistent, versioned data format for published changes (e.g., JSON, Avro, Parquet, CSV).
  • Error Handling & Idempotency: Implement robust error handling, including dead-letter queues for events, retry mechanisms, and idempotency at the external consumer to handle duplicate deliveries gracefully. Track the last successful publication timestamp or sequence number.
  • Scalability & Resiliency: Design the CDC component and message broker/object storage for high availability and scalability to handle varying data volumes and ensure continuous operation.
  • Observability: Implement comprehensive logging, monitoring, and alerting across the entire data flow, from the CDC component to the external delivery endpoint. Track metrics such as data volume, latency, successful transfers, and errors.
  • Direct Database Access Prohibition: Under no circumstances should direct database connections from external parties be permitted. This pattern explicitly enforces an abstraction layer for secure data exchange.
  • Pattern Delegation: For complex data transformations or routing logic that extends beyond simple event publishing, consider delegating to a dedicated data integration platform or event processing workload, rather than embedding complex logic within the CDC component itself.

Security Controls

  • Perimeter Security: All outbound data flow must originate from a Private Subnet (Workloads) and pass through a dedicated Egress Gateway or Managed NAT within a Public Subnet (Perimeter). This ensures centralized control and logging.
  • Transport Security: Enforce strict Transport Layer Security (TLS 1.2 or higher) for all connections, from the CDC component to the message broker/object storage, and from the egress point to the external target system.
  • Authentication & Authorization:
    • For API-based data exchange, use OAuth 2.0 (Client Credentials Grant) or Mutual TLS (mTLS) for system-to-system authentication.
    • For secure file transfer, utilize SFTP with SSH key-based authentication or HTTPS with client certificates.
    • Store all credentials (API keys, certificates, SSH keys) securely in a secrets management service, not in cleartext.
  • Data Integrity & Immutability: Ensure data integrity throughout the capture and transmission process. When publishing to object storage, consider immutability and versioning features.
  • Outbound Controls: The Egress Gateway or secure data transfer service must be configured with strict egress policies, allowing connections only to explicitly whitelisted external IP addresses, fully qualified domain names (FQDNs), or predefined endpoints. Implement Data Loss Prevention (DLP) measures if sensitive data is involved.
  • Data Masking/Anonymization: If transmitting sensitive or personally identifiable information (PII), ensure appropriate data masking, anonymization, or tokenization is applied before data leaves the internal environment.