Understanding the Architecture and Components

Overview of Protegrity Synthetic Data architecture, processing flow, and deployment components on AWS EKS.

Protegrity Synthetic Data generates realistic, privacy-safe synthetic datasets using machine learning models. It learns patterns and distributions from real data, then produces new records with similar statistical properties.

Protegrity Synthetic Data uses Kubernetes for scalable Synthetic Data generation and supports deployment on AWS EKS.

Component Diagram

The following diagram shows the deployment architecture and communication between components.

graph TD
    User([User / Client Application]) -->|HTTPS :443| GW[PPC Gateway]
    User --> SDK[Synthetic Data Python SDK]
    SDK -->|HTTPS :443| GW

    GW -->|:8000  /pty/syntheticdata/v2| App[Synthetic Data
REST Server + ML Engine]

    App -->|:5432  jobstatedb + mlopsdb| DB[(PostgreSQL)]

    subgraph EKS [EKS Cluster · synthetic-data-ns]
        GW
        App
        DB
    end

    subgraph AWS
        S3[(S3 Bucket
Data Storage)]
        IAM[IAM Role
Pod Identity]
    end

    App -.->|assumes| IAM
    IAM -.->|grants access| S3
    App <-->|read / write| S3

Communication Ports

PortDirectionDescription
443User and SDK → PPC GatewayHTTPS entry point for user and SDK traffic
8000Gateway → Synthetic Data REST ServerSynthetic Data REST API (/pty/syntheticdata/v2)
5432Synthetic Data REST Server → PostgreSQLStores job state (jobstatedb) and MLOps model tracking (mlopsdb); internal only

Components

  • PPC Gateway: Exposes the external HTTPS endpoint and routes requests to the Synthetic Data REST API.

  • Synthetic Data REST Server: Exposes the /pty/syntheticdata/v2 API and runs ML models such as VineCopula, TabDiff, TabularGAN, and SMOTE in-process to produce synthetic datasets. It stores job metadata in PostgreSQL, reads input data from the S3 bucket and writes output data to it.

  • PostgreSQL: Hosts two logical databases. jobstatedb stores job metadata, including generation parameters, job status, and result references. mlopsdb stores MLOps model contracts, training runs, metrics, and artifact references managed by the MLOps library.

  • S3 Storage: Stores input datasets and generated synthetic datasets.

  • IAM Role with EKS Pod Identity: Grants the Synthetic Data REST Server secure access to the S3 bucket without static AWS credentials.

  • Python SDK: Provides programmatic access to the REST API. For more information about the Python SDK, refer to the Python SDK Installation section.


Last modified : July 29, 2026