AI Test Harness

Architecture

Reference for control plane, agent runtime, knowledge layer, and analytics services.

System Architecture Overview

The platform runs as modular microservices with event-driven communication. Agent orchestration and execution engines scale independently based on load.

Each service emits traceable events, enabling deterministic replay and quality governance across environments.

Core Services

Control Plane

Manages tenancy, authentication, policy enforcement, and service orchestration. Exposes GraphQL and REST APIs for UI and SDK integration.

Agent Runtime

Sandboxed execution environment for AI agents with resource quotas, permission boundaries, and context isolation.

Knowledge Services

Vector database and graph store for documentation, API schemas, telemetry, and historical test data.

Execution Engine

Distributed test execution with browser pools, API clients, and data validation pipelines.

Analytics Services

Real-time and batch analytics for failure clustering, trend analysis, and release readiness scoring.

Communication Patterns

Services communicate through a combination of synchronous RPC and asynchronous event streams:

  • Synchronous: gRPC for low-latency service-to-service calls
  • Asynchronous: Apache Kafka for event streaming and workflow orchestration
  • Client APIs: GraphQL and REST for external integrations

Data Architecture

The platform uses polyglot persistence optimized for each domain:

bash
PostgreSQL    → Transactional data (users, policies, configs)
MongoDB       → Test execution logs and artifacts
Redis         → Session state and job queues
Elasticsearch → Full-text search and log aggregation
Vector DB     → Semantic embeddings for AI reasoning

Deployment Topology

The platform deploys to Kubernetes with Helm charts. Each service can scale horizontally:

bash
kubectl get pods -n ai-test-harness

NAME                              READY   STATUS
control-plane-6f8d9c7b5d-xyz      2/2     Running
agent-runtime-5c4b8d9f7a-abc      3/3     Running
execution-engine-7d6c5b8a4f-def   5/5     Running
analytics-worker-4a9b7c6d5e-ghi   2/2     Running

Security Architecture

  • mTLS for all inter-service communication
  • JWT-based authentication with short-lived tokens
  • Role-based access control (RBAC) enforced at API gateway
  • Secrets managed via Kubernetes secrets or external vaults
  • Network policies for service isolation