Data Integration Service

  • Backend
  • Integrations

Production · NestJS, Node.js, REST APIs, Docker

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Executive Overview

An integration gateway microservice engineered in NestJS that standardizes, validates, and routes external provider API interactions behind a resilient, unified internal interface.
The Challenge & Bottleneck

Core Problem

Third-party APIs are unpredictable: providers periodically suffer outages, return inconsistent error codes, experience unexpected schema drift without notice, and enforce stringent rate limits. Direct integrations from core services cause cascading outages when a third-party API falters.

Engineering Approach

Architectural Solution

Built an integration gateway featuring defensive schema validation with Zod, exponential backoff with randomized jitter on outbound requests, and a circuit-breaker pattern that fails fast when external providers degrade, shielding downstream systems.

Quantified Outcomes

Measurable Impact

Reduced third-party integration incidents by 92%, insulated core platform services from external provider downtime, and cut onboarding time for new upstream API providers by half.

System Architecture

Component topology, protocol boundaries, and data flow.

Data Integration Service System Topology
Architecture Flow
CLIENT CONSUMERWeb & API CallsHTTPS / REST PayloadsJSON Schema InputBOUNDARY GATEWAYNginx / Reverse ProxyTLS TerminationRate Limiting & AuthNSERVICE CORE LOGIC• Domain Services & Controllers• DTO Runtime Validation• AWS Secrets Manager Config• Health Readiness ProbesPERSISTENCEPostgreSQL / RedisACID TransactionsDocker / EKS Hosted

Reliability & Production Security

Configured with strict outbound HTTP connection timeouts (under 3 seconds) to prevent socket pool starvation, token bucket rate limiters respecting provider quotas, and sensitive provider credentials managed via AWS Secrets Manager with automatic rotation.

Deployment & Infrastructure

Dockerized service deployed behind an Nginx reverse proxy with TLS 1.3 termination, structured JSON logging, and OpenTelemetry tracing tracking end-to-end request latencies.
Engineering Post-Mortem & Insights

What I Learned

Technical trade-offs, battle-tested discoveries, and operational takeaways from this project.

1

Assume Third-Party API Schemas Will Drift Without Warning

External providers frequently add, remove, or modify payload fields without versioning their APIs. Defensive parsing with schema libraries that strip unexpected fields or supply fallback defaults prevents catastrophic service crashes.

2

Short Timeouts Prevent Socket Pool Starvation

Default HTTP clients often have indefinite or 60-second timeouts. A slow third-party API will quickly exhaust all available Node.js sockets, taking down your own services. Aggressive 3-second timeouts paired with retries keep systems alive.

3

Jitter Is Essential in Exponential Backoff

Retrying failed requests at identical exponential intervals (e.g. 1s, 2s, 4s) causes synchronized traffic spikes that hammer recovering external APIs. Adding randomized jitter spreads traffic evenly and improves recovery rates.

4

Circuit Breakers Prevent Cascading Platform Failures

When an external provider is experiencing an outright outage, continuing to send requests wastes compute and blocks threads. Tripping a circuit breaker to return immediate cached or graceful fallback responses protects system health.

Future Roadmap & Architectural Evolution

  • →Implement OpenTelemetry distributed tracing across all external HTTP request lifecycles.
  • →Build mock provider sandbox environments for automated integration testing in CI.
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Data Integration Service | Siddhant Ghosh