Content ID Platform

A simplified content identification platform inspired by high-volume automatic content recognition systems. The project demonstrates a .NET API, Go match worker, asynchronous queue processing, PostgreSQL, MongoDB, LocalStack-backed AWS resources, OpenTelemetry, OpenTofu-style infrastructure, and Python automation.

Architecture

flowchart LR
  Client --> API[ContentId.Api]
  API --> PG[(PostgreSQL)]
  API --> Mongo[(MongoDB)]
  API --> SQS[SQS Job Queue]
  SQS --> Worker[Go Match Worker]
  Worker --> Mongo
  Worker --> PG
  API --> OTel[OpenTelemetry Collector]
  Worker --> OTel
  SQS --> DLQ[SQS DLQ]

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Screenshots

Capability Report

API Surface

Match Result

Local Quickstart

docker compose up --build

In another terminal:

./scripts/healthcheck.py

Submit a known matching fingerprint:

curl -s -X POST http://localhost:18080/v1/submissions \
  -H "Content-Type: application/json" \
  -d '{
    "title": "Interview Demo Track",
    "sourcePlatform": "PartnerUpload",
    "contentType": "audio",
    "durationSeconds": 191,
    "fingerprintHash": "abc123"
  }'

Useful endpoints:

• POST /v1/submissions
• GET /v1/submissions/{id}
• GET /v1/submissions/{id}/matches
• GET /health
• GET /metrics

What This Demonstrates

• C#/.NET platform API for submission intake and result retrieval.
• Go worker for asynchronous content matching.
• SQS queue plus DLQ for retryable background processing.
• PostgreSQL for normalized job state and match summaries.
• MongoDB for flexible fingerprint and raw match documents.
• LocalStack for local AWS SQS, SNS, and S3 resources.
• OpenTelemetry traces from API and worker.
• OpenTofu/Terraform-style AWS infrastructure in infra/opentofu.
• Python automation in scripts/healthcheck.py.

JD Alignment

This repo maps directly to backend/platform responsibilities in the target role: scalable APIs, async processing, C#/.NET, Go, MongoDB, PostgreSQL, AWS messaging, Docker Compose, IaC, observability, Python scripting, production runbooks, and clear developer documentation.

See:

• Architecture
• Runbook
• JD Mapping
• Interview Talking Points