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πŸ“½οΈ Intelligent Media Processing Pipeline (IMPP) - DevOps/AI/FinOps

A fully automated, event-driven AWS pipeline for ingesting, analyzing, transforming, and archiving dash cam and creative media, with built-in cost control and security.


🎯 Project Objective

  • Ingest media from home lab/edge (dash cam, content creation) to AWS S3.
  • AI Analysis: Automatic object, scene, and content detection (Rekognition, Transcribe).
  • Transformation: Multi-format transcoding (MediaConvert) for web/mobile/YouTube.
  • Smart Archiving: S3 Intelligent Tiering, Glacier for cost savings.
  • Observability: Real-time monitoring, alerting, and FinOps reporting.

πŸ—οΈ Architecture

Dash Cam/Server --> S3 (Ingest Bucket)
    |
    v
EventBridge (S3:ObjectCreated)
    |
    v
Step Functions State Machine
  +--- Lambda: AI Analysis (Rekognition, Transcribe)
  +--- MediaConvert: Transcoding
  +--- Lambda: Archive Decision (S3 Lifecycle)
  +--- CloudFront: Delivery
  +--- SNS/Slack/Discord: Alerts
[All secrets in AWS Secrets Manager]

πŸš€ Quick Start

Prerequisites

  • AWS account (MFA, IAM best practices)
  • Pulumi/Terraform CLI
  • Python 3.11+ or Node.js (Lambda)
  • Local server for dash cam uploads

1. Clone & Install

git clone https://github.com/yourusername/media-processing-pipeline.git
cd media-processing-pipeline/infra
pip install -r requirements.txt

2. Deploy Infrastructure

  • Use Pulumi/Terraform to provision all AWS resources.
  • Place all sensitive config (bucket names, webhook URLs) in Secrets Manager.

3. Configure Edge Upload Script

  • Script watches dash cam directory, syncs new files to S3 with metadata.
  • Includes checksum, source, and timestamp tags.

πŸ”’ Security Best Practices

  • Secrets: All secrets in AWS Secrets Manager.
  • S3: All buckets private, server-side encryption enabled, Macie scans for PII.
  • IAM: Least-privilege roles for all functions/services.
  • Alerting: SNS/Slack/Discord for all critical pipeline events.
  • Audit: CloudWatch logs for all pipeline steps.

πŸ“Š Observability & Cost Control

  • CloudWatch Dashboards for processing stats and cost metrics.
  • Automated alerts for failures or unexpected cost increases.
  • S3 lifecycle policies for cost-effective storage.

πŸ›‚ Feature Roadmap

  • Multi-source ingestion (dash cam, content creator, phone)
  • SageMaker custom model support
  • Automated cost anomaly detection
  • Multi-account/org support
  • OpenSearch/Grafana dashboards

🀝 Contributing

  • Fork, branch, and PR (feat/refactor/fix/chore).
  • Security and cost reviews required before merge.
  • See CONTRIBUTING.md for team standards.

πŸ“„ License

MIT License. See LICENSE for details.


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