How to Deploy a Scalable Meltano + Airflow Stack on AWS ECS
We’ve built and deployed a flexible data pipeline architecture using Meltano and Airflow on AWS ECS—successfully run across both EC2 and Fargate. This setup is production-ready, cost-efficient, and modular.
Why Use Meltano + Airflow?
Meltano simplifies ELT with 300+ connectors and dbt integration. Airflow offers robust orchestration with DAGs, retries, and monitoring. Together, they form a powerful, scalable platform for modern data teams.
Architecture at a Glance
- Auto-scaling ECS Cluster with compute and memory-optimized instances
- Airflow webserver and scheduler as ECS services behind ALB
- Meltano pipelines triggered on-demand as ECS tasks
- EFS for shared DAGs, logs, and project storage
- Infrastructure managed end-to-end with Terraform
Deployment Highlights
- Rapid provisioning via Terraform automation
- On-demand, isolated Meltano tasks improve reliability and scaling
- Integrated monitoring with CloudWatch and ECS Container Insights
- Support for both EC2 and Fargate deployment modes
What Sets It Apart
- End-to-end infrastructure-as-code architecture
- Native AWS service integration (EFS, ALB, Secrets Manager)
- Proven patterns for retries, alerting, and fan-out task orchestration
What’s Next
We’re evolving toward EKS-based orchestration, multi-region failover and extended automation. This architecture is built to grow with your data demands.
Want to implement this stack? Read the full technical guide or connect with us to discuss your data infrastructure needs.
