PathPilot: AI cloud infrastructure optimization
"Working with Tech 42 was a fantastic experience. Their team brought deep AWS expertise and made a significant impact on our infrastructure, helping us transition from manual AMI-based deployment to a modern, scalable architecture using ECS, Docker, and SQS. The shift has streamlined our DevOps process and positioned us to better support future AI workloads.
Our assigned engineer, in particular, was an incredible partner, knowledgeable, hardworking, and always responsive. His support with Terraform, AWS deployment, and infrastructure tuning was invaluable. We learned a lot throughout the engagement and were able to move significantly faster thanks to the foundation Tech 42 provided.”
David Altman
Head of Artificial Intelligence
Project summary
PathPilot needed to move beyond manual, AMI-based deployments to support scaling AI workloads. Tech 42 refactored their backend and worker services into Docker containers deployed on AWS ECS Fargate. The architecture replaced Redis with AWS SQS for message queuing and implemented Celery for task processing. Service discovery was configured through AWS Cloud Map. Automated CI/CD pipelines replaced manual deployment steps. The new infrastructure scales based on CPU and queue metrics, enabling PathPilot to support variable demand without manual intervention. The transition modernized their DevOps process and positioned the platform to handle future AI infrastructure growth. Deployment speed increased, and operational overhead decreased through automation and container orchestration.
