Automated CI/CD for an AI Manufacturing Platform — From Code Push to Production in Minutes
For Autolist.ai
Autolist is an AI-powered platform for manufacturing companies. It deploys intelligent agents that turn technical documents — specs, drawings, CAD files — into structured, living product data. The platform links documents to material masters, extracts attributes automatically, and keeps everything synchronized as engineering changes happen.
The Challenge
Autolist was being built from the ground up. The platform needed to process complex documents, run AI models, handle async workflows, and integrate with enterprise systems — all while moving fast enough to ship features weekly and iterate based on early customer feedback.
- The core DevOps challenges:
- Shipping speed without sacrificing reliability. The engineering team needed to push code multiple times a day without worrying about breaking production. Every deployment had to be safe, repeatable, and reversible.
- Multiple services, one coordinated pipeline. This wasn't a single monolith. The platform consisted of multiple microservices — each with its own build, its own container image, its own deployment target on Kubernetes. Coordinating this manually would consume engineering hours every day.
- Environment consistency. "It works on my machine" had to be eliminated from day one. Development, staging, and production needed to run identical infrastructure — same services, same networking, same configuration patterns.
- No dedicated DevOps team. There was no separate ops team to manage deployments, monitor pipelines, or respond to infrastructure issues. The CI/CD system had to be self-sufficient — automated enough that developers could focus entirely on building the product.
Project Details
Our Solution
We built a fully automated, production-grade cloud platform where everything is managed through Terraform — from CI/CD pipelines and Kubernetes workloads to networking, secrets, and data services. With a single terraform apply
Automated Pipeline: Push to Deploy
The CI/CD pipeline eliminates every manual step between writing code and running it in production. A developer pushes code — that’s the last human action.
- Git-based triggers — Cloud Build pipelines activate automatically per branch and service
- Automated build & test — Docker images are built and validated before deployment
- Artifact Registry versioning — every image is tagged, traceable, and rollback-ready
- Automated GKE deployment — no SSH, no kubectl, no manual intervention
- Fast rollback — redeploy any previous image within minutes if issues arise
Infrastructure as Code: One Codebase, Every Environment
The entire platform infrastructure is defined in Terraform and managed through Git-based workflows. Staging and production environments are generated from the same codebase with environment-specific parameters.
- One-command environment setup — full infrastructure via
terraform apply - Version-controlled infrastructure — every change reviewed and tracked in Git
- No environment drift — what you test is exactly what you ship
- Full audit trail — infrastructure changes are transparent and reproducible
- No tribal knowledge — infrastructure lives in code, not in people’s heads
Microservices Architecture & Platform Services
The platform runs as independent microservices on GKE, allowing each service to scale, deploy, and roll back without impacting the rest of the system.
- Independent microservices — isolated deployments, scaling, and resource allocation
- Temporal workflows — orchestration of complex, multi-step processes
- Redis — caching, session management, and real-time data access
- RabbitMQ — asynchronous messaging and event-driven communication
- Cloud SQL (PostgreSQL) — managed database with backups and reliability
Visual Showcase
Screenshots and interfaces from the final product
The Results
Measurable impact within the first 6 months
Technologies & Tools
Related Projects
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