Production-Grade Microservices on GKE — One Terraform Command, Full Visibility, $110/mo Dev
For TradeVo.ai
TradeVo.ai is an AI-powered trading intelligence platform that processes real-time market data, orchestrates automated workflows, and delivers actionable insights to traders. The platform demands low-latency processing, event-driven architecture, and rock-solid reliability — the kind of infrastructure that typically costs enterprise-level budgets.
The Challenge
TradeVo.ai needed a platform that could run complex, stateful microservices — not simple stateless containers, but Redis clusters, RabbitMQ with high availability, a Temporal workflow engine, and a managed SQL database — all coordinated on Kubernetes. The requirements were clear:
- One command to deploy everything. No SSH-ing into servers, no clicking through console UIs, no maintaining separate YAML files that drift from reality. One Terraform command provisions the entire stack — from the GKE cluster to the last secret in Secret Manager.
- Full infrastructure visibility. The team needed to see exactly where every dollar goes in billing, trace every build through the CI/CD pipeline, and access workload logs across all services from a single pane of glass. No black boxes.
- Production reliability at startup costs. The architecture had to support horizontal and vertical auto-scaling, HA failover for all stateful services, and zero-downtime deployments — without the $5K-$10K/month cloud bills that typically come with this level of infrastructure.
- Security without complexity. API keys, database credentials, and service tokens managed through proper secret management with IAM bindings — not environment variables scattered across config files.
Project Details
Our Solution
We made a deliberate architectural choice: everything is managed in Terraform — from the GKE cluster and workloads to networking, CI/CD, secrets, and storage. With a single terraform apply
What $110/Month Gets You in Development
The development environment isn't a stripped-down toy. For $110/month, the team gets:
- Running GKE cluster with all workloads deployed
- Cloud SQL instance — managed PostgreSQL
- Temporal workflow engine — same orchestration layer as production
- Redis cluster — caching, session management, real-time data
- RabbitMQ cluster — async messaging and event routing
- Cloud Build pipelines — automated builds on every push
- Artifact Registry — container image versioning
- Secret Manager — rotatable and auditable credentials
- Full logging & monitoring — same observability stack as production
What ~$1,000/Month Gets You in Production
Production runs the same Terraform codebase with production-grade parameters:
- Horizontal Pod Autoscaler (HPA) — scales automatically with traffic
- Vertical Pod Autoscaler (VPA) — optimized resource allocation
- Cluster autoscaler — dynamic node scaling
- Redis (HA mode) — automatic failover
- RabbitMQ (HA mode) — resilient messaging
- 5 Temporal production workers — trade signal processing & async jobs
- Cloud SQL (HA) — automated failover & backups
- Multi-stage CI/CD — build → test → push → deploy
- Full observability — logs, metrics, and audit trail
Full Infrastructure Visibility
One of the most underrated aspects of this architecture: the team can see everything.
- Billing visibility — tagged resources with clear cost breakdowns
- Pipeline visibility — logged Cloud Build executions with full audit trail
- Workload visibility — structured logs & metrics across services
- Infrastructure change tracking — every change versioned via Terraform
- Secret access tracking — monitored credential access logs
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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