CloudGoScaling the product meant scaling the whole stack.
Telos, an early-stage developer productivity SaaS company, had launched on Render. Its API services and background AI workers were tightly coupled, so scaling required duplicating entire service stacks. With growth ahead and AWS credits available, the team needed an architecture plan and a data-backed view of when a migration would make financial sense.
The context behind the decision.
The planning considered the existing PaaS deployment, service relationships, usage patterns, product requirements, and growth assumptions linked to peak concurrency. It evaluated how AWS could support independent scaling while preserving a practical migration and rollback path.
What the connected picture revealed.
Scale the API and workers independently
The target architecture separated backend API services from background AI workers, with static frontend hosting and a CDN.
Make the transition reviewable
The plan used shadow deployments and weighted traffic shifts, retained Render as a rollback option, and defined checks for authentication, webhooks, and background jobs.
Connect the move to the economics
A cost model compared AWS and Render as concurrency increased, estimating a break-even point near 500 concurrent customers.
A plan the team could work from.
CloudGo delivered an AWS-ready architecture and migration plan in one day. The model projected approximately 50–60% lower infrastructure cost at scale compared with Render. Together, the technical plan and cost model gave Telos a way to evaluate both how to migrate and when the move could be justified.
- An AWS target architecture with independent service scaling
- Phased migration steps and a rollback strategy
- Cutover validation checkpoints
- A cost and scaling model tied to peak concurrency
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