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No-Code Infrastructure Platform

Self-service Aurora provisioning through Backstage — production-ready clusters without writing Terraform, roughly 80–95% faster than ticket-based workflows.

  2 minute read  

The bottleneck in database infrastructure was never the databases — it was the queue in front of them. This platform removed the queue: product teams provision production-ready Aurora clusters through a web form, no Terraform required.

Challenge

Infrastructure as code made provisioning repeatable, but it traded one bottleneck for another:

  • Terraform expertise required. Not every team has it, and shouldn’t need it to get a database.
  • Lead times. A routine cluster request waited on the platform team’s queue.
  • Inconsistent patterns. Left to hand-write HCL, teams produced infrastructure that drifted in quality and shape.
  • The platform team as critical path. Every database request flowed through a small group — that doesn’t scale.

The goal: democratize provisioning without democratizing misconfiguration.

Approach

Three layers, each doing one job:

Opinionated wrapper modules. Engine-specific Terraform modules that require only application name, environment, and size. Everything else is a curated default: current stable engine version, 30-day backup retention, encryption on, Performance Insights on, deletion protection on in prod, monitoring and secrets wired in. Engine versions restricted to supported releases; instance sizes limited to approved tiers.

Backstage templates. The user-facing form. A template collects the three or four real decisions, validates the rest, and generates a repository with Terraform configuration and a ready-to-run pipeline. No HCL visible anywhere.

Integrated operations. Vault for credentials, monitoring dashboards and alarms provisioned with the cluster — out of the box, not as a follow-up ticket.

Two practices made it stick:

  • Customer zero. Every module change is validated by provisioning through the real template flow before release — the platform team uses its own platform first.
  • One-to-many publishing. The module release pipeline maps one upstream module to engine-specific wrappers, with regression testing at every tier.

Result

Product teams provision production-ready Aurora MySQL and PostgreSQL clusters in minutes instead of days — roughly 80–95% faster than the ticket-based workflow, an estimated 3,000+ engineering hours a year given back. Every cluster follows the same hardened pattern, so review, cost analysis, and security scanning all get consistency for free.

The real trade-off: the platform is now a product with users. Defaults, upgrade guides, and documentation are ongoing obligations — but that scales infinite times better than being the provisioning bottleneck.