The pattern we built for
A central platform team runs the infrastructure every product team in the company ships on. Every change funnels through one queue.
Every change funnels through one team.
Plan time is a tax on every downstream team.
You are the bottleneck
Every product team is downstream of your queue. A 20-minute plan is a 20-minute tax on the whole org.
Teams need isolation
Product teams can't step on each other's state, but you operate it all together.
Compliance is non-negotiable
Regulated industries, sensitive workloads, or sovereign deployments. Self-hosted isn't a nice-to-have.
The platform team queue
Same four teams. Same four changes. Two architectures.
Traditional Backend
Stategraph
Why Stategraph fits
Architecture choices that pay off at platform scale.
Resource-level locking
Independent teams and independent changes don't wait on each other. The platform team stops being a serialization point.
Multi-state transactions
One plan, one apply across every state your platform touches. True blast radius across teams, no glue scripts.
SQL-queryable resource graph
WHERE ami = 'ami-abc';
Answer "which teams use this AMI" or "where is this key referenced" in a query, not a half-day audit.
Subgraph execution
Plan time scales with the size of the change, not the size of the platform. 20,000 resources stays fast.
Drop-in for Terraform/OpenTofu
Your existing modules, providers, and code work unchanged. Migration is configuration, not rewrite.
RBAC and audit by default
Per-team boundaries, per-environment permissions, and a full transaction history that satisfies auditors.
Does this describe your team?
If you're running an internal platform that the rest of the company depends on, we should talk. Demos are run by engineers, not sales.
Need deployment options, SSO, or a custom SLA? See Enterprise.