AWS infrastructure that governs itself
CloudBooster replaces the cloud engineer function for teams that can't afford one yet — AI authors the change, policy governs it, your account runs it.
How CloudBooster runs the cloud engineer function
On the hosted Platform, every change runs the same path: proposed, checked, approved, applied, and recorded, with evidence at each gate.
How does the Platform move a proposed change to production without skipping checks?
These are the steps a cloud engineer performs manually, 10 times a week. CloudBooster runs them in software, for every change, with a complete audit trail.
On the hosted Platform you describe the outcome, CloudBooster plans it, runs checks, routes approval, you apply in your account under control, and evidence is stored.
Before the governed lifecycle
When you are ready for propose → check → approve → apply in your cloud account, the Platform gives you a governed path with checks, approvals, and evidence.
Propose
Describe the change you want in plain English; the AI assistant turns intent into a plan and the underlying Terraform or CloudFormation. You review what was generated before it enters Check.
Check
Validate security, cost, and conflicts on the real change before it reaches production.
Approve
Explicit human or policy sign-off; approvers see checks, the plan, and who proposed it.
Apply
Controlled execution in your account; the run stops on unsafe or unexpected states.
Verify
Record what changed, confirm outcome, and watch drift against what was approved.
Monitor
Watch drift, health, and regressions after the change so issues surface while still small.
Every change that moves through this lifecycle becomes a ChangeSet: the atomic unit of governed infrastructure change in CloudBooster.
How it runs in your account
CloudBooster's control plane orchestrates the lifecycle and governance, while your AWS account runs the infrastructure workload under your ownership.
CloudBooster control plane
- ›Compiles change proposals into plans
- ›Runs pre-apply checks (security, cost, conflicts)
- ›Routes approvals to the right person
- ›Records every ChangeSet and audit event
least-privilege
Your AWS account
- ›Apply runs here, under your IAM
- ›Your infrastructure lives here
- ›Your data, secrets, and network stay here
- ›You can revoke our access at any time
Pricing
The plans below are for the hosted Platform when you deploy and govern at scale in your account.
Start with a Platform pilot or early team rollout for new infrastructure on AWS. Expand usage as more infrastructure changes flow through CloudBooster.
Free
Explore the full platform. One project, one environment.
- •1 project, 1 environment
- •AI assistant included
- •Full infrastructure catalog & composition
- •Preview → approve → deploy
- •3 security checks included
Starter
Ship real infrastructure with your team.
- •2 projects, 2 environments
- •5 team members
- •3 connected cloud accounts
- •50 ChangeSets/mo
- •5 security checks + remediation
- •Manual drift detection
- •Email support
Growth
Team-scale governance for growing teams.
- •5 projects, 5 environments
- •20 team members
- •Separate approver required
- •Unlimited ChangeSets
- •Email + support cases
Premium
Enterprise scale, compliance & dedicated support.
- •Unlimited projects & environments
- •Unlimited team members
- •Separation of duties (SoD)
- •Full audit trail + SIEM export
- •Scheduled scans + auto-remediation
- •Enterprise SSO
- •Priority + dedicated support
You still pay your cloud provider(s) directly.
The cloud engineer function costs $180K/year.
4 months to hire. 60% of its time on toil that software can do.
Creating infrastructure changes is now trivial for any engineer or AI coding agent. The hard part hasn't changed: someone still has to evaluate blast radius, route approval, apply safely, and record what ran. CloudBooster is that someone — running in software, in your account, at machine speed.
AI coding agents and IDE assistants can also invent AWS shapes that look plausible: wrong SKUs, deprecated APIs, or policies that do not match your account. Governed ChangeSets on the Platform keep production changes grounded.
These are the failure patterns we see most often:
CTO as bottleneck
The CTO or founder still owns every infra change, slowing product work.
Unsafe AI-generated changes
AI ships infra with no one checking blast radius, cost, or security.
Too early for a DevOps hire
You are too small to hire DevOps, too big for ad-hoc scripts.
Consultant dependency
You need a consultant for every change; knowledge never stays in-house.
Is CloudBooster a good fit for our stage and how we use AWS?
We built for startups and lean teams on new or growing AWS work where a founder or engineer still owns cloud: no platform org yet, no spare DevOps hire.
- ↗Developers building and operating AWS infrastructure with governance needs
- ↗Building new infrastructure on AWS (Platform)
- ↗Lean engineering team without a dedicated DevOps / platform team
- ↗Want safer infrastructure changes without adding headcount
- ↗Already feeling the pain of ad-hoc infra ownership
- ↗Want a governed process from day one
- →Broader coverage of existing AWS estates
- →CLI/MCP depth with the hosted Platform
- →Multi-cloud setups
- –Multi-cloud-first enterprises
- –Large organizations with mature internal platform teams
- –Teams looking only for a Terraform runner
- –Teams expecting a hosting platform / PaaS
Questions engineering teams ask before adopting CloudBooster
Ready to replace your cloud engineer function with software?
CloudBooster runs the cloud engineer function for lean teams on AWS. Limited pilot slots open now.
What can we run with CloudBooster today, and what is on the roadmap?
Implementation today is AWS-first: new infrastructure with guided onboarding and the governed lifecycle (propose, check, approve, apply, record). Deeper CLI and MCP ties to the hosted Platform and multi-cloud setups are on the roadmap.