A practical look at Spacelift, env0, Atlantis, and Scalr for teams outgrowing HCP Terraform on price, policy, or OpenTofu support.
HCP Terraform (the platform formerly branded Terraform Cloud) is the default answer when a team decides it needs remote state and run automation. It is a fine product. But we keep hearing the same three reasons teams start shopping around, and none of them are about whether the tool works.
The first reason is pricing. HCP Terraform charges per resource under management. That model is fine at 500 resources and painful at 50,000. A team running a few hundred workspaces with large state files can watch the bill cross five figures a month without adding a single feature. When your cost scales with your infrastructure count rather than your team size, growth punishes you.
Second, policy and governance features are gated behind the higher tiers. Sentinel, HashiCorp's policy language, is proprietary and only unlocks on the Plus tier. Teams that want Open Policy Agent (OPA) and Rego, which they already use for Kubernetes admission control, have to look elsewhere or run policy checks outside the platform.
Third, OpenTofu. After the license change to BSL, a chunk of the community moved to OpenTofu, the MPL-licensed fork. HCP Terraform does not run OpenTofu. If you have committed to the fork, you need a runner platform that supports it, and most of the alternatives do.
Strip away the branding and a Terraform automation platform is doing a handful of jobs:
plan and apply from the pull request itself.Every option below covers the first two. Where they diverge is policy, drift, self-hosting, and how the pricing meter runs.
Spacelift. The most feature-complete commercial alternative. It supports Terraform, OpenTofu, Pulumi, CloudFormation, Ansible, and Kubernetes from one control plane. Policy is OPA/Rego, applied at multiple decision points (which plans run, which get auto-approved, what triggers notifications). Drift detection, stack dependencies, and self-hosted runners on your own compute are all first-class. Pricing is per-user plus concurrent runs, so it decouples cost from resource count. It is the strongest pick when you have serious governance requirements and a platform team to own it.
env0. Positioned around cost visibility and self-service environments. Developers spin up ephemeral environments through templates, and env0 tracks the cloud spend of each one and tears them down on a TTL. It supports Terraform, OpenTofu, Terragrunt, and Pulumi, uses OPA for policy, and leans into the "internal developer platform" angle. If your pain is developers waiting on ops to provision sandboxes, env0 targets that directly.
Atlantis. The open-source, self-hosted incumbent. You run it yourself, it listens for pull request webhooks, and it comments plans back into the PR. No per-resource fee, no per-seat fee, just the server you host it on. The trade-off is that Atlantis is PR automation and nothing more. It has no built-in remote state (you point it at your own S3 or GCS backend), no managed drift detection, and policy is bolted on via a Conftest step you wire up yourself. For a cost-conscious team that already knows Terraform, it is often all you need.
Scalr. A middle path. Remote state, RBAC, OPA policy, drift detection, and a hierarchy of environments, priced per-run rather than per-resource. It positions itself explicitly as a cheaper HCP Terraform replacement and supports OpenTofu. Less sprawling than Spacelift, more managed than Atlantis.
GitHub Actions / GitLab CI (DIY). You can skip a dedicated platform entirely. A workflow runs terraform plan on PR and terraform apply on merge, state lives in S3 with a DynamoDB lock, and policy is a Conftest job. It is free-ish and fully under your control. It is also unpaid platform-engineering work: you own the state locking edge cases, the secret handling, the drift cron, and the plan-output-to-PR plumbing that the commercial tools give you out of the box.
Here is a small atlantis.yaml that runs a Conftest policy check between plan and apply, so a bad plan never reaches apply:
version: 3
projects:
- name: production-network
dir: environments/prod/network
workspace: default
terraform_version: v1.9.5
autoplan:
when_modified: ["*.tf", "../../modules/**/*.tf"]
enabled: true
apply_requirements: [approved, mergeable]
workflow: policy-checked
workflows:
policy-checked:
plan:
steps:
- init
- plan
- run: conftest test $PLANFILE --policy /policies
apply:
steps:
- apply
The apply_requirements line is the quiet hero. It refuses to apply unless the PR is approved and mergeable, which closes the "I ran apply on my own unreviewed change" gap that burns teams.
If you are leaving HCP Terraform over cost and you are Terraform or OpenTofu only, start with Scalr and price it against your actual run volume. It is the least disruptive swap. If you have never had automation at all and you are cost-sensitive, stand up Atlantis first, because it teaches you what PR-driven workflows should feel like before you pay for one.
If governance is the real driver, if you have Rego policies you want to enforce and more than one IaC tool in play, go straight to Spacelift and give a platform engineer ownership of it. Do not try to reproduce it in raw CI. The DIY route is genuinely cheaper only until you count the hours spent maintaining it.
For the wider tooling landscape, see our guide to the best Infrastructure-as-Code tools, and for a head-to-head on the commercial platforms, Spacelift vs env0 vs Atlantis.
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