Scalr vs. Terraform Cloud (HCP Terraform)

In this article, we break down what Scalr and HCP Terraform are designed to do, then focus on the practical differences teams usually run into when standardizing Terraform at scale.

What is Scalr?

Scalr is a Terraform-centered infrastructure automation platform used to manage infrastructure as code (IaC) across teams and environments. It adds organizational controls around Terraform, such as centralized policy enforcement, standardized workflows, and role-based access, while supporting everyday needs like state management, remote execution, and integrations with CI/CD pipelines and identity providers.

Scalr is typically adopted by organizations that want more consistent governance and visibility over infrastructure changes without abandoning existing Terraform practices.

Key features of Scalr include:

• Terraform automation workflows (remote runs, approvals, standardized execution patterns)
• State management (centralized storage, locking, workspace organization)
• Role-based access control (RBAC) for teams, environments, and projects
• Policy and governance controls to enforce guardrails and compliance
• Multi-environment support (dev/test/prod segmentation and promotion patterns)
• Integrations with VCS providers, CI/CD tools, and identity/SAML/SSO systems
• Auditability and visibility via run history, logs, and change tracking

What is Terraform Cloud (HCP Terraform)?

Terraform Cloud, now branded HCP Terraform, is HashiCorp's hosted (SaaS) platform for running and governing Terraform workflows across teams. It centralizes Terraform operations by providing managed workspaces that can execute runs remotely, store and version state, and integrate with version control so infrastructure changes follow a consistent, auditable process.

Key features of Terraform Cloud include:

• Remote Terraform runs via workspaces (standardized execution environments)
• Managed state storage and history (workspace state, versioning, and state version rollback support)
• VCS integrations and VCS-driven workflows (trigger runs from commits and pull requests)
• Policy enforcement and policy as code (for example, Sentinel and OPA (edition-dependent))
• Private registry for modules and providers (share approved artifacts internally)
• Run Tasks to plug third-party checks into the run lifecycle
• Drift detection and health assessments to spot changes outside Terraform

Key differences between Scalr and Terraform Cloud (HCP Terraform)

At a high level, Scalr is a governance and control plane that runs Terraform (and also OpenTofu) with vendor-neutral guardrails, while Terraform Cloud (HCP Terraform) is HashiCorp's native SaaS built around Terraform-first workflows.

Here are five differences that tend to matter most in practice.

1. Deployment model and where runs execute

HCP Terraform is HashiCorp's hosted SaaS offering (Terraform Cloud rebranded). HashiCorp also offers Terraform Enterprise as a self-hosted distribution for organizations that want a private instance.

Scalr is also a centralized remote-operations platform and, like HCP Terraform, can run Terraform operations using agents deployed in your own infrastructure when workloads need private network access.

In practice, both platforms separate a control plane (UI/API, state, and workflow) from the execution environment (where plans and applies run). HCP Terraform formalizes this through agent pools that connect to private or on-premises environments, and Scalr similarly supports agent-based execution so teams can keep network access and tooling close to the target infrastructure.

2. Organizational structure and permission boundaries

Scalr uses a three-tier hierarchy (Account → Environment → Workspace) designed to support inheritance of configuration, policies, and integrations. HCP Terraform organizes resources with organizations and workspaces, and adds projects as a grouping layer to scope access and ownership across multiple workspaces.

Both platforms can support multi-team setups, but they differ in how you model governance at scale: Scalr emphasizes inheritance across environments (helpful when many workspaces share common guardrails), while HCP Terraform projects emphasize group-based boundaries and permissions for sets of workspaces (helpful when teams map cleanly to workspace groups).

3. Policy as code options and how guardrails are expressed

Scalr's policy engine is built around Open Policy Agent (OPA) and Rego to evaluate Terraform/OpenTofu data and enforce administrator-defined rules. HCP Terraform supports both Sentinel and OPA as policy-as-code frameworks, with availability and permissioning depending on the edition/plan.

A practical difference is portability and skill alignment: OPA/Rego is used across many systems beyond Terraform, while Sentinel is specific to the HashiCorp ecosystem. At the same time, both platforms use policy sets applied globally or scoped to subsets of workspaces/projects, so the day-to-day governance workflow can look similar even when the policy language differs.

4. Extending the run lifecycle with external checks and automation

HCP Terraform provides Run Tasks to integrate third-party tools at defined points in the run lifecycle (for example, validating configuration, scanning plans, or running security checks). Scalr supports similar needs with Hooks/Custom Hooks (scripts or commands run before/after plan/apply) and webhooks for event-driven notifications to external systems.

Both patterns can achieve comparable outcomes (policy checks, security scans, linting, and change notifications), but they differ in operational shape. Run Tasks are typically modeled as integrations attached to workspaces, while hooks execute as part of the run environment and can be standardized through a hooks registry and inherited across environments.

5. IaC engine scope and mixed-toolchain support

Scalr explicitly targets workflows for Terraform and OpenTofu, positioning itself for organizations that run both tools (or are evaluating OpenTofu alongside Terraform). HCP Terraform is centered on Terraform workflows, so organizations with a mixed Terraform/OpenTofu footprint typically need to verify how non-Terraform executions fit into their operating model.

Because both platforms are built around remote operations, workspaces, and governance controls, this difference tends to show up during standardization and migration work, for example, deciding whether one control plane should govern multiple IaC engines or whether Terraform-only governance is sufficient for the organization's roadmap.

Alternative to Scalr and TFC - Spacelift

Organizations often look for an alternative to Scalr and Terraform Cloud (HCP Terraform) when they need one place to standardize governance and automation beyond Terraform, want more flexibility in how runs execute and integrate with existing platforms, or prefer a tool that can adapt to multi-team, multi-account, and multi-cloud operating models without forcing a single-vendor ecosystem.

Spacelift is an infrastructure orchestration platform designed to run and govern IaC workflows across teams and environments. It provides a centralized control plane built around stacks (the unit that ties together source code, configuration, and runtime settings) and worker pools for executing runs. You can deploy Spacelift as SaaS or self-host it.

Beyond Terraform-style workflows, Spacelift supports multiple IaC technologies, which makes it a practical option for organizations standardizing automation and governance across heterogeneous environments or migrating between tools over time.

With Spacelift, you get:

• Fine-grained Policies to control what resources engineers can create, which parameters they can use, how many approvals a run needs, which tasks you execute, what happens when a pull request is opened, and where to send notifications
• Stack dependencies to model real-world, multi-stack workflows — for example, provision EC2 instances with Terraform and configure them with Ansible in a single automated pipeline
• Self-service infrastructure with Blueprints, so developers can request and manage their own stacks without giving up guardrails or central control
• Quality-of-life features like contexts (reusable containers for environment variables, files, and hooks), plus the ability to run arbitrary code when you need to go beyond standard Terraform workflows
• Drift detection and optional automated remediation, so you can catch and fix drift before it becomes an incident
• Multi-IaC support by design, so you're not locked into a single tool or vendor as your platform evolves
• Dynamic cloud credentials for AWS, Azure, and GCP, so runs use short-lived access tied to identity instead of static keys stored in configuration

The table below compares all three tools:

If you want to learn more about what you can do with Spacelift, check out this article.

Key points

The clearest way to separate Scalr and HCP Terraform is to look at what each platform is built around and how it's meant to be extended. HCP Terraform is HashiCorp's first-party Terraform platform, while Scalr is an independent control plane that also supports OpenTofu.

In practice, those choices tend to show up most in execution options, organizational and permission modeling, policy tooling, and integration style.

If your decision hinges on flexibility, control, or fitting Terraform into a wider delivery ecosystem, it can also help to compare a third option like Spacelift - especially if you want a dedicated infrastructure orchestration layer with strong governance and deep integration into your existing CI/CD practices.