What Role Do CI/CD Tools Play in Infrastructure Workflows?

For Terraform-based infrastructure, CI/CD isn’t just about automation - it’s about eliminating manual risk.

A good CI/CD setup runs terraform init, plan, and apply automatically when changes are pushed to a branch or opened as a pull request. It makes sure that every run uses pinned provider versions, the correct backend, and environment-specific variables. No one runs Terraform locally - which means no more drift caused by someone applying from the wrong workspace or skipping a plan.

It also enforces review. Every infrastructure change starts with a pull request. CI runs a plan, posts the diff, and the team reviews it. Nothing gets merged or applied without approval. This gives you a clear audit trail: who made the change, what exactly changed, and when it was applied.

CI/CD makes Git the gatekeeper. If it’s not in version control, it doesn’t get deployed. That tight coupling between code and infrastructure means fewer surprises in production and makes rollback trivial.

On top of that, it’s how you integrate secrets management, policy checks (like OPA or Sentinel), and drift detection. Without CI/CD, you’re relying on tribal knowledge and shell scripts. With it, you have a repeatable, reviewable, and secure way to manage infrastructure at scale.

What Should You Look for in a CI/CD Tool for Terraform?

Once you’ve decided to manage infrastructure through CI/CD, the next step is choosing the right tool. Not every CI/CD platform supports Terraform well. Some need custom scripts just to get started, while others miss critical features like policy checks or secure secrets handling.

Here’s what really matters when evaluating a CI/CD tool for Terraform:

Terraform Support

The tool should run init, plan, and apply cleanly in isolated environments. Look for support for remote backends, provider versioning, modules, and per-environment configs. If you’re writing wrappers just to make basic workflows run, that’s a red flag.

Secrets Management

Terraform needs access to credentials and tokens. Your CI/CD tool should handle secrets securely via vaults, scoped env vars, or native secrets management without exposing them in logs or pipelines.

Git Integration

The tool should support pull-request-based workflows: plan on PR open, apply on merge or approval, and ideally post comments back to the PR. Everything should tie back to version control.

Policy Enforcement

Whether it’s OPA, Sentinel, or a custom ruleset, your tool should help block risky infrastructure changes before they go live. Example: preventing untagged resources or open security groups.

Drift Detection

It should catch changes made outside Terraform by comparing actual infrastructure to state and alerting you to drift, ideally via PR checks or GitHub comments.

Tool-by-Tool Breakdown: How Each CI/CD Option Supports Terraform

Now that we know what makes a CI/CD platform Terraform-ready, let’s look at how some of the most widely used tools actually perform in practice. This isn’t just a feature checklist – it’s a realistic look at how these platforms fit into day-to-day infrastructure work: how much effort they take to set up, how well they handle Terraform specifics, and whether they help or get in the way as your infrastructure scales.

In this blog, we'll cover:

Terrateam

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Terrateam is purpose-built GitOps CI/CD for Terraform and OpenTofu that runs entirely inside GitHub. It’s not a generic CI tool - it’s a Terraform-specific automation layer that handles planning, applying, drift detection, cost estimation, and policy enforcement, all through pull requests. You install it as a GitHub App and configure it with a YAML file - no pipeline logic, no external runners, and minimal setup. For teams already using GitHub, Terrateam eliminates the need to script or maintain Terraform workflows in GitHub Actions directly. It listens for pull request events, runs terraform plan, and posts results as comments. When approved, it applies automatically - respecting locks, policies, and OIDC-based authentication along the way.

Upsides

Purpose-built for Terraform and OpenTofu: Not a general-purpose runner. Terrateam understands Terraform workflows deeply, including plan/apply lifecycles, state handling, and policy enforcement.
No-pipeline setup: You define behavior through a simple YAML config. No need to write CI scripts or wire up custom steps.
Smart locking and concurrency control: Prevents conflicting changes across environments by managing locks and execution queues.
Built-in policy enforcement: Integrates with OPA (via Conftest or Gatekeeper) to enforce tagging, region constraints, and custom policies.
Drift detection and cost estimates: Automatically detects drift between live infrastructure and code, and surfaces cost impact with Infracost.
OIDC-based cloud authentication: No static credentials - Terrateam uses GitHub’s OIDC provider for secure, short-lived authentication.
Multi-environment support: Cleanly separates dev, staging, and prod workflows with environment-aware config and variables.

Downsides

GitOps mindset required: Terrateam is built around a GitOps-first model. Teams unfamiliar with pull request-driven workflows might face a learning curve, but once adopted, it tends to simplify collaboration and reduce manual risk.

Terrateam is ideal for teams managing infrastructure-as-code in GitHub who want Terraform workflows that are secure, scalable, and policy-driven - without the overhead of building and maintaining CI pipelines. For teams using GitHub, it's the top choice on this list for Terraform workflows in 2025.

Most importantly, Terrateam is open source - you can review, self-host, and contribute to it.

GitHub Actions

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For teams that want more general-purpose automation or need to run Terraform alongside other workflows - GitHub Actions is the next logical step. It runs directly inside your GIthub repository, so triggering Terraform workflows on pull requests or merges is pretty simple. You define workflows using YAML, run Terraform with shell steps or community-maintained actions, and wire it all up using GitHub’s event system.

This tight coupling between code and CI makes it easy to get started - but GitHub Actions is a general-purpose automation tool. It doesn’t know anything about Terraform, so you’ll be responsible for stitching everything together: remote backends, secrets, environment variables, policy checks, and apply safety.

Upsides

Tight GitHub integration: It runs directly in your repo. Triggers like push, pull_request, or workflow_dispatch make it easy to automate plan and apply commands around PRs and merges.
PR-based workflows: Teams can enforce that every infrastructure change goes through a PR, with required approvals and automated plan diffs.
Rich action ecosystem: There are hundreds of Terraform-related actions for formatting, validating, planning, and applying code - no need to reinvent the wheel.
Minimal setup for small teams: For smaller teams or simpler setups, GitHub Actions keeps infrastructure and CI tightly coupled without introducing any kind of extra tools.

Downsides

No native Terraform context: GitHub Actions doesn’t understand Terraform-specific workflows. You have to handle things like locking, state consistency, and error handling yourself.
Secrets management is basic: Secrets are encrypted and stored at the repo/org level, but there’s no built-in support for automatic rotation, fine-grained access control, or dynamic credentials.
No policy or drift support out of the box: You’ll need to bolt on tools for drift detection, OPA/Sentinel policy checks, and environment separation.
Scaling is manual: As infra scales, so does the complexity of the workflows. Maintaining hundreds of lines of YAML for multi-env Terraform becomes painful without internal tooling.

GitHub Actions is great when your infrastructure is in GitHub, your Terraform usage is pretty simple, and you don’t need heavy guardrails yet. But as your team scales or compliance requirements grow, you may need something more purpose-built.

GitLab CI/CD

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While GitHub Actions fits well for teams working inside GitHub, many organizations use GitLab as their central DevOps platform. In that case, GitLab CI/CD becomes the obvious choice - not just for version control, but for handling infrastructure workflows end-to-end within the same system.

GitLab provides a tightly integrated experience. You define Terraform pipelines in .gitlab-ci.yml, run jobs using GitLab Runners, and manage secrets, environments, and approvals all within the GitLab UI. This consolidation reduces external dependencies and makes it easier to enforce infrastructure change processes across teams.

Like with GitHub Actions, Terraform automation is something you have to build - GitLab CI/CD doesn't come with built-in knowledge of Terraform. But it gives you the right primitives to support full workflows from plan to apply.

Upsides

Unified platform for code and CI: Source control, pipelines, merge requests, and approvals all live in one place - making it easier to enforce infrastructure change workflows without stitching together tools.
Secure and flexible secrets management: Supports scoped CI variables and environment-level configuration, making it simple to inject cloud credentials or Terraform variables securely.
Merge-request-based automation: Plan runs on merge request open; apply runs only after approval and merge - all using native GitLab features like required approvals and protected branches.
Supports reusable Terraform pipelines: You can define consistent pipeline patterns using includes or templates, which helps scale across environments and teams.

Downsides

Lacks Terraform-native features: GitLab doesn’t understand Terraform-specific concerns like locking, policy gates, or state management. You’ll need to integrate external tooling for things like Sentinel or drift detection.
Pipeline logic can become brittle: Complex .gitlab-ci.yml files can get hard to maintain as infrastructure scales - especially when managing multiple environments, regions, or accounts.
No native plan diff rendering: You have to manually format and post Terraform plan outputs to merge requests if you want clear visibility during reviews.

GitLab CI/CD is a strong fit for teams standardizing on GitLab and looking for centralized control. It simplifies platform overhead but requires discipline to make Terraform workflows reliable, auditable, and scalable.

Azure DevOps Pipelines

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If you’re operating mostly within the Microsoft ecosystem, Azure DevOps Pipelines is the natural extension of your tooling. After GitHub Actions and GitLab CI/CD, which both focus on developer-first workflows, Azure DevOps brings a more enterprise-oriented setup - especially appealing to organizations already using Azure Active Directory, Azure Repos, and Azure Boards.

Azure Pipelines supports Terraform well, especially when targeting Azure infrastructure. It lets you automate init, plan, and apply steps using either inline scripts or the official Terraform extension. You can securely inject secrets from Azure Key Vault, enforce approvals between stages, and apply role-based access control across pipelines - all using Microsoft-native services.

It’s not as lightweight or intuitive as GitHub Actions, and it takes more time to configure, but if your infra is mostly in Azure, this tighter integration pays off.

Upsides

Strong Azure-native integration: Pipelines plug into Azure services natively - from resource provisioning to using managed identities and built-in RBAC. There’s minimal glue code needed to authenticate and deploy across your Azure subscriptions.
Enterprise-grade access and approval controls: Built-in pipeline environments support approvals, required reviewers, and deployment gates without needing any external tools. This makes it easier to enforce change workflows and compliance requirements.
Secure secrets handling via Azure Key Vault: You can link Key Vault to your pipeline and inject secrets at runtime without storing them in the pipeline definition. This adds a solid layer of security to Terraform workflows.
Support for modular pipeline templates: YAML-based pipeline templates make it possible to define reusable Terraform workflows across teams and services - helpful for managing multiple environments at scale.

Downsides

Initial setup is more involved: Compared to GitHub or GitLab, Azure Pipelines takes more configuration upfront - defining service connections, permissions, and environment scopes can slow down early adoption.
Steeper learning curve: The Azure DevOps interface and YAML syntax aren’t as friendly to newcomers. Teams without prior experience may find the UX less intuitive.
Best suited for Azure-first infrastructure: While it technically supports AWS, GCP, or on-prem targets, those use cases require more custom setup. Azure Pipelines shines when everything lives inside Azure.

Azure DevOps Pipelines is ideal for teams deeply embedded in Microsoft’s ecosystem. If your infrastructure is built on Azure and you’re already using Azure Repos or Boards, it gives you a full-stack, policy-compliant way to run Terraform without leaving the platform.

Atlantis

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Now, for teams that lean heavily into GitOps and want a focused solution just for Terraform, Atlantis is a compelling option. Unlike broader CI/CD platforms, Atlantis was built from the ground up to automate terraform plan and apply using pull request events - no dashboards, no extra UI, just comments and commit history driving everything.

You deploy it as a self-hosted service, point it at your Git provider, and it listens for events like PR open or merge. When someone opens a pull request, Atlantis runs terraform plan and comments the result. Once approved, a simple /atlantis apply comment triggers the deployment. It’s Git-native by design and avoids the overhead of managing full-blown CI pipelines.

Upsides

Pure GitOps workflow: Everything runs through Git. Plans are triggered by PRs, changes are reviewed in code, and applies happen through comments - no need to bounce between multiple systems.
Simple and fast to deploy: Atlantis is a single binary and easy to stand up. For small teams or internal platforms, you can get running in an hour.
Multi-Git provider support: It works with GitHub, GitLab, Bitbucket, and even self-hosted providers, giving teams flexibility across ecosystems.

Downsides

No UI or job dashboard: All interaction happens via Git comments. While that keeps things simple, it can make debugging harder and limits visibility for non-Git users.
No native secrets or policy engine: You’ll need to bolt on external tools or wrap Atlantis in custom scripts to handle secrets, policy enforcement, or approvals.
Scaling requires orchestration: Running Atlantis for many teams or projects usually means building tooling around it - repo whitelisting, auto-approvals, and lock coordination.
Operational burden grows with scale: It's not HA out of the box. Teams adopting it at scale need to manage persistence, state locking, and failover manually.

Atlantis is best suited for teams that want to keep Terraform workflows as close to Git as possible - with minimal dependencies and a strong audit trail. But as your organization scales, you may hit limitations around visibility, security, and multi-team orchestration.

Jenkins

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If you’ve been in infrastructure long enough, you’ve probably run into Jenkins. It’s one of the oldest and most flexible CI/CD platforms out there - and that’s both its strength and its weakness.

Jenkins can run anything. If you want to run Terraform, it’ll do it - but you’re on your own. You wire up the plugins, write the shell steps, manage the credentials, and maintain the agent fleet. There’s no native support for Terraform, no built-in security model, and no opinionated guidance. It’s a blank slate.

Upsides

Fully customizable: You can build exactly what you want, however you want it. Pipelines, triggers, and integrations can be tailored down to the finest detail.
Vast plugin ecosystem: There’s a plugin for almost everything - version control, secrets, notifications, runners, and beyond.
Universal runner support: Jenkins can run jobs across nearly any OS or environment, including hybrid on-prem/cloud setups.

Downsides

Heavy operational burden: You’re responsible for running Jenkins, securing it, upgrading plugins, scaling agents, and troubleshooting failures.
Terraform support is DIY: There’s no Terraform context built in - you write all the logic for init, plan, apply, error handling, and rollback yourself.
Pipeline complexity scales fast: Large Terraform setups require careful orchestration and often brittle Groovy or YAML scripts to coordinate environments and approvals.

Jenkins is a fit when you already have it running and need to bolt Terraform workflows onto an existing pipeline. But if you’re starting fresh or want strong Terraform-native features, it’s not the path of least resistance.

Terraform Cloud

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If you’d rather not deal with setting up pipelines at all, Terraform Cloud offers an official, fully managed path. Built by HashiCorp, it’s the reference implementation for Terraform automation - tightly aligned with the CLI, registry, providers, and state model you already use.

Terraform Cloud abstracts away the pipeline. You push code to Git, and it handles init, plan, and apply via workspaces. It stores remote state, secures variables, runs policies, and provides a clean UI for managing everything - no YAML required.

Upsides

Built-in Terraform intelligence: Designed from the ground up for Terraform: version management, remote state, backend locking, and workspace separation are all handled natively.
Out-of-the-box VCS integration: Connects to GitHub, GitLab, Bitbucket, and others to trigger runs directly from pull requests and commits.
Policy-as-code with Sentinel: Enforce fine-grained guardrails (e.g., require encryption, block public access, ensure tags) using HashiCorp’s own policy engine.
Enterprise-grade security and governance: Offers variable scoping, granular RBAC, SSO integration, audit logging, and drift detection - especially valuable in regulated environments.

Downsides

Cost scales quickly: The free tier covers up to 500 resources per month, but many key features like drift detection and advanced policy enforcement are locked behind paid plans. Pricing starts at $0.10 per resource/month for the Standard plan, $0.47 for Plus, and $0.99 for Premium, which can add up fast in large environments.
Less customizable pipelines: Great for standard Terraform flows, but rigid if you need non-standard workflows, extra orchestration, or integration with tools outside HashiCorp’s ecosystem.
Sentinel learning curve: While powerful, Sentinel uses its own DSL - teams may face a ramp-up before enforcing complex policies.

Terraform Cloud is ideal when you want a zero-hassle Terraform experience with robust governance and are fine working within HashiCorp’s workflow model. It shines for larger orgs that prioritize compliance, auditability, and control, and don’t want to roll their own solution.

Each of these tools brings its own tradeoffs, from flexibility and control to simplicity and scale, and the right choice depends on your infrastructure setup, how your team operates, and how much overhead you're willing to take on.

CICD Tools Comparison For Terraform

Now, we’ve walked through how each CI/CD platform approaches Terraform workflows - from general-purpose automation tools like GitHub Actions to purpose-built options like Terraform Cloud. Now it’s time to compare them head-to-head.

This isn’t about feature checklists for marketing slides. It’s about operational fit: how each tool supports (or complicates) core parts of a Terraform-based workflow. The goal here is to help you cut through the noise and figure out what actually matters for your team - whether you’re managing a single environment or coordinating dozens across cloud accounts.

Here’s how the six tools stack up across the attributes that shape real-world infrastructure work:

✅ = Supported natively or works well out of the box
🔶 = Supported with some effort or partial implementation
❌ = Not supported or requires significant external tooling

Terrateam

Terraform Command Support: ✅ Native plan/apply, built-in to PR flow
Secrets Handling: ✅ OIDC-based auth, no static secrets
GitOps Readiness: ✅ Native PR-based workflow
Policy-as-Code Support: ✅ OPA support (Conftest/Gatekeeper)
Drift Detection: ✅ Built-in, automatic
Maintenance Overhead: ✅ No pipeline code, minimal upkeep
Best Suited For: GitHub teams needing purpose-built Terraform automation
Cost Considerations: ✅ Free & open source, optional SaaS
Modular Reusability: ✅ Module-aware config with automatic discovery and reuse support
Cloud Platform Bias: ✅ Cloud-agnostic

GitHub Actions

Terraform Command Support: ✅ Shell steps or actions; flexible
Secrets Handling: 🔶 Basic repo/org-level secrets
GitOps Readiness: ✅ PR triggers and comment bots possible
Policy-as-Code Support: ❌ Requires integration (OPA or checks)
Drift Detection: ❌ None built-in
Maintenance Overhead: 🔶 Low at first, grows with scale
Best Suited For: GitHub-centric teams needing flexibility
Cost Considerations: ✅ Free tier available
Modular Reusability: ✅ Composite actions for shared workflows
Cloud Platform Bias: ✅ Cloud-agnostic

GitLab CI/CD

Terraform Command Support: ✅ Jobs in .gitlab-ci.yml
Secrets Handling: ✅ Scoped CI variables & secret management
GitOps Readiness: ✅ MR-based pipelines, approvals supported
Policy-as-Code Support: ❌ External tools needed
Drift Detection: ❌ None built-in
Maintenance Overhead: 🔶 Moderate; YAML config can get complex
Best Suited For: GitLab users wanting all-in-one DevOps
Cost Considerations: ✅ Free/self-hosted option available
Modular Reusability: ✅ Includes/templates in .gitlab-ci.yml
Cloud Platform Bias: ✅ Cloud-agnostic

Azure DevOps

Terraform Command Support: ✅ Inline scripts or Terraform task
Secrets Handling: ✅ Azure Key Vault integration
GitOps Readiness: ✅ Approvals via environment gates
Policy-as-Code Support: 🔶 Possible with custom pipeline steps
Drift Detection: ❌ None built-in
Maintenance Overhead: 🔶 Higher setup; low ongoing effort
Best Suited For: Azure-native orgs with enterprise needs
Cost Considerations: ✅ Included in Azure plans
Modular Reusability: ✅ YAML templates and task reuse
Cloud Platform Bias: ❌ Strong Azure bias

Atlantis

Terraform Command Support: ✅ Native plan/apply via PR events
Secrets Handling: ❌ Needs external secrets management
GitOps Readiness: ✅ Native GitOps via PR comments
Policy-as-Code Support: ❌ No built-in policy engine
Drift Detection: ❌ None built-in
Maintenance Overhead: ✅ Lightweight for small setups
Best Suited For: GitOps-focused teams, no extra CI
Cost Considerations: ✅ Free & open source
Modular Reusability: 🔶 Limited, mostly per-repo
Cloud Platform Bias: ✅ Cloud-agnostic

Jenkins

Terraform Command Support: ✅ Fully manual via shell or plugins
Secrets Handling: 🔶 Manual via plugins/env vars
GitOps Readiness: 🔶 Requires custom scripting/setup
Policy-as-Code Support: ❌ Fully manual
Drift Detection: ❌ None built-in
Maintenance Overhead: ❌ High (agents, plugins, infra upkeep)
Best Suited For: Legacy/hybrid orgs with Jenkins experience
Cost Considerations: ✅ Free & open source
Modular Reusability: ✅ Shared libraries and scripted pipelines
Cloud Platform Bias: ✅ Cloud-agnostic

Terraform Cloud

Terraform Command Support: ✅ Native support for init, plan, apply
Secrets Handling: ✅ Secure variable storage with RBAC
GitOps Readiness: ✅ Git-triggered runs and PR workflows
Policy-as-Code Support: ✅ Sentinel (built-in policy engine)
Drift Detection: ✅ Native drift detection (paid tier)
Maintenance Overhead: ✅ Fully managed SaaS
Best Suited For: Compliance-focused orgs needing SaaS
Cost Considerations: ❌ Paid tiers for full feature set
Modular Reusability: 🔶 Standardized workflows, limited extensibility
Cloud Platform Bias: ✅ Cloud-agnostic (HashiCorp ecosystem)

Matching CI/CD Tools to Your Team Size

Now that we’ve compared these tools across Terraform-specific capabilities, let’s look at how they stack up based on team size. The right choice isn’t just about features, it also depends on how many engineers are collaborating, how much time you can spend maintaining CI pipelines, and how complex your infrastructure setup really is.

Team Size	Recommended Tools	Why It Works
1–3 engineers	Terrateam, Atlantis	Fast setup, GitOps-native, no custom CI logic, low maintenance
4–10 engineers	Terrateam, GitHub Actions, GitLab CI, Terraform Cloud (Standard)	Adds support for approvals, policies, and secure secrets early in growth
11–30 engineers	Terrateam, Azure DevOps, Terraform Cloud (Plus)	Supports environment separation, RBAC, and more formalized workflows
30+ engineers	Terrateam, Terraform Cloud (Premium), Jenkins (if legacy)	Enterprise-level control, auditability, multi-team scaling, and compliance needs

So... Which CI/CD Tool Is Best for Terraform in 2025?

If you just take a look at the comparison table above - covering Terraform command support, secrets handling, GitOps readiness, policy enforcement, drift detection, and more - one pattern is clear: Terrateam is the only tool that checks every box.

It combines deep Terraform awareness with a native GitHub PR experience, low maintenance, strong policy-as-code support, and zero-pipeline configuration. Whether you’re a small team or running infrastructure at scale, Terrateam keeps your workflows clean, auditable, and scalable, without bolting together plugins or YAML templates.

For GitHub-centric teams, it’s a no-brainer. For everyone else, it’s worth a serious look.

In short, Terrateam is the best CI/CD solution for Terraform workflows in 2025.

Frequently Asked Questions

Which CI/CD tool is most popular?

GitHub Actions is currently the most widely adopted CI/CD tool, especially among teams using GitHub for source control.

How do I choose a CI/CD tool?

Pick the tool that integrates best with your existing stack, supports your infrastructure provider, fits your team’s workflow (e.g., GitOps, enterprise controls), and minimizes setup and maintenance.

What are the top DevOps tools for infrastructure automation in 2025?

Leading tools include Terraform, Terragrunt, Pulumi, Ansible, Spacelift, Terraform Cloud, and GitHub Actions + Terrateam.

How can I extend GitHub Actions to better support Terraform workflows?

Use purpose-built actions (e.g., hashicorp/setup-terraform) and layer in a Terraform-specific tool like Terrateam to handle drift detection, policy-as-code, secrets management, and safe apply workflows.

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