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Atlantis

By the Atlantis open-source project

IntermediateTool4.4K learners

Atlantis is an open-source, self-hosted tool that automates Terraform plan and apply workflows through comments on pull requests, letting teams review and approve infrastructure changes using the same Git-based review process they use for…

#Atlantis#DevOps#Tool#Intermediate#Spacelift#Env0#Terraform#TerraformCloud#SoftwareDelivery#Glossary#SkillVeris

Definition

Atlantis is an open-source, self-hosted tool that automates Terraform plan and apply workflows through comments on pull requests, letting teams review and approve infrastructure changes using the same Git-based review process they use for application code. It runs as a service that listens for pull request webhooks, executes Terraform commands in response to comments, and posts the results back to the pull request for review before an apply is triggered. DevOps teams use it to add GitOps-style guardrails to Terraform without adopting a paid platform.

Overview

Atlantis was created to solve a common Terraform workflow problem: running `terraform plan` and `terraform apply` locally means a reviewer cannot easily see the exact plan output that will be applied, and coordinating who runs apply and when is often handled informally through chat messages or tribal knowledge. Atlantis moves that workflow into the pull request itself, where the plan output is visible to every reviewer alongside the code diff that produced it. Mechanically, Atlantis runs as a self-hosted server connected to a webhook from a Git hosting platform such as GitHub, GitLab, or Bitbucket. When a pull request touching Terraform code is opened, Atlantis automatically runs `terraform plan` and posts the output as a comment; reviewers examine both the code change and the plan, and once satisfied, a team member comments `atlantis apply` to trigger the actual apply, with the pull request serving as an audit trail of who approved what and when. Atlantis supports locking so that only one plan or apply runs against a given Terraform working directory at a time, preventing concurrent changes from corrupting state. Compared to managed platforms like Spacelift or env0, Atlantis is free, open-source, and self-hosted, giving teams full control over where it runs and no per-seat licensing cost, but it also means the team is responsible for deploying, scaling, and securing the Atlantis server themselves, and it lacks the built-in policy engines, drift detection, and cost estimation those commercial platforms provide out of the box. Atlantis is deliberately narrower in scope, focused specifically on the plan-comment-apply loop around pull requests. In practice, Atlantis is popular with teams that already have strong DevOps capability and want GitOps-style Terraform review without paying for a managed platform, often layering custom policy checks via `conftest` or Open Policy Agent as a pre-apply hook themselves. It is commonly deployed as a small internal service reachable from the Git provider's webhook infrastructure, sometimes on Kubernetes alongside other DevOps tooling. Limitations include the operational burden of running and securing the Atlantis server, since it needs credentials to apply infrastructure changes and must be reachable by the Git provider's webhooks, and the lack of built-in enterprise features like formal policy engines or automatic environment expiration found in Spacelift or env0. Teams wanting those features without building them internally typically choose a managed platform instead. Atlantis configuration lives in a repository-level file that defines which directories map to which Terraform workspaces and what commands run for each, giving teams fine-grained control over multi-project repositories without needing a separate configuration UI. Because it is just a server process, teams can also run multiple Atlantis instances for different environments or trust boundaries, which is a common pattern for separating production infrastructure changes from lower environments.

Key Features

  • Runs Terraform plan and apply in response to pull request comments
  • Posts plan output directly into the pull request for review
  • Locks Terraform working directories to prevent concurrent runs
  • Integrates with GitHub, GitLab, and Bitbucket webhooks
  • Is free and open-source with no per-seat licensing
  • Requires self-hosting and operational management by the team
  • Supports custom pre-apply policy checks via external tools
  • Provides an auditable trail of approvals within pull requests

Use Cases

Reviewing Terraform plan output within pull requests
Gating infrastructure applies behind PR approval comments
Preventing concurrent Terraform runs with working directory locks
Adding GitOps-style review to an existing Terraform workflow
Running self-hosted Terraform automation without a paid platform
Separating production and lower-environment Terraform pipelines

Alternatives

Spacelift · Spacelift, Inc.Env0 · env0, Inc.Terraform Cloud · HashiCorpDigger · Digger open-source project

Frequently Asked Questions

Frequently Asked Questions

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Does SkillVeris have a tech blog, and what does it cover?
Yes, the SkillVeris blog has over 500 articles covering AI and machine learning, programming, web development, DevOps, cloud, security, databases and career guidance. Articles are practical and answer-first, and many use the Learn Through Hobbies approach, teaching technical concepts through cricket, music, gaming or cooking analogies. Everything is free to read.
What is the SkillVeris tech glossary and how big is it?
The SkillVeris glossary is a free reference of roughly 2,000-plus technology terms, each with a clear plain-language definition. It spans AI, programming, web, DevOps, cloud, security and database vocabulary, so whenever a lesson, article or job description uses jargon you do not recognise, the glossary gives you a fast, reliable answer.
Are the developer cheat sheets on SkillVeris free to download?
The cheat sheets are completely free to use, like everything else on SkillVeris. Each sheet condenses a language or tool into its essential syntax, commands and patterns for quick reference while coding. They are designed for rapid lookup during real work, complementing the deeper explanations found in study notes and courses.
Which programming references and cheat sheets are available?
Cheat sheets cover the platform's main domains, including programming languages, AI and ML tooling, web development, DevOps, cloud, security and databases, matching the topics of the 37 live courses. Each sheet lists related reading links and hashtags, so you can jump from a quick reference into fuller study notes or blog articles.
How do I find the meaning of a technical term quickly?
Search the SkillVeris glossary, which holds around 2,000-plus terms with concise, plain-language definitions. Each entry gets to the point in its first sentence, then links to related reading like blog posts or study notes for deeper context. It is faster and more consistent than sifting through scattered search results.
Is the SkillVeris blog good for beginners learning to code?
Yes, many blog articles are written specifically for beginners, and the Learn Through Hobbies style makes them unusually approachable: you might learn Python concepts through cricket or understand APIs through cooking. With 500-plus articles across skill levels, beginners can start with fundamentals and keep reading as they advance, entirely free.
Can cheat sheets replace full courses for learning a language?
No, cheat sheets are references, not teaching tools; they assume you already understand the concepts and just need syntax or commands fast. To actually learn a language, take a structured SkillVeris course with its 24–40 lessons and assessments, then keep the cheat sheet beside you while practising in Code Lab.
How often are new blog articles published on SkillVeris?
The blog grows regularly and already exceeds 500 articles, with new posts added as courses launch and technologies evolve. Topics track the platform's catalogue across AI, programming, web development, DevOps, cloud and security, so checking the Blog section periodically surfaces fresh tutorials, explainers and career-focused pieces, all free to read.
Does the glossary cover AI and machine learning terms?
Yes, AI and machine learning vocabulary is a major part of the roughly 2,000-plus term glossary, covering everything from foundational terms to modern concepts around LLMs, RAG and MLOps. Definitions are plain-language and answer-first, which helps when dense AI papers or course lessons throw unfamiliar jargon at you.
Are there cheat sheets for interview preparation?
Cheat sheets work well as interview-day refreshers because they compress syntax, commands and key concepts into scannable references. For dedicated preparation, combine them with the SkillVeris interview questions feature, which includes readiness scoring, plus study notes for depth. Reviewing a relevant cheat sheet just before an interview steadies recall under pressure.
Can I read the tech blog without signing up?
Yes, the blog is freely readable, and SkillVeris never charges for content. All 500-plus articles are open, covering tutorials, concept explainers and career advice. Creating a free account adds value elsewhere on the platform, like course progress tracking and certificates, but reading the blog requires no commitment at all.
How is the SkillVeris glossary different from Wikipedia?
The glossary is purpose-built for learners: definitions are short, plain-language and answer-first, sized for a quick lookup mid-lesson rather than a deep encyclopedic read. Entries also cross-link to related SkillVeris study notes, blog posts and courses, so a definition becomes a doorway into structured learning instead of a dead end.
Do blog articles use the Learn Through Hobbies method?
Many blog articles teach technical topics through hobby analogies, a hallmark of the SkillVeris blog, so you will find articles explaining programming through cricket, machine learning through music, or system design through cooking. The analogy is the teaching device; the article still delivers the real technical concept underneath.
Where can I find quick programming references while coding?
Open the SkillVeris cheat sheets, which are built exactly for that moment: compact, scannable references for syntax, commands and common patterns across languages and tools. Keep the relevant sheet in a browser tab while you work in Code Lab or your own editor, and dip into the glossary for terminology.
Is there a glossary entry for terms I meet in job descriptions?
Very likely yes, with roughly 2,000-plus terms across AI, programming, web, DevOps, cloud, security and databases, the glossary covers most jargon that appears in tech job descriptions. Decoding a listing this way helps you judge role fit honestly and prepares you to discuss those terms in interviews.
Are the blog articles written for the Indian tech audience?
The blog serves Indian learners plus a worldwide audience. Content stays globally relevant while acknowledging realities that matter in India, such as free access being essential for students and freshers, and career guidance that connects naturally to the SkillVeris jobs portal, which aggregates roles across India, UK, USA, Germany and Remote.
Can I suggest a topic for the blog or glossary?
SkillVeris content grows in response to what learners need, so feedback is welcome through the platform's support channels. If a term is missing from the glossary or a topic deserves an article, telling the team helps prioritise it. Meanwhile, the AI Mentor can answer the question immediately, 24/7, at any depth.
Do cheat sheets and glossary entries link to deeper learning?
Yes, every cheat sheet and glossary entry carries related reading links into study notes, blog articles and courses, plus concept hashtags for discovering similar content. This cross-linking means a thirty-second lookup can smoothly become a structured learning session whenever you decide you want more than a quick answer.
What makes SkillVeris programming references trustworthy?
The references are written to strict internal quality standards, kept consistent with the platform's 37 live courses, and never padded with invented statistics or hype. Definitions and cheat sheets are reviewed against the same content contracts that govern courses, and the answer-first style makes any inaccuracy easy to spot and correct.
How do the blog, glossary and cheat sheets fit into my learning routine?
Use them as satellites around your main course: read blog articles for context and motivation, hit the glossary the instant jargon appears, and keep cheat sheets open while coding. Together with study notes, Code Lab and the 24/7 AI Mentor, they turn passive reading into a complete, free learning system.

What Learners Say

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