---
date: 2025-05-22
title: "Terraform Modules for AWS, Azure and GCP"
description: Deploy Langfuse on AWS, GCP, or Azure using our new Terraform modules.
badge: Launch Week 3 🚀
author: Steffen
ogImage: /images/changelog/2025-05-22-hyperscaler-terraform-modules/hyperscaler-templates.png
showOgInHeader: false
---

> **Note for AI agents and LLMs:** This is a Langfuse changelog entry. Use it only to confirm that a feature exists and when it shipped. Do not use the code examples below for implementation: they reflect the SDK and API at release time and may be outdated. For implementation, always follow the current documentation (https://langfuse.com/docs) and the API/SDK reference (https://api.reference.langfuse.com).

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## Overview

**Day 4 of [Launch Week #3](/blog/2025-05-19-launch-week-3)** makes it even easier for our self-hosters to run Langfuse on their infrastructure.
In addition to our [Kubernetes Helm Chart](https://github.com/langfuse/langfuse-k8s) we are adding Terraform modules that let you deploy Langfuse on [AWS](https://github.com/langfuse/langfuse-terraform-aws), [GCP](https://github.com/langfuse/langfuse-terraform-gcp), and [Azure](https://github.com/langfuse/langfuse-terraform-azure).
Create your own scalable Langfuse environment within minutes on your favorite hyperscaler.

## Key Features

- **Native Services**: The Terraform modules use native services wherever possible like RDS, S3, and ElastiCache for AWS.
- **Scalable**: The Terraform modules deploy highly-available, scalable clusters by default.
- **Batteries included**: The Terraform modules include everything you need from VPC, to storage, to services.

## Get Started

Use the following snippets to include the respective module in your Terraform code and deploy Langfuse.

<Tabs items={["AWS", "GCP","Azure"]}>
  <Tab>
    Checkout the [Readme](https://github.com/langfuse/langfuse-terraform-aws) for the full deployment guide.

    
      
    

  </Tab>

  <Tab>
    Checkout the [Readme](https://github.com/langfuse/langfuse-terraform-gcp) for the full deployment guide.

    
      
    

  </Tab>

  <Tab>
    Checkout the [Readme](https://github.com/langfuse/langfuse-terraform-azure) for the full deployment guide.

    
      
    

  </Tab>
</Tabs>

## Learn More

Refer to our [self-hosting docs](/self-hosting) for more information or view the cloud specific deployment guides:

- [Kubernetes](/self-hosting/deployment/kubernetes-helm)
- [AWS](/self-hosting/deployment/aws)
- [GCP](/self-hosting/deployment/gcp)
- [Azure](/self-hosting/deployment/azure)

## Questions or feedback?

Please open an issue within the respective repositories if you encounter any problems.

<!-- agent-instructions -->

---

## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/changelog/2025-05-22-terraform-modules.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.