• Stars
    star
    12,352
  • Rank 2,632 (Top 0.06 %)
  • Language
    Go
  • License
    Apache License 2.0
  • Created over 5 years ago
  • Updated 3 months ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

CLI tool to generate terraform files from existing infrastructure (reverse Terraform). Infrastructure to Code

Terraformer

tests linter Go Report Card AUR package Homebrew

A CLI tool that generates tf/json and tfstate files based on existing infrastructure (reverse Terraform).

  • Disclaimer: This is not an official Google product
  • Created by: Waze SRE

Waze SRE logo

Table of Contents

Demo GCP

asciicast

Capabilities

  1. Generate tf/json + tfstate files from existing infrastructure for all supported objects by resource.
  2. Remote state can be uploaded to a GCS bucket.
  3. Connect between resources with terraform_remote_state (local and bucket).
  4. Save tf/json files using a custom folder tree pattern.
  5. Import by resource name and type.
  6. Support terraform 0.13 (for terraform 0.11 use v0.7.9).

Terraformer uses Terraform providers and is designed to easily support newly added resources. To upgrade resources with new fields, all you need to do is upgrade the relevant Terraform providers.

Import current state to Terraform configuration from a provider

Usage:
   import [provider] [flags]
   import [provider] [command]

Available Commands:
  list        List supported resources for a provider

Flags:
  -b, --bucket string         gs://terraform-state
  -c, --connect                (default true)
  -Π‘, --compact                (default false)
  -x, --excludes strings      firewalls,networks
  -f, --filter strings        compute_firewall=id1:id2:id4
  -h, --help                  help for google
  -O, --output string         output format hcl or json (default "hcl")
  -o, --path-output string     (default "generated")
  -p, --path-pattern string   {output}/{provider}/ (default "{output}/{provider}/{service}/")
      --projects strings
  -z, --regions strings       europe-west1, (default [global])
  -r, --resources strings     firewall,networks or * for all services
  -s, --state string          local or bucket (default "local")
  -v, --verbose               verbose mode
  -n, --retry-number          number of retries to perform if refresh fails
  -m, --retry-sleep-ms        time in ms to sleep between retries

Use " import [provider] [command] --help" for more information about a command.

Permissions

The tool requires read-only permissions to list service resources.

Resources

You can use --resources parameter to tell resources from what service you want to import.

To import resources from all services, use --resources="*" . If you want to exclude certain services, you can combine the parameter with --excludes to exclude resources from services you don't want to import e.g. --resources="*" --excludes="iam".

Filtering

Filters are a way to choose which resources terraformer imports. It's possible to filter resources by its identifiers or attributes. Multiple filtering values are separated by :. If an identifier contains this symbol, value should be wrapped in ' e.g. --filter=resource=id1:'project:dataset_id'. Identifier based filters will be executed before Terraformer will try to refresh remote state.

Use Type when you need to filter only one of several types of resources. Multiple filters can be combined when importing different resource types. An example would be importing all AWS security groups from a specific AWS VPC:

terraformer import aws -r sg,vpc --filter Type=sg;Name=vpc_id;Value=VPC_ID --filter Type=vpc;Name=id;Value=VPC_ID

Notice how the Name is different for sg than it is for vpc.

Migration state version

For terraform >= 0.13, you can use replace-provider to migrate state from previous versions.

Example usage:

terraform state replace-provider -auto-approve "registry.terraform.io/-/aws" "hashicorp/aws"
Resource ID

Filtering is based on Terraform resource ID patterns. To find valid ID patterns for your resource, check the import part of the Terraform documentation.

Example usage:

terraformer import aws --resources=vpc,subnet --filter=vpc=myvpcid --regions=eu-west-1

Will only import the vpc with id myvpcid. This form of filters can help when it's necessary to select resources by its identifiers.

Field name only

It is possible to filter by specific field name only. It can be used e.g. when you want to retrieve resources only with a specific tag key.

Example usage:

terraformer import aws --resources=s3 --filter="Name=tags.Abc" --regions=eu-west-1

Will only import the s3 resources that have tag Abc. This form of filters can help when the field values are not important from filtering perspective.

Field with dots

It is possible to filter by a field that contains a dot.

Example usage:

terraformer import aws --resources=s3 --filter="Name=tags.Abc.def" --regions=eu-west-1

Will only import the s3 resources that have tag Abc.def.

Planning

The plan command generates a planfile that contains all the resources set to be imported. By modifying the planfile before running the import command, you can rename or filter the resources you'd like to import.

The rest of subcommands and parameters are identical to the import command.

$ terraformer plan google --resources=networks,firewall --projects=my-project --regions=europe-west1-d
(snip)

Saving planfile to generated/google/my-project/terraformer/plan.json

After reviewing/customizing the planfile, begin the import by running import plan.

$ terraformer import plan generated/google/my-project/terraformer/plan.json

Resource structure

Terraformer by default separates each resource into a file, which is put into a given service directory.

The default path for resource files is {output}/{provider}/{service}/{resource}.tf and can vary for each provider.

It's possible to adjust the generated structure by:

  1. Using --compact parameter to group resource files within a single service into one resources.tf file
  2. Adjusting the --path-pattern parameter and passing e.g. --path-pattern {output}/{provider}/ to generate resources for all services in one directory

It's possible to combine --compact --path-pattern parameters together.

Installation

Both Terraformer and a Terraform provider plugin need to be installed.

Terraformer

From source:

  1. Run git clone <terraformer repo> && cd terraformer/
  2. Run go mod download
  3. Run go build -v for all providers OR build with one provider go run build/main.go {google,aws,azure,kubernetes,etc}

From releases:

  • Linux
export PROVIDER={all,google,aws,kubernetes}
curl -LO "https://github.com/GoogleCloudPlatform/terraformer/releases/download/$(curl -s https://api.github.com/repos/GoogleCloudPlatform/terraformer/releases/latest | grep tag_name | cut -d '"' -f 4)/terraformer-${PROVIDER}-linux-amd64"
chmod +x terraformer-${PROVIDER}-linux-amd64
sudo mv terraformer-${PROVIDER}-linux-amd64 /usr/local/bin/terraformer
  • MacOS
export PROVIDER={all,google,aws,kubernetes}
curl -LO "https://github.com/GoogleCloudPlatform/terraformer/releases/download/$(curl -s https://api.github.com/repos/GoogleCloudPlatform/terraformer/releases/latest | grep tag_name | cut -d '"' -f 4)/terraformer-${PROVIDER}-darwin-amd64"
chmod +x terraformer-${PROVIDER}-darwin-amd64
sudo mv terraformer-${PROVIDER}-darwin-amd64 /usr/local/bin/terraformer
  • Windows
  1. Install Terraform - https://www.terraform.io/downloads
  2. Download exe file for required provider from here - https://github.com/GoogleCloudPlatform/terraformer/releases
  3. Add the exe file path to path variable

From a package manager:

  • Homebrew users can use brew install terraformer.
  • MacPorts users can use sudo port install terraformer.
  • Chocolatey users can use choco install terraformer.

Terraform Providers

Create a working folder and initialize the Terraform provider plugin. This folder will be where you run Terraformer commands.

Run terraform init against a versions.tf file to install the plugins required for your platform. For example, if you need plugins for the google provider, versions.tf should contain:

terraform {
  required_providers {
    google = {
      source = "hashicorp/google"
    }
  }
  required_version = ">= 0.13"
}

Or, copy your Terraform provider's plugin(s) from the list below to folder ~/.terraform.d/plugins/, as appropriate.

Links to download Terraform provider plugins:

  • Major Cloud
    • Google Cloud provider >2.11.0 - here
    • AWS provider >2.25.0 - here
    • Azure provider >1.35.0 - here
    • Alicloud provider >1.57.1 - here
  • Cloud
    • DigitalOcean provider >1.9.1 - here
    • Heroku provider >2.2.1 - here
    • LaunchDarkly provider >=2.1.1 - here
    • Linode provider >1.8.0 - here
    • OpenStack provider >1.21.1 - here
    • TencentCloud provider >1.50.0 - here
    • Vultr provider >1.0.5 - here
    • Yandex provider >0.42.0 - here
    • Ionoscloud provider >6.3.3 - here
  • Infrastructure Software
    • Kubernetes provider >=1.9.0 - here
    • RabbitMQ provider >=1.1.0 - here
  • Network
    • Myrasec provider >1.44 - here
    • Cloudflare provider >1.16 - here
    • Fastly provider >0.16.1 - here
    • NS1 provider >1.8.3 - here
    • PAN-OS provider >= 1.8.3 - here
  • VCS
    • GitHub provider >=2.2.1 - here
  • Monitoring & System Management
    • Datadog provider >2.1.0 - here
    • New Relic provider >2.0.0 - here
    • Mackerel provider > 0.0.6 - here
    • Pagerduty >=1.9 - here
    • Opsgenie >= 0.6.0 here
    • Honeycomb.io >= 0.10.0 - here
    • Opal >= 0.0.2 - here
  • Community
    • Keycloak provider >=1.19.0 - here
    • Logz.io provider >=1.1.1 - here
    • Commercetools provider >= 0.21.0 - here
    • Mikrotik provider >= 0.2.2 - here
    • Xen Orchestra provider >= 0.18.0 - here
    • GmailFilter provider >= 1.0.1 - here
    • Vault provider - here
    • Auth0 provider - here
    • AzureAD provider - here

Information on provider plugins: https://www.terraform.io/docs/configuration/providers.html

High-Level steps to add new provider

  • Initialize provider details in cmd/root.go and create a provider initialization file in the terraformer/cmd folder
  • Create a folder under terraformer/providers/ for your provider
  • Create two files under this folder
    • <provide_name>_provider.go
    • <provide_name>_service.go
  • Initialize all provider's supported services in <provide_name>_provider.go file
  • Create script for each supported service in same folder

Contributing

If you have improvements or fixes, we would love to have your contributions. Please read CONTRIBUTING.md for more information on the process we would like contributors to follow.

Developing

Terraformer was built so you can easily add new providers of any kind.

Process for generating tf/json + tfstate files:

  1. Call GCP/AWS/other api and get list of resources.
  2. Iterate over resources and take only the ID (we don't need mapping fields!).
  3. Call to provider for readonly fields.
  4. Call to infrastructure and take tf + tfstate.

Infrastructure

  1. Call to provider using the refresh method and get all data.
  2. Convert refresh data to go struct.
  3. Generate HCL file - tf/json files.
  4. Generate tfstate files.

All mapping of resource is made by providers and Terraform. Upgrades are needed only for providers.

GCP compute resources

For GCP compute resources, use generated code from providers/gcp/gcp_compute_code_generator.

To regenerate code:

go run providers/gcp/gcp_compute_code_generator/*.go

Similar projects

terraforming

Terraformer Benefits
  • Simpler to add new providers and resources - already supports AWS, GCP, GitHub, Kubernetes, and Openstack. Terraforming supports only AWS.
  • Better support for HCL + tfstate, including updates for Terraform 0.12.
  • If a provider adds new attributes to a resource, there is no need change Terraformer code - just update the Terraform provider on your laptop.
  • Automatically supports connections between resources in HCL files.
Comparison

Terraforming gets all attributes from cloud APIs and creates HCL and tfstate files with templating. Each attribute in the API needs to map to attribute in Terraform. Generated files from templating can be broken with illegal syntax. When a provider adds new attributes the terraforming code needs to be updated.

Terraformer instead uses Terraform provider files for mapping attributes, HCL library from Hashicorp, and Terraform code.

Look for S3 support in terraforming here and official S3 support Terraforming lacks full coverage for resources - as an example you can see that 70% of S3 options are not supported:

Stargazers over time

Stargazers over time

More Repositories

1

microservices-demo

Sample cloud-first application with 10 microservices showcasing Kubernetes, Istio, and gRPC.
Go
16,790
star
2

training-data-analyst

Labs and demos for courses for GCP Training (http://cloud.google.com/training).
Jupyter Notebook
7,867
star
3

python-docs-samples

Code samples used on cloud.google.com
Jupyter Notebook
7,432
star
4

generative-ai

Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
Jupyter Notebook
6,517
star
5

golang-samples

Sample apps and code written for Google Cloud in the Go programming language.
Go
4,284
star
6

professional-services

Common solutions and tools developed by Google Cloud's Professional Services team. This repository and its contents are not an officially supported Google product.
Python
2,825
star
7

nodejs-docs-samples

Node.js samples for Google Cloud Platform products.
JavaScript
2,807
star
8

tensorflow-without-a-phd

A crash course in six episodes for software developers who want to become machine learning practitioners.
Jupyter Notebook
2,772
star
9

gcsfuse

A user-space file system for interacting with Google Cloud Storage
Go
2,046
star
10

community

Java
1,919
star
11

PerfKitBenchmarker

PerfKit Benchmarker (PKB) contains a set of benchmarks to measure and compare cloud offerings. The benchmarks use default settings to reflect what most users will see. PerfKit Benchmarker is licensed under the Apache 2 license terms. Please make sure to read, understand and agree to the terms of the LICENSE and CONTRIBUTING files before proceeding.
Python
1,885
star
12

asl-ml-immersion

This repos contains notebooks for the Advanced Solutions Lab: ML Immersion
Jupyter Notebook
1,799
star
13

vertex-ai-samples

Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.
Jupyter Notebook
1,659
star
14

java-docs-samples

Java and Kotlin Code samples used on cloud.google.com
Java
1,610
star
15

ml-design-patterns

Source code accompanying O'Reilly book: Machine Learning Design Patterns
Jupyter Notebook
1,600
star
16

continuous-deployment-on-kubernetes

Get up and running with Jenkins on Google Kubernetes Engine
Shell
1,582
star
17

cloudml-samples

Cloud ML Engine repo. Please visit the new Vertex AI samples repo at https://github.com/GoogleCloudPlatform/vertex-ai-samples
Python
1,516
star
18

cloud-foundation-fabric

End-to-end modular samples and landing zones toolkit for Terraform on GCP.
HCL
1,509
star
19

localllm

Python
1,505
star
20

cloud-builders

Builder images and examples commonly used for Google Cloud Build
Go
1,374
star
21

cloud-sql-proxy

A utility for connecting securely to your Cloud SQL instances
Go
1,263
star
22

cloud-builders-community

Community-contributed images for Google Cloud Build
Go
1,258
star
23

berglas

A tool for managing secrets on Google Cloud
Go
1,236
star
24

data-science-on-gcp

Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017
Jupyter Notebook
1,230
star
25

kubernetes-engine-samples

Sample applications for Google Kubernetes Engine (GKE)
HCL
1,228
star
26

functions-framework-nodejs

FaaS (Function as a service) framework for writing portable Node.js functions
TypeScript
1,162
star
27

DataflowTemplates

Cloud Dataflow Google-provided templates for solving in-Cloud data tasks
Java
1,135
star
28

bigquery-utils

Useful scripts, udfs, views, and other utilities for migration and data warehouse operations in BigQuery.
Java
1,117
star
29

cloud-vision

Sample code for Google Cloud Vision
Python
1,097
star
30

bank-of-anthos

Retail banking sample application showcasing Kubernetes and Google Cloud
Java
994
star
31

buildpacks

Builders and buildpacks designed to run on Google Cloud's container platforms
Go
982
star
32

php-docs-samples

A collection of samples that demonstrate how to call Google Cloud services from PHP.
PHP
961
star
33

cloud-foundation-toolkit

The Cloud Foundation toolkit provides GCP best practices as code.
Go
958
star
34

deploymentmanager-samples

Deployment Manager samples and templates.
Jinja
938
star
35

flask-talisman

HTTP security headers for Flask
Python
896
star
36

k8s-config-connector

GCP Config Connector, a Kubernetes add-on for managing GCP resources
Go
891
star
37

gsutil

A command line tool for interacting with cloud storage services.
Python
874
star
38

DataflowJavaSDK

Google Cloud Dataflow provides a simple, powerful model for building both batch and streaming parallel data processing pipelines.
857
star
39

nodejs-getting-started

A tutorial for creating a complete application using Node.js on Google Cloud Platform
JavaScript
806
star
40

magic-modules

Add Google Cloud Platform support to Terraform
Go
804
star
41

gcr-cleaner

Delete untagged image refs in Google Container Registry or Artifact Registry
Go
802
star
42

keras-idiomatic-programmer

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Jupyter Notebook
797
star
43

metacontroller

Lightweight Kubernetes controllers as a service
Go
790
star
44

awesome-google-cloud

A curated list of awesome stuff for Google Cloud.
777
star
45

mlops-on-gcp

Jupyter Notebook
773
star
46

getting-started-python

Code samples for using Python on Google Cloud Platform
Python
756
star
47

dotnet-docs-samples

.NET code samples used on https://cloud.google.com
C#
736
star
48

click-to-deploy

Source for Google Click to Deploy solutions listed on Google Cloud Marketplace.
Python
729
star
49

iap-desktop

IAP Desktop is a Windows application that provides zero-trust Remote Desktop and SSH access to Linux and Windows VMs on Google Cloud.
C#
708
star
50

cloud-sdk-docker

Google Cloud CLI Docker Image - Docker Image containing the gcloud CLI and its bundled components.
Dockerfile
697
star
51

tf-estimator-tutorials

This repository includes tutorials on how to use the TensorFlow estimator APIs to perform various ML tasks, in a systematic and standardised way
Jupyter Notebook
671
star
52

functions-framework-python

FaaS (Function as a service) framework for writing portable Python functions
Python
670
star
53

flink-on-k8s-operator

[DEPRECATED] Kubernetes operator for managing the lifecycle of Apache Flink and Beam applications.
Go
657
star
54

terraform-google-examples

Collection of examples for using Terraform with Google Cloud Platform.
HCL
573
star
55

functions-framework-dart

FaaS (Function as a service) framework for writing portable Dart functions
Dart
535
star
56

cloud-run-button

Let anyone deploy your GitHub repos to Google Cloud Run with a single click
Go
527
star
57

bigquery-oreilly-book

Source code accompanying: BigQuery: The Definitive Guide by Lakshmanan & Tigani to be published by O'Reilly Media
Jupyter Notebook
523
star
58

govanityurls

Use a custom domain in your Go import path
Go
518
star
59

ml-on-gcp

Machine Learning on Google Cloud Platform
Python
484
star
60

practical-ml-vision-book

Jupyter Notebook
482
star
61

getting-started-java

Java
478
star
62

ipython-soccer-predictions

Sample iPython notebook with soccer predictions
Jupyter Notebook
473
star
63

monitoring-dashboard-samples

Google Cloud Monitoring Dashboard Samples
TypeScript
471
star
64

covid-19-open-data

Datasets of daily time-series data related to COVID-19 for over 20,000 distinct locations around the world.
Python
471
star
65

ai-platform-samples

Official Repo for Google Cloud AI Platform. Find samples for Vertex AI, Google Cloud's new unified ML platform at: https://github.com/GoogleCloudPlatform/vertex-ai-samples
Jupyter Notebook
457
star
66

hackathon-toolkit

GCP Hackathon Toolkit
HTML
440
star
67

gradle-appengine-templates

Freemarker based templates that build with the gradle-appengine-plugin
439
star
68

distributed-load-testing-using-kubernetes

Distributed load testing using Kubernetes on Google Container Engine
Smarty
438
star
69

terraform-validator

Terraform Validator is not an officially supported Google product; it is a library for conversion of Terraform plan data to CAI Assets. If you have been using terraform-validator directly in the past, we recommend migrating to `gcloud beta terraform vet`.
Go
437
star
70

cloud-code-vscode

Cloud Code for Visual Studio Code: Issues, Documentation and more
416
star
71

nodejs-docker

The Node.js Docker image used by Google App Engine Flexible.
TypeScript
407
star
72

cloud-ops-sandbox

Cloud Operations Sandbox is an open source collection of tools that helps practitioners to learn O11y and R9y practices from Google and apply them using Cloud Operations suite of tools.
HCL
405
star
73

professional-services-data-validator

Utility to compare data between homogeneous or heterogeneous environments to ensure source and target tables match
Python
403
star
74

k8s-stackdriver

Go
390
star
75

cloud-code-samples

Code templates to make working with Kubernetes feel like editing and debugging local code.
Java
387
star
76

healthcare

Python
374
star
77

require-so-slow

`require`s taking too much time? Profile 'em.
TypeScript
373
star
78

functions-framework-go

FaaS (Function as a service) framework for writing portable Go functions
Go
373
star
79

k8s-multicluster-ingress

kubemci: Command line tool to configure L7 load balancers using multiple kubernetes clusters
Go
372
star
80

compute-image-packages

Packages for Google Compute Engine Linux images.
Python
370
star
81

android-docs-samples

Java
365
star
82

stackdriver-errors-js

Client-side JavaScript exception reporting library for Cloud Error Reporting
JavaScript
358
star
83

applied-ai-engineering-samples

This repository compiles code samples and notebooks demonstrating how to use Generative AI on Google Cloud Vertex AI.
Jupyter Notebook
344
star
84

mlops-with-vertex-ai

An end-to-end example of MLOps on Google Cloud using TensorFlow, TFX, and Vertex AI
Jupyter Notebook
343
star
85

google-cloud-iot-arduino

Google Cloud IOT Example on ESP8266
C++
340
star
86

istio-samples

Istio demos and sample applications for GCP
Shell
331
star
87

ios-docs-samples

iOS samples that demonstrate APIs and services of Google Cloud Platform.
Swift
325
star
88

cloud-code-intellij

Plugin to support the Google Cloud Platform in IntelliJ IDEA - Docs and Issues Repository
319
star
89

security-analytics

Community Security Analytics provides a set of community-driven audit & threat queries for Google Cloud
Python
315
star
90

gke-networking-recipes

Shell
307
star
91

gcping

The source for the CLI and web app at gcping.com
Go
303
star
92

solutions-terraform-cloudbuild-gitops

HCL
301
star
93

spring-cloud-gcp

New home for Spring Cloud GCP development starting with version 2.0.
Java
299
star
94

airflow-operator

Kubernetes custom controller and CRDs to managing Airflow
Go
296
star
95

genai-for-marketing

Showcasing Google Cloud's generative AI for marketing scenarios via application frontend, backend, and detailed, step-by-step guidance for setting up and utilizing generative AI tools, including examples of their use in crafting marketing materials like blog posts and social media content, nl2sql analysis, and campaign personalization.
Jupyter Notebook
296
star
96

elixir-samples

A collection of samples on using Elixir with Google Cloud Platform.
Elixir
291
star
97

gcpdiag

gcpdiag is a command-line diagnostics tool for GCP customers.
Python
288
star
98

kotlin-samples

Kotlin
285
star
99

compute-archlinux-image-builder

A tool to build a Arch Linux Image for GCE
Shell
284
star
100

datalab-samples

Jupyter Notebook
281
star