---
slug: /1008/aws-cloudformation/
---
# Provision infrastructure with Dagger and AWS CloudFormation
In this guide, you will learn how to automatically [provision infrastructure](https://dzone.com/articles/infrastructure-provisioning-–) on AWS by integrating [Amazon Cloudformation](https://aws.amazon.com/cloudformation/) in your Dagger environment.
We will start with something simple: provisioning a new bucket on [Amazon S3](https://en.wikipedia.org/wiki/Amazon_S3). But Cloudformation can provision almost any AWS resource, and Dagger can integrate with the full Cloudformation API.
## Prerequisites
### Reminder
#### Guidelines
The provisioning strategy detailed below follows S3 best practices. However, to remain agnostic of your current AWS level, it profoundly relies on S3 and Cloudformation documentation.
#### Relays
The first thing to consider when developing a plan based on relays is to read their universe reference: it summarizes the expected inputs and their corresponding formats. [Here](../reference/aws/cloudformation.md) is the Cloudformation one.
## Initialize a Dagger Project and Environment
### (optional) Setup example app
You will need the local copy of the [Dagger examples repository](https://github.com/dagger/examples) used in previous guides
```shell
git clone https://github.com/dagger/examples
```
Make sure to run all commands from the todoapp directory:
```shell
cd examples/todoapp
```
### Organize your package
Let's create a new directory for our Cue package:
```shell
mkdir cloudformation
```
## Create a basic plan
Let's implement the Cloudformation template and convert it to a Cue definition for further flexibility.
### Setup the template and the environment
#### Setup the template
The idea here is to follow best practices in [S3 buckets](https://docs.aws.amazon.com/AmazonS3/latest/userguide/HostingWebsiteOnS3Setup.html) provisioning. Thankfully, the AWS documentation contains a working [Cloudformation template](https://docs.aws.amazon.com/fr_fr/AWSCloudFormation/latest/UserGuide/quickref-s3.html#scenario-s3-bucket-website) that fits 95% of our needs.
##### 1. Tweaking the template: output bucket name only
Create a file named `template.cue` and add the following configuration to it.
```cue file=./tests/cloudformation/template.cue title="todoapp/cloudformation/template.cue"
```
##### 2. Cloudformation relay
As our plan relies on [Cloudformation's relay](../reference/aws/cloudformation.md), let's dissect the expected inputs by gradually incorporating them into our plan.
```shell
dagger doc alpha.dagger.io/aws/cloudformation
# Inputs:
# config.region string AWS region
# config.accessKey dagger.#Secret AWS access key
# config.secretKey dagger.#Secret AWS secret key
# source string Source is the Cloudformation template (JSON/YAML…
# stackName string Stackname is the cloudformation stack
# parameters struct Stack parameters
# onFailure *"DO_NOTHING" | "ROLLBACK" | "DELETE" Behavior when failure to create/update the Stack
# timeout *10 | >=0 & int Maximum waiting time until stack creation/update…
# neverUpdate *false | true Never update the stack if already exists
```
###### 1. General insights
As seen above in the documentation, values starting with `*` are default values. However, as a plan developer, we may need to add default values to inputs from relays without one: Cue gives you this flexibility.
###### 2. The config value
The config values are all part of the `aws` relay. Regarding this package, as you can see above, five of the required inputs miss default options (`parameters` field is optional):
> - _config.region_
> - _config.accessKey_
> - _config.secretKey_
> - _source_
> - _stackName_
Let's implement the first step, use the `aws.#Config` relay, and request its first inputs: the region to deploy and the AWS credentials.
```cue file=./tests/cloudformation/source-begin.cue title="todoapp/cloudformation/source.cue"
```
This defines:
- `awsConfig`: AWS CLI Configuration step using the package `alpha.dagger.io/aws`. It takes three user inputs: a `region`, an `accessKey`, and a `secretKey`
#### Setup the environment
##### 1. Create a new environment
Let's create a project:
```shell
dagger init
```
Let's create an environment to run it:
```shell
dagger new 'cloudformation' -p ./cloudformation
```
##### 2. Check plan
_Pro tips_: To check whether it worked or not, these three commands might help
```shell
dagger input list -e cloudformation # List our personal plan's inputs
# Input Value Set by user Description
# awsConfig.region string false AWS region
# awsConfig.accessKey dagger.#Secret false AWS access key
# awsConfig.secretKey dagger.#Secret false AWS secret key
dagger query -e cloudformation # Query values / inspect default values (Instrumental in case of conflict)
# {}
dagger up -e cloudformation # Try to run the plan. As expected, we encounter a failure because some user inputs haven't been set
# 4:11PM ERR system | required input is missing input=awsConfig.region
# 4:11PM ERR system | required input is missing input=awsConfig.accessKey
# 4:11PM ERR system | required input is missing input=awsConfig.secretKey
# 4:11PM FTL system | some required inputs are not set, please re-run with `--force` if you think it's a mistake missing=0s
```
#### Finish template setup
Now that we have the `config` definition properly configured, let's modify the Cloudformation one:
```cue file=./tests/cloudformation/source-end.cue title="todoapp/cloudformation/source.cue"
```
This defines:
- `suffix`: random suffix leveraging the `random` relay. It doesn't have a seed because we don't care about predictability
- `cfnStackName`: Name of the stack, either a default value `stack-suffix` or user input
- `cfnStack`: Cloudformation relay with `AWS config`, `stackName` and `JSON template` as inputs
### Configure the environment
Before bringing up the deployment, we need to provide the `cfnStack` inputs declared in the configuration. Otherwise, Dagger will complain about missing inputs.
```shell
dagger up -e cloudformation
# 3:34PM ERR system | required input is missing input=awsConfig.region
# 3:34PM ERR system | required input is missing input=awsConfig.accessKey
# 3:34PM ERR system | required input is missing input=awsConfig.secretKey
# 3:34PM FTL system | some required inputs are not set, please re-run with `--force` if you think it's a mistake missing=0s
```
You can inspect the list of inputs (both required and optional) using dagger input list:
```shell
dagger input list -e cloudformation
# Input Value Set by user Description
# awsConfig.region string false AWS region
# awsConfig.accessKey dagger.#Secret false AWS access key
# awsConfig.secretKey dagger.#Secret false AWS secret key
# suffix.length *12 | number false length of the string
# cfnStack.onFailure *"DO_NOTHING" | "ROLLBACK" | "DELETE" false Behavior when failure to create/update the Stack
# cfnStack.timeout *10 | >=0 & int false Maximum waiting time until stack creation/update (in minutes)
# cfnStack.neverUpdate *false | true false Never update the stack if already exists
```
Let's provide the missing inputs:
```shell
dagger input text awsConfig.region us-east-2 -e cloudformation
dagger input secret awsConfig.accessKey yourAccessKey -e cloudformation
dagger input secret awsConfig.secretKey yourSecretKey -e cloudformation
```
### Deploying
Finally ! We now have a working template ready to be used to provision S3 infrastructures. Let's deploy it:
<Tabs
defaultValue="nd"
values={[
{ label: 'Normal deploy', value: 'nd', },
{ label: 'Debug deploy', value: 'dd', },
]
}>
<TabItem value="nd">
```shell
dagger up -e cloudformation
#2:22PM INF suffix.out | computing
#2:22PM INF suffix.out | completed duration=200ms
#2:22PM INF cfnStack.outputs | computing
#2:22PM INF cfnStack.outputs | #15 1.304 {
#2:22PM INF cfnStack.outputs | #15 1.304 "Parameters": []
#2:22PM INF cfnStack.outputs | #15 1.304 }
#2:22PM INF cfnStack.outputs | #15 2.948 {
#2:22PM INF cfnStack.outputs | #15 2.948 "StackId": "arn:aws:cloudformation:us-east-2:817126022176:stack/stack-emktqcfwksng/207d29a0-cd0b-11eb-aafd-0a6bae5481b4"
#2:22PM INF cfnStack.outputs | #15 2.948 }
#2:22PM INF cfnStack.outputs | completed duration=35s
dagger output list -e cloudformation
# Output Value Description
# suffix.out "emktqcfwksng" generated random string
# cfnStack.outputs.Name "arn:aws:s3:::stack-emktqcfwksng-s3bucket-9eiowjs1jab4" -
```
</TabItem>
<TabItem value="dd">
```shell
dagger up -l debug -e cloudformation
#Output:
# 3:50PM DBG system | detected buildkit version version=v0.8.3
# 3:50PM DBG system | spawning buildkit job localdirs={
# "/tmp/infra-provisioning/.dagger/env/infra/plan": "/tmp/infra-provisioning/.dagger/env/infra/plan"
# } attrs=null
# 3:50PM DBG system | loading configuration
# ... Lots of logs ... :-D
# Output Value Description
# suffix.out "abnyiemsoqbm" generated random string
# cfnStack.outputs.Name "arn:aws:s3:::stack-abnyiemsoqbm-s3bucket-9eiowjs1jab4" -
dagger output list -e cloudformation
# Output Value Description
# suffix.out "abnyiemsoqbm" generated random string
# cfnStack.outputs.Name "arn:aws:s3:::stack-abnyiemsoqbm-s3bucket-9eiowjs1jab4" -
```
</TabItem>
</Tabs>
The deployment went well!
In case of a failure, the `Debug deploy` tab shows the command to get more information.
The name of the provisioned S3 instance lies in the `cfnStack.outputs.Name` output key, without `arn:aws:s3:::`
> With this provisioning infrastructure, your dev team will easily be able to instantiate aws infrastructures: all they need to know is `dagger input list -e cloudformation` and `dagger up -e cloudformation` isn't that awesome? :-D
## Cue Cloudformation template
This section will convert the inlined JSON template to CUE to take advantage of the language features.
To do so quickly, we will first transform the template from JSON format to Cue format, then optimize it to leverage Cue's forces.
### 1. Create convert.cue
We will create a new `convert.cue` file to process the conversion
import Tabs from "@theme/Tabs";
import TabItem from "@theme/TabItem";
```cue file=./tests/cloudformation/template/convert.cue title="todoapp/cloudformation/convert.cue"
```
This defines:
- `s3Template`: contains the unmarshalled template.
You need to empty the plan and copy the `convert.cue` file to the plan for Dagger to reference it
```shell
mv cloudformation/source.cue ~/tmp/
```
### 2. Retrieve the Unmarshalled JSON
Then, still in the same folder, query the `s3Template` value to retrieve the Unmarshalled result of `s3`:
```shell
dagger query s3Template -e cloudformation
# {
# "AWSTemplateFormatVersion": "2010-09-09",
# "Outputs": {
# "Name": {
# "Description": "Name S3 Bucket",
# "Value": {
# "Fn::GetAtt": [
# "S3Bucket",
# "Arn"
# ...
```
The commented output above is the cue version of the JSON Template, copy it
### 3. Remove convert.cue
```shell
rm cloudformation/convert.cue
```
### 4. Store the output
Open `cloudformation/template.cue` and append below elements with copied Cue definition of the JSON:
```cue file=./tests/cloudformation/template/template-begin.cue title="todoapp/cloudformation/template.cue"
```
We're using the built-in `json.Marshal` function to convert CUE back to JSON, so Cloudformation still receives the same template.
You can inspect the configuration using `dagger query -e cloudformation` to verify it produces the same manifest:
```shell
dagger query template -f text -e cloudformation
```
Now that the template is defined in CUE, we can use the language to add more flexibility to our template.
Let's define a re-usable `#Deployment` definition in `todoapp/cloudformation/deployment.cue`:
```cue file=./tests/cloudformation/template/deployment.cue title="todoapp/cloudformation/deployment.cue"
```
`template.cue` can be rewritten as follows:
```cue file=./tests/cloudformation/template/template-end.cue title="todoapp/cloudformation/template.cue"
```
Verify template
Double-checks at the template level can be done with manual uploads on Cloudformation's web interface or by executing the below command locally:
```shell
tmpfile=$(mktemp ./tmp.XXXXXX) && dagger query template -f text -e cloudformation > "$tmpfile" && aws cloudformation validate-template --template-body file://"$tmpfile" ; rm "$tmpfile"
```
Let's make sure it yields the same result:
```shell
dagger query template -f text -e cloudformation
# {
# "description": "Name S3 Bucket",
# "indexDocument": "index.html",
# "errorDocument": "error.html",
# "version": "2012-10-17",
# "deletionPolicy": "Retain",
# "accessControl": "PublicRead",
# "template": {
# "AWSTemplateFormatVersion": "2010-09-09",
# "Outputs": {
# "Name": {
# "Description": "Name S3 Bucket",
# "Value": {
```
Reimplement `source.cue`:
```cue file=./tests/cloudformation/source-end.cue title="todoapp/cloudformation/source.cue"
```
And we can now deploy it:
```shell
dagger up -e cloudformation
#2:22PM INF suffix.out | computing
#2:22PM INF suffix.out | completed duration=200ms
#2:22PM INF cfnStack.outputs | computing
#2:22PM INF cfnStack.outputs | #15 1.304 {
#2:22PM INF cfnStack.outputs | #15 1.304 "Parameters": []
#2:22PM INF cfnStack.outputs | #15 1.304 }
#2:22PM INF cfnStack.outputs | #15 2.948 {
#2:22PM INF cfnStack.outputs | #15 2.948 "StackId": "arn:aws:cloudformation:us-east-2:817126022176:stack/stack-emktqcfwksng/207d29a0-cd0b-11eb-aafd-0a6bae5481b4"
#2:22PM INF cfnStack.outputs | #15 2.948 }
#2:22PM INF cfnStack.outputs | completed duration=35s
```
Name of the deployed bucket:
```shell
dagger output list -e cloudformation
# Output Value Description
# suffix.out "ucwcecwwshdl" generated random string
# cfnStack.outputs.Name "arn:aws:s3:::stack-ucwcecwwshdl-s3bucket-gaqmj8rzsl08" -
```
The name of the provisioned S3 instance lies in the `cfnStack.outputs.Name` output key, without `arn:aws:s3:::`
PS: This plan could be further extended with the AWS S3 example. It could provide infrastructure and quickly deploy it.
PS1: As it could be an excellent first exercise for you, this won't be detailed here. However, we're interested in your imagination: let us know your implementations :-)