Kubeform by AppsCode is a Kubernetes operator for Terraform. Kubeform provides auto-generated Kubernetes CRDs for Terraform resources and modules so that you can manage any cloud infrastructure in a Kubernetes native way. You just write a CRD for a cloud infrastructure, apply it and Kubeform will create it for you! Kubeform currently supports 5 top cloud platforms. These are AWS, Google Cloud, Azure, Digitalocean and Linode.

The key features of Kubeform are:

Native kubernetes support

Built on Terraform

Supports Terraform resources and modules

Use cloud infrastructures as code

Define & Manage cloud infrastructures as Kubernetes CRD (Custom Resource Definition)

(Custom Resource Definition) Supports multiple cloud platform

100% open source

How Kubeform Works

The following diagram shows how Kubeform creates a resource on a Cloud Provider (GCP, AWS, etc.).

Fig: How Kubeform Works

The Resource Creation Process of Kubeform consists of the following steps:

At first, a user creates a secret with access credentials of the Cloud provider where the resource will be created. Then, he creates a CRD of the resource that specifies the information of the Cloud Resource. The CRD also holds the credential information. The KubeForm Controller (KFC) watches the created CRD. Then, KFC creates .tf files from the CRD Spec and the provider secret. If the .tfstate file doesn’t exist then KFC creates the .tfstate file from the status.output & status.state fields of the CRD. Then KFC runs terraform apply commands on the .tfstate file and .tf files that were created in the previous steps. After successful execution of terraform apply command, it creates the specified resource on the specified Cloud Provider. Then terraform apply command updates the tfstate file if necessary. If the .tfstate file is updated, KFC also updates the status.output & status.state fields of the CRD.

How to use Kubeform

Let’s take a look at how can we create anp AWS RDS (Relational Database Service) using Kubeform .

First install the kubeform operator following the instructions here:

Using Helm 3 Kubeform can be installed via Helm using the chart from AppsCode Charts Repository. To install the chart with the release name my-release : $ helm repo add appscode https://charts.appscode.com/stable/ $ helm repo update $ helm search repo appscode/kubeform NAME CHART VERSION APP VERSION DESCRIPTION appscode/kubeform v0.1.0 v0.1.0 Kubeform by AppsCode - Build Cloud Infrastructure from Kubernetes $ helm install kfc appscode/kubeform --version v0.1.0 --namespace kube-system To see the detailed configuration options, visit here. Using Helm 2 Kubeform can be installed via Helm using the chart from AppsCode Charts Repository. To install the chart with the release name my-release : $ helm repo add appscode https://charts.appscode.com/stable/ $ helm repo update $ helm search appscode/kubeform NAME CHART VERSION APP VERSION DESCRIPTION appscode/kubeform v0.1.0 v0.1.0 Kubeform by AppsCode - Build Cloud Infrastructure from Kubernetes $ helm install appscode/kubeform --name kfc --version v0.1.0 --namespace kube-system To see the detailed configuration options, visit here.

Now, we need AWS provider secrets to connect with AWS. For terraform, this secrets are provided like this in a .tf file:

{ "provider": { "aws": { "access_key": "ACCESS_KEY", "region": "us-east-1", "secret_key": "SECRET_KEY" } } }

For using it in Kubeform , we need to convert it to a secret like this:

apiVersion : v1 kind : Secret metadata : name : aws type : kfc.io/aws data : region : dXMtZWFzdC0xCg== # base64 encoded value of `us-east-1` access_key : '<base64 encoded access key>' secret_key : '<base64 encoded secret key>'

Then we have to reference it from our Resource CRD.

Now We need to create the AWS RDS CRD. We can create the AWS RDS CRD using the following kubectl command:

kubectl apply -f https://github.com/kubeform/kubeform/raw/master/api/crds/aws.kubeform.com_dbinstances.yaml

The AWS RDS configuration of terraform is given in a .tf like this:

{ "resource": { "aws_db_instance": { "test1": { "allocated_storage": 5, "engine": "mysql", "engine_version": "5.7", "instance_class": "db.t2.micro", "name": "mydb", "parameter_group_name": "default.mysql5.7", "password": "foobar1234", "storage_type": "gp2", "username": "foo" } } } }

We can see that, there is a field called password, which is a sensitive value. So, we should not use this kind of sensitive value directly in the yaml. We’ll create a secret to store the sensitive value like the this:

apiVersion : v1 kind : Secret metadata : name : rds-pass type : kfc.io/aws data : password : Zm9vYmFyMTIzNAo= # base64 encoded value of `foobar1234`

Then we can reference it from our DbInstance CRD. The DbInstance CRD will look like this:

apiVersion : aws.kubeform.com/v1alpha1 kind : DbInstance metadata : name : test1 spec : allocatedStorage : 5 storageType : gp2 engine : mysql engineVersion : '5.7' instanceClass : db.t2.micro name : mydb username : foo parameterGroupName : default.mysql5 .7 providerRef : name : aws secretRef : name : rds-pass

Here, we can see that the provider secret is referenced using a field called providerRef and the sensitive value secret is referenced using a field called secretRef .

Let’s put it altogether and apply it using kubectl. First create a aws_rds.yaml using the following yaml:

AWS RDS apiVersion : v1 kind : Secret metadata : name : aws type : kfc.io/aws data : region : dXMtZWFzdC0xCg== access_key : '<base64 encoded access key>' secret_key : '<base64 encoded secret key>' --- apiVersion : v1 kind : Secret metadata : name : rds-pass type : kfc.io/aws data : password : Zm9vYmFyMTIzNAo= --- apiVersion : aws.kubeform.com/v1alpha1 kind : DbInstance metadata : name : test1 spec : allocatedStorage : 5 storageType : gp2 engine : mysql engineVersion : '5.7' instanceClass : db.t2.micro name : mydb username : foo parameterGroupName : default.mysql5 .7 providerRef : name : aws secretRef : name : rds-pass

Then, run:

kubectl apply -f aws_rds.yaml

After that, an AWS RDS will be created!

To delete the rds instance just run:

kubectl delete -f aws_rds.yaml

How Kubeform handles Terraform State

Terraform Resource

For individual resources, Kubeform doesn’t store the full tfstate file in the CRD. The tfstate json file contains version , terraform_version , serial , lineage and resources fields.

Kubeform stores the tfstate file in the CRD using the following way:

The version , terraform_version , serial and, lineage fields are stored in status.state field in the custom resources. The data from the resources field that are not sensitive are stored in the output field of the CRD. The data from the resources field that are sensitive are stored in a secret. The secret name is specified in a secretRef field of the CRD. If the secretRef is not set, then KFC creates a secret and stores the sensitive outputs there.

To obtain the tfstate from the state field:

The version , terraform_version , serial and, lineage fields are retrieves from the status.state field of a Kubeform resource. The non-sensitive data from the output field of status and the sensitive data from the secret are merged and then set on the resources field.

Terraform Module

For Terraform modules, Kubeform stores the full tfstate file in the CRD status object. As the tfstate file may contain sensitive information, KFC doesn’t store the tfstate file directly.

Before storing the tfstate file in the CRD, the tfstate is transformed in the following steps:

First, the content of the tfstate file is compressed using gzip . Then the compressed data is encrypted using a secret key. The secret key is a base64 encoded key which is 32 bytes when decoded. The secret key is provided by the user to the Kubeform operator( kfc ). The encrypted data is basE91 encoded. basE91 is an advanced method for encoding binary data as ASCII characters. It is similar to base64, but is more efficient. The overhead produced by basE91 depends on the input data. It amounts at most to 23% (versus 33% for base64). Finally, the base91 encoded data is stored in the state field of status object in the CRD.

The process is shown in the following figure:

Fig: `tfstate` to `state` string in CRD

To obtain the tfstate file from the status.state field of a custom resource, the steps is followed in reverse:

First, the status.state field of the Kubeform module resource is base91 decoded. The base91 decoded data is then decrypted using the secret key. Then the decrypted data is decompressed using gzip . Finally, decompressed data is saved as a tfstate file.

The process is shown in the following figure:

Fig: `state` string in CRD to `tfstate`

Alternatives

We have explored the option of using Kubernetes Service Catalog project to consume cloud services in Kubernetes using the Open Service Broker API. But CRDs provide better tooling in the context of Kubernetes. Also, this project has seen very little activity in recent times and cloud providers are abandoning it in favor of CRD based solutions.

Visit Kubeform project website to learn more. You can also find us on GitHub.

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