Introduction

AWS Lambda environment variables use to adjust the function's behavior without updating the code. An environment variable is a pair of strings that are stored in a function's version-specific configuration. Lambda runtime makes environment variables available to our code and sets additional environment variables that contain information about the function and invocation request. We are going to use the addLambdaEnvironmentVariables operation to add the Lambda function environment variables. We can use the file or Input Argument to add the environment variables and the operation also supports encryption of the variables using AWS KMS key. We can select the option to publish a new version, by default operation will not publish the new version. The operation will use the configured AWS cloud account to perform the operation.

Objective

The goal of the tutorial is to add the environment variables using the environment file present at the git repository and input argument, in the already created Lambda Function. We are going to add secured variables also and to encrypt these variables we are going to use the AWS KMS key. Also we are going to publish the function version with added environment variables. We will have project property added in the deploy workflow and this project property value will be the list of the environment variables that we are going to provide in the input argument of the environment variables. We can use the dynamic value in both the environment file and input argument, please refer the document to get more details about environment variables' acceptable structure.

• configuration of the properties e.g. Cloud account, and CLI path.

• cloning the environment file from a Git repository.

• adding the environment variables to the Lamba function.

• sample code to retrieve the value of secured environment variables.

Checklist

Configure Cloud Account

To connect with AWS Lambda Function, we required to configure Cloud account, with credentials details. Configure AWS Cloud Account under Integration. FlexDeploy will connect to the Lambda Function and add the environment variables.

1. Navigate to the Integrations

2. Select Cloud from the left-hand pane

3. Create a new Cloud account with the “+” button. Create a new Cloud account of provider type “AWS”

It should have a AWS Access Key and AWS Secret Key. The user must have relevant access to AWS Lambda Function.

1. AWS Secret Key is a password field and hence needs to be kept hidden. To update the same click on the pencil icon as shown below

2. Update the AWS Secret Key value under Secret Text. This is to make sure no one else can retrieve the password

After configuration we would be able to use the Cloud Account as a drop down from the list.

Create AWS Lambda Function

AWS Lambda is a compute service that lets you run code without provisioning or managing servers. Lambda runs your code on a high-availability compute infrastructure and performs all of the administration of the compute resources, including server and operating system maintenance, capacity provisioning and automatic scaling, and logging. With Lambda, all you need to do is supply your code in one of the language runtimes that Lambda supports. Please refer to the link for more information https://docs.aws.amazon.com/lambda/latest/dg/welcome.html

To create the Lambda Function go to the AWS console

1. Navigate to the Services

2. Select Compute from the left-hand pane

3. Now click on the Lambda service option

After selecting the Lambda service, new window will open and it contains detail of all the functions.

Now select the create function option, it will open window to create function and configured detail.

By default AWS creates execution role with basic Lambda permissions, we can select an existing role also. In above example we are using existing role ( basic-lambda-role ) . Please refer to the link for more information https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles.html

The role which we are selecting must have basic Lambda permissions, the role we have selected also have permission for KMS key to decrypt the secured variables. If we are using the KMS key to encrypt the secured variables then we must have to give permission to the role to use the KMS key.

In above role we can see we have one permissions policy name as kms-access, this policy allow us to use the KMS key to decrypt the variables, which we have used to encrypt the variables.

Policy detail:

Trust relationships detail: ( Entities that can assume this role under specified conditions )

Detail of the AWS Lambda function which we have created and going to use for this tutorial:

In above function if we see the Environment variables details under the Configuration, there is no environment variables are present. Once successful execution of the operation we should be able to see some environment variables.

Create AWS KMS Key

AWS Key Management Service (AWS KMS) is a managed service that makes it easy for us to create and control the cryptographic keys that are used to protect our data. Please refer to the link for more information https://aws.amazon.com/kms/

AWS KMS key is required to encrypt the secured variables before adding them to Lambda function. If we don’t have any secured variables in that case we don’t required to configure KMS key detail in the project. In our scenario we are adding both secured and non-secured variables to the Lambda function.

To create the Lambda Function go to the AWS console

1. Navigate to the Services

2. Select Security, Identity, & Compliance from the left-hand pane

3. Now click on the Key Management Service service option

Detail of the KMS key which we are using for this tutorial:

We can use Key ID or Key ARN value in the project to encrypt the variables, both are accepted.

Git Repository Structure

The Git repository contains the Environment file.

The Sample Git repository structure is given below.

Pre-requisite

Configure IAM User

To access the Lambda Function we need to create an AWS IAM account with required permissions. To create the AWS IAM user navigate to the AWS Identity and Access Management (IAM) service page, and click on the Add users option. Next assign the required permission to access the Lambda Function. Once user is created, AWS secret key can be generated, this key we have to configure in Cloud account.

For more information about IAM user please ref. IAM users - AWS Identity and Access Management

CLI Installation

• AWS CLI should be installed in the m/c where the plugin is to be executed. Preferably add AWS CLI path in m/c classpath.

Build and Deploy Workflows

Navigate to the Workflows tab and create a workflow using the “+”(Click to create new Workflow) button as highlighted below.

Next, create one Build and Deploy workflow as shown below. The workflow Type field defines the type of workflow.
Build Workflow

1. Navigate to the Workflows

2. Select the “+” button from the left-hand pane to create a new workflow

Deploy Workflow

1. navigate to the Workflows

2. Select the “+” button from the left-hand pane to create a new workflow

The Workflow Group and Subgroup define the folder hierarchy. Once both workflows are created it should look like the below. No constraint on workflow or folder naming convention.

The steps of the workflow execution can be configured through the Workflow Definition section.

Below given is a sample build workflow to copy the file from Git repository.

Step-i: Clone Git Repository
This step will clone the Git repository codebase into the project execution working directory. The Git URL will be retrieved from Source Control configured under Project Configuration.

Step-ii: Copy the environment file
The below step will copy the environment file to the artifact. Also check the Produces Artifact option to save the files as artifact so that can be used from Deploy workflow.

Below given is a sample build workflow to add the environment variable to the AWS Lambda function.

Step-i: add environment variables

This step will add environment variables to the Lambda Function and publish the version.

In above configuration using following Inputs.

Project Configuration

Navigate to the Project tab and create a Project with a logical name(AWS-Lambda-Environment-Variable in this case)

Configure the Build and Deploy workflow that has been created in previous steps as shown below.

Source Control

Configure the Source SCM repository under Source Control as shown below.

1. To configure Project specific Source Control one first need to navigate to the Project Configuration tab.

2. Next, expand the SOURCE CONTROL option from the left-hand pane.

3. Select the appropriate Source Control Type

4. Configure Source Repository. For detailed steps of Source Control configuration please refer to Configure Source Control in FlexDeploy

Project Properties

Lambda Function name: Name of the Function to add the environment variables, if lambda function name is not given name of the environment file will be use as function name.

Environment Variable File Path: Path of the file which contains list of the environment variables.

Please refer to the document for more details about Lambda function name and Environment Variable File path . AWS Lambda - Environment Variable File and zip File location options

KMS detail: Key Id or Key ARN details, both are accepted. Please refer to the document for more details. https://docs.aws.amazon.com/kms/latest/developerguide/overview.html

Target Properties

Select Topology from the menu and then select Targets. Select the target group and environment, provide the properties detail, according to the description.

Below given are the environment-specific values which need to be updated.

Cloud Account

The AWS Cloud account needs to be set here from the drop-down. It will show all Cloud Accounts configured under Topology, which we have already mentioned earlier.

CLI Path

AWS CLI path can be set as environment property, if it’s not set then by default plugin will check for CLI in system classpath.

Override Properties at Project Level

Let assume a scenario, where we want to change Cloud account for any specific project. Apart from setting at environment level, it can also be set at project properties by using Override Property. Please check below mentioned steps.

1. Navigate to the Project Configuration tab as shown above.

2. Next, select the PROPERTIES option from the left-hand pane.

3. Click on the OVERRIDE option.

4. Select the Cloud Account option from Property.

5. Select the Environment from the drop down list.

6. Select the Target Group from the drop down list.

Build and Deploy Execution

For detailed steps on how to perform build and deploy, please refer to document. Deploy through FlexDeploy for AWS plugin

After Deploy Execution

Once the add environment operation successful we can see the variable details on the AWS Lambda Function console.

And we have selected the publish version option from the workflow so we can verify the published function version, from the plugin output and AWS Lambda console.

Sample Code to Retrieve the Secured Variables

We have also added some non-secured variables ( Password and Mysql_Connection_String ) to the Lambda Function and to encrypt these variables we have used AWS KMS key, to get the values of secured variables we can use the sample code provided by AWS Lambda according to the Function code language. In our case we are using java script, below is the sample code to get the value of secured and non-secured variables and creating the response to print the values.

const AWS = require('aws-sdk');
AWS.config.update({ region: 'us-east-1' });

const functionName = process.env.AWS_LAMBDA_FUNCTION_NAME;
let password;
let userName;
let connectionString;

function processEvent(event) {
}

exports.handler = async (event) => {

    const kms = new AWS.KMS();
    try {
      password = process.env['Password'];
      userName = process.env['UserName'];
      connectionString = process.env['Mysql_Connection_String'];
      let req = {
        CiphertextBlob: Buffer.from(password, 'base64'),
        EncryptionContext: { LambdaFunctionName: functionName },
      };
      let data = await kms.decrypt(req).promise();
      password= data.Plaintext.toString('ascii');

      req = {
        CiphertextBlob: Buffer.from(connectionString, 'base64'),
        EncryptionContext: { LambdaFunctionName: functionName },
      };
      data = await kms.decrypt(req).promise();
      connectionString = data.Plaintext.toString('ascii');
    } catch (err) {
      console.log('Decrypt error:', err);
      throw err;
    }
  
  processEvent(event);
   const response = {
        UserName: userName,
        Password: password,
        ConnectionString: connectionString
    };

  return  {
  "isBase64Encoded": false,
  "statusCode": 200,
  "body": JSON.stringify(response),
  "headers": {
    "content-type": "application/json"
  }
};
};

We can use the test option of the AWS-Lambda to test our function code, in our case test response will be:

Please refer to the link, for more details about encryption and decryption of the secured variables AWS KMS --encryption-context understanding