Extend your service mesh to support AWS Lambda

While managing a service mesh with Consul, you may need to exchange the source of a service for another source. For example, a service mesh hosted on a Kubernetes cluster could include a service that experiences heavy amounts of traffic which exceeds the provisioned capacity of the cluster. Autoscaling a cluster is a common method to manage peak capacity, but autoscaling takes time to provision new instances within a cluster to meet the needs of the service. Serverless computing solutions like AWS Lambda can quickly scale to the capacity a service requires, without the time investment of waiting for instances to provision. During instances of peak demand, this can help you or your organization manage workloads in a sustainable predictable manner.

With Consul on AWS Lambda, you can take advantage of the benefits of serverless workloads. These benefits include reducing cost, decreasing administrative overhead, and scaling services inside a Consul service mesh with minimal context switching.

In this tutorial, you will deploy HashiCups, a demo application, onto an Amazon Elastic Kubernetes Services (EKS). Then, you will learn how to route traffic away from a Kubernetes service and towards a Lambda function, using Consul's service splitter and terminating gateway.

Prerequisites

The tutorial assumes an intermediate understanding of Consul, AWS, and Kubernetes. If you're new to Consul, refer to the Getting Started tutorials collection.

For this tutorial, you will need:

• An HCP account configured for use with Terraform

• An AWS account configured for use with Terraform

• aws-cli 2.4.15+

• docker 4.3.1+

• kubectl < v1.23.9

• terraform 1.2.5+

• git v2.30.1+

• jq v1.6+

A cleanup script is provided to help minimize the time resources are actively accruing charges to your AWS account.

Clone example repository

Clone the GitHub repository containing the configuration files and resources.

$ git clone https://github.com/hashicorp-education/learn-consul-terraform

$ git clone git@github.com:hashicorp/learn-consul-terraform.git

Navigate into the repository folder.

$ cd learn-consul-terraform

Fetch the latest tags and check out the v0.9 tag of the repository.

$ git fetch --all --tags && git checkout tags/v0.10

Navigate into the project's terraform folder for this tutorial.

$ cd datacenter-deploy-hcp-eks-lambda

Deploy tutorial infrastructure

This tutorial deploys an HCP Consul Dedicated cluster, an Amazon EKS cluster with Consul installed via Helm and supporting infrastructure. The Consul cluster on EKS is pre-configured with support for AWS Lambda, and includes a terminating gateway you will configure later in this tutorial.

Initialize the Terraform project.

$ terraform init Initializing the backend... Initializing provider plugins... Terraform has been successfully initialized! You may now begin working with Terraform. Try running "terraform plan" to seeany changes that are required for your infrastructure. All Terraform commandsshould now work. If you ever set or change modules or backend configuration for Terraform,rerun this command to reinitialize your working directory. If you forget, othercommands will detect it and remind you to do so if necessary.

Then, deploy the resources. Confirm by entering yes.

$ terraform apply ## . . .Do you want to perform these actions? Terraform will perform the actions described above. Only 'yes' will be accepted to approve.  Enter a value: yes ## . . . Apply complete! Resources: 122 added, 0 changed, 0 destroyed.

Once complete, Terraform will display a list of outputs that you will use to connect to your HCP Consul Dedicated and Kubernetes clusters.

## . . .Apply complete! Resources: 122 added, 0 changed, 0 destroyed.Outputs:cloudwatch_logs_path = {  "eks" = "/aws/eks/consullambda-w19vbd/cluster"  "payments" = "/aws/lambda/payments-lambda-w19vbd"  "registrator" = "/aws/lambda/lambda_registrator-consullambda-w19vbd"}consul_addr = "https://consullambda-w19vbd.consul.98a0dcc3-5473-4e4d-a28e-6c343c498530.aws.hashicorp.cloud"eks_update_kubeconfig_command = "aws eks --region us-west-2 update-kubeconfig --name consullambda-w19vbd"hcp_login_token = <sensitive>kubernetes_cluster_endpoint = "https://7CE233483FD372627372941C9C68D0F8.gr7.us-west-2.eks.amazonaws.com"region = "us-west-2"

Configure your terminal to connect to HCP Consul Dedicated and Kubernetes

Update your local kubeconfig file by using the Terraform output eks_update_kubeconfig_command. Then, verify that you can connect to your EKS cluster with kubectl cluster-info.

$ terraform output -json | jq -r '.eks_update_kubeconfig_command.value' | $SHELL && kubectl cluster-infoUpdated context arn:aws:eks:us-west-2:REDACTED:cluster/consullambda-dl0r7o in /Users/user/.kube/configKubernetes control plane is running at https://FD534A8E1D33199C6A1394F490B63394.gr7.us-west-2.eks.amazonaws.comCoreDNS is running at https://FD534A8E1D33199C6A1394F490B63394.gr7.us-west-2.eks.amazonaws.com/api/v1/namespaces/kube-system/services/kube-dns:dns/prox

Set the environment variables required by kubectl and the AWS CLI.

$ export AWS_REGION=$(terraform output -raw region) && \export LOG_GROUP="$(terraform output -json cloudwatch_logs_path | jq -r '.registrator')" && \export LAMBDA_FUNC_LOG=$(terraform output -json | jq -r '.cloudwatch_logs_path.value.payments')

Set your HCP Consul Dedicated environment variables. You will use these to configure your Consul CLI to interact with your HCP Consul cluster.

$ export CONSUL_HTTP_TOKEN=$(terraform output -raw hcp_login_token) && \export CONSUL_HTTP_ADDR=$(terraform output -raw consul_addr) && \export POLICY_NAME="payments-lambda-tgw"

Verify tutorial infrastructure

Copy and paste the Consul public URL (consul_public_endpoint) into your browser to visit the Consul UI. Since HCP Consul is secure by default, copy and paste the ACL token (hcp_login_token) into the Consul authentication prompt to use the Consul UI.

Once you have authenticated, click the Services tab on the left navigation pane to review your deployed services.

Verify HashiCups deployment

Retrieve the URL of the Consul API Gateway. Input this URL into your browser to confirm HashiCups is working.

$ kubectl get services api-gatewayNAME          TYPE           CLUSTER-IP       EXTERNAL-IP                                                               PORT(S)        AGEapi-gateway   LoadBalancer   10.100.171.204   a315d8970349c44928b9c12b07d7a118-1429028736.us-west-2.elb.amazonaws.com   80:32601/TCP   30m

Verify payment service routing to Kubernetes

Verify HashiCups is routing payments traffic to the Kubernetes pod. Later, you will compare this output to the payments service routing to the Lambda function.

Create a port-forward, sending local requests to port 8080 to the public-api.

$ kubectl port-forward deploy/public-api 8080Forwarding from 127.0.0.1:8080 -> 8080Forwarding from [::1]:8080 -> 8080

In another terminal, simulate a payment by sending the following request with curl to the HashiCups public-api endpoint.

$  curl -v 'http://localhost:8080/api' \      -H 'Accept-Encoding: gzip, deflate, br' \      -H 'Content-Type: application/json' \      -H 'Accept: application/json' \      -H 'Connection: keep-alive' \      -H 'DNT: 1' \      -H 'Origin: http://localhost:8080' \      --data-binary '{"query":"mutation{ pay(details:{ name: \"HashiCups_User!\", type: \"mastercard\", number: \"1234123-0123123\", expiry:\"10/02\",    cv2: 1231, amount: 12.23 }){id, card_plaintext, card_ciphertext, message } }"}' --compressed | jq

The following message indicates a successful response to your request. The Kubernetes-based payments service is returning unencrypted data as noted by the card_ciphertext return value.

{  "data": {    "pay": {      "id": "edb7bc10-164c-4d0b-a285-d6797bcfd953",      "card_plaintext": "1234123-0123123",      "card_ciphertext": "Encryption Disabled",      "message": "Payment processed successfully, card details returned for demo purposes, not for production"    }  }}

Create AWS Lambda function registrator

Since Lambda functions do not include a Consul agent, you must register Lambda functions to the Consul service mesh using the Consul API. You can do this using the consul-lambda-registrator Terraform module, or manually through the Consul API. In this tutorial, you will use consul-lambda-registrator to automatically register Lambda functions in Consul service mesh.

The Terraform module deploys a registrator Lambda function. The registrator function checks for Lambda functions with specific Consul annotations in your account, in the deployed region, on an interval, defined by the Lambda function's tags block in the aws_lambda resource. When discovered, the registrator functions registers the Lambda function as a service in Consul service mesh.

The registrator module also deploys a private Elastic Container Registry repository to store the registrator's container image in your AWS account.

Begin by adding the Lambda function registrator code to the lambda-tutorial.tf Terraform file. Note the highlighted lines below for the sync frequency and the ECR repository.

module "lambda-registration" {  source                    = "hashicorp/consul-lambda-registrator/aws//modules/lambda-registrator"  version                   = "0.1.0-beta1"  name                      = aws_ecr_repository.lambda-registrator.name  ecr_image_uri             = "${aws_ecr_repository.lambda-registrator.repository_url}:${local.ecr_image_tag}"  subnet_ids                = module.infrastructure.vpc_subnets_lambda_registrator  security_group_ids        = [module.infrastructure.vpc_default_security_group]  sync_frequency_in_minutes = 1   consul_http_addr       = module.infrastructure.consul_addr  consul_http_token_path = aws_ssm_parameter.token.name   depends_on = [    null_resource.push-lambda-registrator-to-ecr  ]} resource "aws_ecr_repository" "lambda-registrator" {  name = local.ecr_repository_name} resource "null_resource" "push-lambda-registrator-to-ecr" {  triggers = {    ecr_base_image = local.ecr_base_image  }   provisioner "local-exec" {    command = <<EOF    aws ecr get-login-password --region ${local.public_ecr_region} | docker login --username AWS --password-stdin ${aws_ecr_repository.lambda-registrator.repository_url}    docker pull ${local.ecr_base_image}    docker tag ${local.ecr_base_image} ${aws_ecr_repository.lambda-registrator.repository_url}:${local.ecr_image_tag}    docker push ${aws_ecr_repository.lambda-registrator.repository_url}:${local.ecr_image_tag}    EOF  }   depends_on = [    aws_ecr_repository.lambda-registrator  ]} resource "aws_ssm_parameter" "token" {  name  = "/${local.ecr_repository_name}/token"  type  = "SecureString"  value = module.infrastructure.consul_token  tier  = "Advanced"}

Use terraform get in the project folder to download the consul-lambda-registrator module.

$ terraform getDownloading hashicorp/consul-lambda-registrator/aws 0.1.0-alpha2 for lambda-registration...- lambda-registration in .terraform/modules/lambda-registration/modules/lambda-registratorDownloading terraform-aws-modules/eventbridge/aws 1.14.1 for lambda-registration.eventbridge...- lambda-registration.eventbridge in .terraform/modules/lambda-registration.eventbridge

Create the registrator. Confirm by entering yes.

$ terraform apply -auto-approve## . . . Plan: 14 to add, 0 to change, 0 to destroy. Do you want to perform these actions?  Terraform will perform the actions described above.  Only 'yes' will be accepted to approve.   Enter a value: Apply complete! Resources: 14 added, 0 changed, 0 destroyed. ## . . .

Deploy AWS Lambda function for HashiCups payments

Next, you will deploy the Lambda function payments workload and supporting infrastructure. This includes an IAM Role and Policy to write logs to CloudWatch, allowing you to confirm success in using this tutorial. The diagram below reflects the flow of how the payments service routes to AWS Lambda via the terminating gateway.

The Lambda function resource includes a block of tags. You must include these annotations for the registrator to register your Lambda function to the Consul service mesh.

Add the following block of Terraform code to lambda-tutorial.tf to deploy the Lambda function. The Lambda function will replace the payments service and pods in Kubernetes.

resource "aws_lambda_function" "lambda-payments" {  filename         = local.lambda_payments_path  source_code_hash = filebase64sha256(local.lambda_payments_path)  function_name    = local.lambda_payments_name  role             = aws_iam_role.lambda_payments.arn  handler          = "lambda-payments"  runtime          = "go1.x"  tags = {    "serverless.consul.hashicorp.com/v1alpha1/lambda/enabled"             = "true"    "serverless.consul.hashicorp.com/v1alpha1/lambda/payload-passthrough" = "false"    "serverless.consul.hashicorp.com/v1alpha1/lambda/invocation-mode"     = "SYNCHRONOUS"  }} resource "aws_iam_policy" "lambda_payments" {  name        = "${local.lambda_payments_name}-policy"  path        = "/"  description = "IAM policy lambda payments"   policy = <<EOF{  "Version": "2012-10-17",  "Statement": [    {      "Action": [        "logs:CreateLogGroup",        "logs:CreateLogStream",        "logs:PutLogEvents"      ],      "Resource": "arn:aws:logs:*:*:*",      "Effect": "Allow"    }  ]}EOF} resource "aws_iam_role" "lambda_payments" {  name = "${local.lambda_payments_name}-role"   assume_role_policy = <<EOF{  "Version": "2012-10-17",  "Statement": [    {      "Action": "sts:AssumeRole",      "Principal": {        "Service": "lambda.amazonaws.com"      },      "Effect": "Allow",      "Sid": ""    }  ]}EOF} resource "aws_iam_role_policy_attachment" "lambda_payments" {  role       = aws_iam_role.lambda_payments.name  policy_arn = aws_iam_policy.lambda_payments.arn}

Create the Lambda function. Confirm by entering yes.

$ terraform apply## . . . Plan: 4 to add, 0 to change, 0 to destroy. Do you want to perform these actions?  Terraform will perform the actions described above.  Only 'yes' will be accepted to approve.   Enter a value: Apply complete! Resources: 4 added, 0 changed, 0 destroyed. ## . . .

When Terraform finishes creating the function, wait one minute for the registrator to sync and register the new Lambda function. Use the following aws logs command to verify the registrator found and registered the payments Lambda function.

$ aws logs filter-log-events --region $AWS_REGION --log-group-name $LOG_GROUP  --filter-pattern "Upserting" | jq '.events[].message'"2022-07-08T13:50:15.979Z [INFO]  Upserting Lambda: arn=arn:aws:lambda:us-west-2:REDACTED:function:lambda-payments-klgvh\n"

Next, navigate into the Consul UI's Services section, to verify the Lambda function is registered in Consul service mesh. You should find a service starting with payments-lambda- in the dashboard.

Migrate Consul payments service to Lambda function

The Lambda function is present in the service mesh, but is not receiving traffic. As the Lambda function is considered an external workload by Consul, the Consul terminating gateway will serve as the proxy for this Lambda function.

Configure ACL for terminating gateway

The terminating gateway needs permission the via an ACL policy to interact with the Lambda function in Consul.

Retrieve the terminating gateway's ACL token, saving the AccessorID as an environment variable named TGW_TOKEN.

$ TGW_TOKEN=$(consul acl token list -format=json | jq '.[] | select(.Roles[]?.Name | contains("terminating-gateway"))' | jq -r '.AccessorID') && echo $TGW_TOKEN00000000-0000-0000-0000-000000000000

Next, open practitioner/terminating-gateway-policy.hcl. This is a pre-rendered policy file for the ACL token, that grants read (intentions) and write (policy) access to the payment service and payments Lambda service. Your policy file should look similar to the following code block.

service "payments-lambda-00000" {  policy = "write"  intentions = "read"} service "payments" {  policy = "write"  intentions = "read"}

Create an ACL policy with the pre-rendered policy file.

$ consul acl policy create -name "${POLICY_NAME}" -description "Allows Terminating Gateway to pass traffic from the payments Lambda function" -rules @./practitioner/terminating-gateway-policy.hclID:           4b4cd926-b6f7-1e17-236d-7cee05855f69Name:         payments-lambda-tgwPartition:    defaultNamespace:    defaultDescription:  Allows Terminating Gateway to pass traffic from the payments Lambda functionDatacenters:Rules:service "payments" {  policy = "write"  intentions = "read"} service “payments-lambda-00000" {  policy = "write"  intentions = "read"}

Associate this policy with the saved ACL token for the terminating gateway, merging this policy to existing roles and policies associated to this token.

$ consul acl token update -id $TGW_TOKEN -policy-name $POLICY_NAME -merge-policies -merge-rolesAccessorID:       a91736e9-cbd0-d729-1479-20529fd23155SecretID:         f221d8ef-07de-552e-a712-fe8282bd98d5Partition:        defaultNamespace:        defaultDescription:      token created via login: {"component":"terminating-gateway/consul-terminating-gateway"}Local:            trueAuth Method:      consul-k8s-component-auth-method (Namespace: default)Create Time:      2022-07-08 13:47:05.098979546 +0000 UTCPolicies:   e71932a0-c517-bb3c-3f01-e25e49546a82 - payments-lambda-tgw

Link Lambda payments service to terminating gateway

Associate the Lambda function service to the Consul terminating gateway. The terminating gateway routes requests for the payments service, to the AWS Lambda function. Open ./practitioner/terminating-gateway.yaml to find the pre-rendered service terminating gateway definition.

Review the following YAML example to observe the association of the payments Lambda function to the terminating gateway.

apiVersion: consul.hashicorp.com/v1alpha1kind: TerminatingGatewaymetadata:  name: terminating-gatewayspec:  services:    - name: payments-lambda-000000

Apply the pre-rendered terminating gateway configuration file to the Kubernetes cluster.

$ kubectl apply --filename ./practitioner/terminating-gateway.yamlterminatinggateway.consul.hashicorp.com/terminating-gateway created

In the Consul UI, the Terminating Gateway now includes the payments-lambda service as a linked service to the gateway:

Route traffic to payments Lambda function with service splitter

Since this tutorial uses Consul with ACLs enabled, the public-api service requires a service intention to route requests to the underlying Lambda function. Open ./practitioner/service-intentions.yaml to find the pre-rendered service intentions definition.

apiVersion: consul.hashicorp.com/v1alpha1kind: ServiceIntentionsmetadata:  name: payments-lambda-7u2jmcspec:  sources:    - name: public-api      action: allow  destination:    name: payments-lambda-000000

Apply the pre-rendered service intention definition file.

$ kubectl apply --filename ./practitioner/service-intentions.yamlserviceintentions.consul.hashicorp.com/payments-lambda-w19vbd created

Route traffic to the payments-lambda function with the ServiceSplitter resource. In this tutorial, you will route 100% of the traffic for the payment service to the payments-lambda function. Open ./practitioner/service-intentions.yaml to find the pre-rendered ServiceSplitter definition.

# Example onlyapiVersion: consul.hashicorp.com/v1alpha1kind: ServiceSplittermetadata:  name: paymentsspec:  splits:    - weight: 100      service: payments-lambda-000000    - weight: 0      service: payments

Apply the pre-rendered ServiceSplitter policy.

$ kubectl apply --filename ./practitioner/service-splitter.yamlservicesplitter.consul.hashicorp.com/payments-lambda created

Verify payment service routing to Lambda

Verify HashiCups is routing payments traffic to the Lambda function by simulating a payment.

Create a port-forward that sends local requests to port 8080 to the public-api.

$ kubectl port-forward deploy/public-api 8080 Forwarding from 127.0.0.1:8080 -> 8080Forwarding from [::1]:8080 -> 8080

In a different terminal, simulate a payment by sending the following request with curl to the HashiCups public-api endpoint.

$ curl -v 'http://localhost:8080/api' \  -H 'Accept-Encoding: gzip, deflate, br' \  -H 'Content-Type: application/json' \  -H 'Accept: application/json' \  -H 'Connection: keep-alive' \  -H 'DNT: 1' \  -H 'Origin: http://localhost:8080' \  --data-binary '{"query":"mutation{ pay(details:{ name: \"HELLO_LAMBDA_FUNCTION!\", type: \"mastercard\", number: \"1234123-0123123\", expiry:\"10/02\",    cv2: 1231, amount: 12.23 }){id, card_plaintext, card_ciphertext, message } }"}' --compressed | jq

The following payload indicates a successful response to your request. Note the value of card_ciphertext returning Encryption Enabled. In context of this tutorial, this value confirms the payments service routed to AWS Lambda, as the terminating gateway returns send and returns encrypted traffic.

{  "data": {    "pay": {      "id": "5a73bda6-a9e1-4c60-9163-c467211f8e0f",      "card_plaintext": "1234123-0123123","card_ciphertext": "Encryption Enabled (Lambda)"      "message": "Payment processed successfully, card details returned for demo purposes, not for production"    }  }}

$ terraform output -raw eks_update_kubeconfig_command# Output string of `eks-_update_kubeconfig_command`aws eks --region us-west-2 update-kubeconfig --name consullambda-22qxot

To verify the AWS Lambda function responded to this request, search for the value of the name key from the request payload in the Cloudwatch logs. You should find HELLO_LAMBDA_FUNCTION in the returned data.

$ aws logs filter-log-events --region $AWS_REGION --log-group-name $LAMBDA_FUNC_LOG | jq '.events[].message'"START RequestId: ea34f875-ecf4-4e44-83cd-080a8eacb0c0 Versio: $LATEST""BODY: %+v""{HELLO_LAMBDA_FUNCTION! mastercard 1234123-0123123 10/02 1231}""END RequestId: ea34f875-ecf4-4e44-83cd-080a8eacb0c0""REPORT RequestId: ea34f875-ecf4-4e44-83cd-080a8eacb0c0tDuratio: 16.24 mstBilled Duratio: 17 mstMemory Size: 128 MBtMax Memory Used: 28 MBtIit Duratio: 73.97 mst"

Clean up

To remove all resources, use terraform destroy twice. Use the following command to have terraform destroy immediately begin after the first command finishes running.

$ terraform destroy -auto-approve && terraform destroy --auto approve

Next Steps

In this tutorial, you migrated a Consul service from Kubernetes to an AWS Lambda function. First, you deployed the Terraform Lambda function registrator for Consul, which listens for Lambda functions being created in your AWS account. Then, you used a Terminating Gateway, Service Splitter, and Service Intention to route traffic flow in the service mesh with no downtime. Refer to the Consul AWS Lambda documentation for further details about Lambda function support in Consul.

To register a Lambda function manually in Consul, the Lambda registration documentation provides the necessary instructions and API calls to register services manually.