Managing external traffic with application load balancing

Application load balancing is a concept that focuses on routing and balancing traffic based on the seventh layer of the OSI model, known as the application layer. In practice, for web applications this usually means routing based on the URL path or query parameters. For example, a request to /app/account/balance will be routed to a node running the application and serve the account balance while /html/about-us will be routed to a static GitHub Pages website.

These destinations are referred to as targets and are part of a target group, which can contain one or many targets. Targets can be the final destination for a request and have an application running on the node directly serving the response. In cases where orchestration tools like Nomad or Kubernetes are used, these targets can be nodes running several services, each on a different port.

The Load Balancing with NGINX tutorial shows you how to configure one instance of Nginx to balance traffic between three web application instances, each running on a different node. This tutorial extends that knowledge and teaches you how to add an external application load balancer (ALB) to both allow Internet traffic to your internal services and further balance traffic to different instances of Nginx. In this way, the ALB is responsible for forwarding traffic based on which application service is being requested, and Nginx is responsible for balancing traffic between the multiple instances of the same application service.

Though Nginx was chosen as the internal load balancer for this scenario, other load balancing applications like Fabio, HAProxy, and Traefik can also be used.

In this tutorial, you will create a Nomad cluster, deploy an example web application, deploy Nginx to balance requests to the webapp, and create an external ALB to forward traffic to Nginx. You will then add custom rules to the ALB allowing it to forward requests to the different webapp services based on the URL path parameter.

Architecture overview

Infrastructure diagram

The cluster created in this tutorial consists of three Nomad server nodes and five Nomad client nodes. The Nomad clients are split into two logical datacenters: three of them are in dc1 and two are in dc2. Additionally, the Nomad clients contain custom metadata identifying which hypothetical services should be run on them: the clients in dc1 have a metadata tag of api for the API service while those in dc2 have a payments tag for the payments service. A real-world explanation of splitting these services based on client attributes like this might be that clients with the payments tag have faster storage and higher memory resources enabling quicker processing of payments.

datacenter = "dc1"

client {
  meta {
    node-name = "nomad-client-1"
    service-client = "api"
  }
}

datacenter = "dc2"

client {
  meta {
    node-name = "nomad-targeted-client-1"
    service-client = "payments"
  }
}

Application diagram

The ALB listens for user requests on port 80 and forwards them to the Nomad clients on port 8080, which is where the Nginx service is listening. Nginx then forwards the request to an instance of the web application running on one of the clients in the same Nomad datacenter as it. The port for the web application is a dynamic port in the range of 20000 to 32000 and is allocated by the Nomad scheduler.

Prerequisites

For this tutorial, you will need:

• Packer 1.7.7 or later installed locally
• Terraform 1.0.5 or later installed locally
• Nomad 1.1.5 or later installed locally
• An AWS account with credentials set as local environment variables and an AWS keypair

Clone the example repository

The example repository contains configuration files for creating a Nomad cluster on AWS. It uses Consul for the initial setup of the Nomad servers and clients, enables Access Control Lists for Consul and Nomad, and creates an elastic load balancer for easier access to Consul and Nomad.

Clone the example repository.

$ git clone https://github.com/hashicorp/learn-nomad-external-alb

Navigate to the cloned repository folder.

$ cd learn-nomad-external-alb

Check out the v0.1 tag of the repository as a local branch named nomad-alb.

$ git checkout v0.1 -b nomad-alb

Review repository contents

The shared top level directory contains configuration files and scripts for building the Amazon Machine Image (AMI), the respective ACL policy files for Consul and Nomad, and the agent configuration files for running Consul and Nomad on the AWS instances.

The shared/config directory contains configuration files for the Consul and Nomad agents. Those configuration files contain capitalized placeholder strings that get replaced with proper values during the provisioning process. For example, in the nomad_client.hcl agent file, this includes the datacenter, values for the Consul token, and other custom metadata attributes.

data_dir  = "/opt/nomad/data"
bind_addr = "0.0.0.0"
datacenter = "DATACENTER"

# Enable the client
client {
  enabled = true
  options {
    "driver.raw_exec.enable"    = "1"
    "docker.privileged.enabled" = "true"
  }
  meta {
    node-name = "SERVER_NAME"
    service-client = "SERVICE_CLIENT"
  }
}

acl {
  enabled = true
}

consul {
  address = "127.0.0.1:8500"
  token = "CONSUL_TOKEN"
}

## …

The aws top level directory contains the Packer build file used to create and publish the AMI to AWS as well as the Terraform configurations and additional files necessary for the infrastructure provisioning process. The post-setup.sh script here retrieves the Nomad token from the Consul KV store once the cluster is up and running. Lastly the nomad folder contains the Nomad job spec files for the demo web application and Nginx.

The user-data-client.sh script replaces the placeholder strings in the Nomad client agent file referenced above with actual values based on the AWS metadata tags for the instance.

Note that the nomad_consul_token_secret value will be placed there by Terraform during the provisioning process as it renders the file.

#!/bin/bash

set -e

exec > >(sudo tee /var/log/user-data.log|logger -t user-data -s 2>/dev/console) 2>&1
sudo bash /ops/shared/scripts/client.sh "aws" "${retry_join}" "${nomad_binary}"

NOMAD_HCL_PATH="/etc/nomad.d/nomad.hcl"

sed -i "s/CONSUL_TOKEN/${nomad_consul_token_secret}/g" $NOMAD_HCL_PATH

# Place the AWS instance name as metadata on the
# client for targeting workloads
AWS_SERVER_TAG_NAME=$(curl http://169.254.169.254/latest/meta-data/tags/instance/Name)
sed -i "s/SERVER_NAME/$AWS_SERVER_TAG_NAME/g" $NOMAD_HCL_PATH

# Put targeted nodes in a different datacenter
# and add service_client meta tag
if [[ $AWS_SERVER_TAG_NAME =~ "targeted" ]]; then
    sed -i "s/DATACENTER/dc2/g" $NOMAD_HCL_PATH
    sed -i "s/SERVICE_CLIENT/payments/g" $NOMAD_HCL_PATH
else
    sed -i "s/DATACENTER/dc1/g" $NOMAD_HCL_PATH
    sed -i "s/SERVICE_CLIENT/api/g" $NOMAD_HCL_PATH
fi

sudo systemctl restart nomad

The user-data-server.sh script handles the bootstrapping of the ACL systems for both Consul and Nomad and saves the Nomad user token to the Consul KV store for temporary storage. The post-setup.sh script deletes the token from Consul KV once it's been retrieved and saved locally.

#!/bin/bash

## …

ACL_DIRECTORY="/ops/shared/config"
CONSUL_BOOTSTRAP_TOKEN="/tmp/consul_bootstrap"
NOMAD_BOOTSTRAP_TOKEN="/tmp/nomad_bootstrap"
NOMAD_USER_TOKEN="/tmp/nomad_user_token"

## …

# Bootstrap consul ACLs
consul acl bootstrap | grep -i secretid | awk '{print $2}' > $CONSUL_BOOTSTRAP_TOKEN

if [ $? -eq 0 ]; then
    consul acl policy create -name 'nomad-auto-join' -rules="@$ACL_DIRECTORY/consul-acl-nomad-auto-join.hcl" -token-file=$CONSUL_BOOTSTRAP_TOKEN

    consul acl role create -name "nomad-auto-join" -description "Role with policies necessary for nomad servers and clients to auto-join via Consul." -policy-name "nomad-auto-join" -token-file=$CONSUL_BOOTSTRAP_TOKEN

    consul acl token create -accessor=${nomad_consul_token_id} -secret=${nomad_consul_token_secret} -description "Nomad server/client auto-join token" -role-name nomad-auto-join -token-file=$CONSUL_BOOTSTRAP_TOKEN

    # Wait for nomad servers to come up
    sleep 30

    # Bootstrap nomad ACLs
    nomad acl bootstrap | grep -i secret | awk -F '=' '{print $2}' | xargs > $NOMAD_BOOTSTRAP_TOKEN

    nomad acl policy apply -token $(cat $NOMAD_BOOTSTRAP_TOKEN) -description "Policy to allow reading of agents and nodes and listing and submitting jobs in all namespaces." node-read-job-submit $ACL_DIRECTORY/nomad-acl-user.hcl

    nomad acl token create -token $(cat $NOMAD_BOOTSTRAP_TOKEN) -name "read-token" -policy node-read-job-submit | grep -i secret | awk -F "=" '{print $2}' | xargs > $NOMAD_USER_TOKEN

    # Write user token to kv
    consul kv put -token-file=$CONSUL_BOOTSTRAP_TOKEN nomad_user_token $(cat $NOMAD_USER_TOKEN)
fi

The aws/nomad/webapp.nomad job spec file runs two services of the demo web application: one acting as the api and the other acting as the payments service. These services are configured to run only on the instances that have the corresponding meta.service-client attribute of the Nomad client, which was placed in the agent file by the user-data-client.sh script mentioned above. This is specified in the constraint attribute.

job "demo-webapp" {
  datacenters = ["dc1","dc2"]

  group "api-demo" {
    constraint {
      attribute = "${meta.service-client}"
      operator  = "="
      value     = "api"
    }
    count = 3
      ## …
    }

    service {
      name = "api-service"
      port = "http"

      ## …
    }

    ## ..
  }
  group "payments-demo" {
    constraint {
      attribute = "${meta.service-client}"
      operator  = "="
      value     = "payments"
    }
    count = 2
    ## …

    service {
      name = "payments-service"
      port = "http"

      ## …
    }

    ## …
  }
}

Finally, the aws/nomad/nginx.nomad job spec file runs two instances of Nginx to balance traffic between the different clients associated with the simulated api and payments services – one Nginx for each respective service. It retrieves the IP addresses of the clients running the service by querying Consul. The service name used in the template nginx configuration file matches the name of the service defined in the aws/nomad/webapp.nomad file.

The nginx services also use the constraint attribute mentioned above to run on specific clients.

job "nginx" {
  datacenters = ["dc1", "dc2"]

  group "nginx-api" {
    constraint {
      attribute = "${meta.service-client}"
      operator  = "="
      value     = "api"
    }
    count = 1

    ## …

    task "nginx" {
      ## …

      template {
        data = <<EOF
upstream backend {
{{ range service "api-service" }}
  server {{ .Address }}:{{ .Port }};
{{ else }}server 127.0.0.1:65535; # force a 502
{{ end }}
}

server {
   listen 8080;

   location / {
      proxy_pass http://backend;
   }
}
EOF

        ## …
      }
    }
  }
  group "nginx-payments" {
    constraint {
      attribute = "${meta.service-client}"
      operator  = "="
      value     = "payments"
    }
    count = 1

    ## …

    task "nginx" {
      ## …

      template {
        data = <<EOF
upstream backend {
{{ range service "payments-service" }}
  server {{ .Address }}:{{ .Port }};
{{ else }}server 127.0.0.1:65535; # force a 502
{{ end }}
}

server {
   listen 8080;

   location / {
      proxy_pass http://backend;
   }
}
EOF

        ## …
      }
    }
  }
}

Create the Nomad cluster

Build the AWS Machine Image (AMI)

Navigate to the aws directory.

$ cd aws

Be sure to set your AWS environment variables as Packer uses these to build the image and register the AMI in AWS.

$ export AWS_ACCESS_KEY_ID=<YOUR_ACCESS_KEY> && export AWS_SECRET_ACCESS_KEY=<YOUR_SECRET_KEY>

Initialize Packer to have it retrieve the required plugins.

$ packer init image.pkr.hcl

Then build the image.

$ packer build image.pkr.hcl
Build 'amazon-ebs' finished after 14 minutes 32 seconds.

==> Wait completed after 14 minutes 32 seconds

==> Builds finished. The artifacts of successful builds are:
--> amazon-ebs: AMIs were created:
us-east-1: ami-0445eeea5e1406960

Provision the Nomad cluster

Open the aws/terraform.tfvars file with your text editor and update the key_name variable with the name of your AWS keypair and the ami variable with the value output from the Packer build command above. These are the only required variables that need to be updated but you can modify the other values if you want to provision in a different region or change the cluster size, for example. Save the file.

Open your terminal and use the built-in uuid() function of the Terraform console to generate the required UUIDs for the token's credentials.

$ export TF_VAR_nomad_consul_token_id=$(echo 'uuid()' | terraform console | tr -d '"')

$ export TF_VAR_nomad_consul_token_secret=$(echo 'uuid()' | terraform console | tr -d '"')

$ terraform console
> uuid()
> "a90a52ae-bcb7-e38a-5fe9-6ac084b37078"
> uuid()
"d14d6a73-a0f1-508d-6d64-6b0f79e5cb44"
> exit

nomad_consul_token_id = "a90a52ae-bcb7-e38a-5fe9-6ac084b37078"
nomad_consul_token_secret = "d14d6a73-a0f1-508d-6d64-6b0f79e5cb44"

Initialize Terraform to have it retrieve any required plugins and set up the workspace.

$ terraform init

Provision the resources. Respond yes to the prompt to confirm the operation and then press Enter to start the process. This will take a few minutes to provision.

$ terraform apply

Apply complete! Resources: 25 added, 0 changed, 0 destroyed.

Outputs:

IP_Addresses = <<EOT

Client public IPs: 44.202.254.116, 54.89.162.70, 18.234.36.69

Targeted client public IPs: 54.87.30.59, 3.89.255.114

Server public IPs: 3.95.186.208, 18.206.252.210, 3.86.187.77

The Consul UI can be accessed at http://nomad-server-lb-741030279.us-east-1.elb.amazonaws.com:8500/ui
with the bootstrap token: 233c8af2-65ad-236c-0f1a-b3e2903b61a3

Once Terraform finishes provisioning the resources, verify that the services are healthy by navigating to the Consul UI in your web browser with the link in the Terraform output.

Click on the Log in button and use the bootstrap token secret from the Terraform output to login.

Click on the Nodes page from the left navigation. Note that there are 8 healthy nodes, which include the 3 servers and 5 clients created by Terraform.

Next, run the post-setup.sh script. This script retrieves the Nomad bootstrap token from the Consul KV store, saves it locally to nomad.token, and then deletes the token from the Consul KV store.

$ ./post-setup.sh
The Nomad user token has been saved locally to nomad.token and deleted from the Consul KV store.

Set the following environment variables to access your Nomad cluster with the user token created during setup:

export NOMAD_ADDR=$(terraform output -raw lb_address_consul_nomad):4646
export NOMAD_TOKEN=$(cat nomad.token)

The Nomad UI can be accessed at http://nomad-server-lb-741030279.us-east-1.elb.amazonaws.com:4646/ui
with the bootstrap token: 1cd623c1-c935-1aa2-b80c-bd61e72bfac9

Copy the export commands from the output, paste them into your terminal, and press Enter.

$ export NOMAD_ADDR=$(terraform output -raw lb_address_consul_nomad):4646 && export NOMAD_TOKEN=$(cat nomad.token)

Finally, verify connectivity to the cluster by running a Nomad command.

$ nomad node status
ID        DC   Name              Class   Drain  Eligibility  Status
44664b5d  dc2  ip-172-31-30-145  <none>  false  eligible     ready
5c5caa5c  dc1  ip-172-31-30-28   <none>  false  eligible     ready
5705660c  dc1  ip-172-31-24-223  <none>  false  eligible     ready
a7830be9  dc2  ip-172-31-25-227  <none>  false  eligible     ready
16aac29f  dc1  ip-172-31-86-58   <none>  false  eligible     ready

Be aware that you can also navigate to the Nomad UI in your web browser with the link in the post-setup.sh script output and login with the bootstrap token provided by setting the Secret ID to the token's value, and then clicking on the Clients page from the left navigation.

Run the application job

Open your terminal and submit the demo web application job.

$ nomad job run nomad/webapp.nomad
## …
    ID          = 13941ecc
    Job ID      = demo-webapp
    Job Version = 0
    Status      = successful
    Description = Deployment completed successfully
    
    Deployed
    Task Group     Desired  Placed  Healthy  Unhealthy  Progress Deadline
    api-demo       3        3       3        0          2022-02-16T14:58:51Z
    payments-demo  2        2       2        0          2022-02-16T14:58:52Z

View information about the web application job with the status command.

$ nomad job status demo-webapp
ID            = demo-webapp
Name          = demo-webapp
Submit Date   = 2022-02-16T09:48:06-05:00
Type          = service
Priority      = 50
Datacenters   = dc1,dc2
Namespace     = default
Status        = running
Periodic      = false
Parameterized = false

## …

Latest Deployment
ID          = 13941ecc
Status      = successful
Description = Deployment completed successfully

## …

Allocations
ID        Node ID   Task Group     Version  Desired  Status   Created    Modified
12994155  4a9a3645  api-demo       0        run      running  1m51s ago  1m8s ago
8aa28bbc  4056a16a  payments-demo  0        run      running  1m51s ago  1m5s ago
8d8a96e3  dee493d5  api-demo       0        run      running  1m51s ago  1m6s ago
ba2dbd14  b97489a2  api-demo       0        run      running  1m51s ago  1m6s ago
e757a6b8  d53ce7ce  payments-demo  0        run      running  1m51s ago  1m6s ago

Navigate back to the Nomad UI in your web browser, click on the Jobs link in the left navigation, and then the demo-webapp job to see similar information.

The application instances are ready to handle requests and in the next section you'll use Nginx to balance those incoming requests between the instances.

Run the internal Nginx load balancer job

The Nginx job installs one instance of Nginx on one node in both datacenters. Nginx listens on port 8080 and balances traffic to the web application running on the clients in the same datacenter. Nginx uses consul-template to retrieve the client IPs and ports from the demo-webapp services registered as part of the demo-webapp job.

Open your terminal and submit the Nginx job.

$ nomad job run nomad/nginx.nomad
## …
    ID          = 5ce769a0
    Job ID      = nginx
    Job Version = 0
    Status      = successful
    Description = Deployment completed successfully
    
    Deployed
    Task Group      Desired  Placed  Healthy  Unhealthy  Progress Deadline
    nginx-api       1        1       1        0          2022-02-16T15:11:47Z
    nginx-payments  1        1       1        0          2022-02-16T15:11:48Z

The Nginx instances are filling the role of internal load balancer to the webapp services running within the cluster and will become accessible externally with the application load balancer you'll create in the next section.

Create the application load balancer

Create a new file named alb.tf in the aws directory with the other Terraform configuration files. Copy and paste the contents below into the file and save it.

data "aws_subnet_ids" "default_subnets" {
    vpc_id = data.aws_vpc.default.id
}

resource "aws_lb" "nomad_clients_ingress" {
  name               = "nomad-ingress-alb"
  internal           = false
  load_balancer_type = "application"
  security_groups    = [aws_security_group.clients_ingress_sg.id]
  subnets            = data.aws_subnet_ids.default_subnets.ids
}

resource "aws_lb_listener" "nomad_listener" {
  load_balancer_arn = aws_lb.nomad_clients_ingress.id
  port              = 80

  default_action {
    type             = "forward"
    
    forward {
      target_group {
        arn = aws_lb_target_group.nomad_clients.arn
      }
      target_group {
        arn = aws_lb_target_group.nomad_clients_targeted.arn
      }
    }
  }
}

# nomad clients for api
resource "aws_lb_target_group" "nomad_clients" {
  name     = "nomad-clients"
  # App listener port
  port     = 8080 
  protocol = "HTTP"
  vpc_id   = data.aws_vpc.default.id

  health_check {
    port = 8080
    path = "/"
    # Mark healthy if redirected
    matcher = "200,301,302"
  }
}

resource "aws_lb_target_group_attachment" "nomad_clients" {
  count = var.client_count
  target_group_arn = aws_lb_target_group.nomad_clients.arn
  target_id = element(split(",", join(",", aws_instance.client.*.id)), count.index)
  port             = 8080
}

# nomad clients for payments
resource "aws_lb_target_group" "nomad_clients_targeted" {
  name     = "nomad-clients-targeted"
  # App listener port
  port     = 8080 
  protocol = "HTTP"
  vpc_id   = data.aws_vpc.default.id

  health_check {
    port = 8080
    path = "/"
    # Mark healthy if redirected
    matcher = "200,301,302"
  }
}

resource "aws_lb_target_group_attachment" "nomad_clients_targeted" {
  count = var.targeted_client_count
  target_group_arn = aws_lb_target_group.nomad_clients_targeted.arn
  target_id = element(split(",", join(",", aws_instance.targeted_client.*.id)), count.index)
  port             = 8080
}

output "alb_address" {
    value = "http://${aws_lb.nomad_clients_ingress.dns_name}:80"
}

This creates an application load balancer (ALB) with two target groups containing the Nomad client nodes. The first group contains the clients in the dc1 datacenter that have the api meta tag while the second group contains the clients in dc2 with the payments tag. The ALB listens on port 80 and forwards requests to the Nomad clients on port 8080 where the Nginx service is listening. The target groups each have an equal weighting for requests which means that incoming requests will alternate between being sent to the first group and the second.

Apply the changes with Terraform and respond yes to the prompt to confirm the operation. This will take a few minutes.

$ terraform apply
Apply complete! Resources: 9 added, 0 changed, 0 destroyed.

Outputs:

IP_Addresses = <<EOT

Client public IPs: 3.80.134.141, 52.207.228.149, 54.225.34.175

Targeted client public IPs: 3.88.132.1, 54.89.250.120

Server public IPs: 54.158.105.32, 34.227.116.136, 34.230.47.119

The Consul UI can be accessed at http://nomad-server-lb-227540418.us-east-1.elb.amazonaws.com:8500/ui
with the bootstrap token: 5978db4b-40e7-da10-60aa-cd9463d93d24

EOT
alb_address = "http://nomad-ingress-alb-307671706.us-east-1.elb.amazonaws.com:80"
consul_bootstrap_token_secret = "5978db4b-40e7-da10-60aa-cd9463d93d24"
lb_address_consul_nomad = "http://nomad-server-lb-227540418.us-east-1.elb.amazonaws.com"

Next, verify that the application load balancer is working correctly.

$ while true; do curl $(terraform output -raw alb_address); done
Welcome! You are on node 172.31.23.186:30489
Welcome! You are on node 172.31.80.235:24980
Welcome! You are on node 172.31.93.179:26052
Welcome! You are on node 172.31.30.145:26789
Welcome! You are on node 172.31.23.186:30489
Welcome! You are on node 172.31.93.179:26052
Welcome! You are on node 172.31.30.145:26789
Welcome! You are on node 172.31.23.186:30489

$ terraform output alb_address

Target specific clients

You may want to target a specific client node or group of nodes based on attributes like physical resource configuration (presence of GPUs, higher memory, larger and/or faster storage) or software configuration (presence of a certain part of an application like a DB layer). In these cases, an application load balancer can help direct traffic to the appropriate nodes based on the layer 7 properties like the URL path.

To illustrate this type of scenario, the cluster has been set up with nodes separated into two logical datacenters that each contain a specific piece of an application: the api and payments services.

Currently the ALB directs traffic to both groups of clients evenly. In the next section, each group will be mapped to a specific URL path related to their part of the application.

Update the ALB configuration

Copy the contents below, add them to the end of the alb.tf file, and save the file.

resource "aws_lb_listener_rule" "nomad_clients" {
  listener_arn = aws_lb_listener.nomad_listener.arn

  action {
    type             = "forward"
    target_group_arn = aws_lb_target_group.nomad_clients.arn
  }

  condition {
    path_pattern {
      values = ["/api"]
    }
  }
}

resource "aws_lb_listener_rule" "nomad_clients_targeted" {
  listener_arn = aws_lb_listener.nomad_listener.arn

  action {
    type             = "forward"
    target_group_arn = aws_lb_target_group.nomad_clients_targeted.arn
  }

  condition {
    path_pattern {
      values = ["/payments"]
    }
  }
}

This will map the /api path to the Nomad clients in dc1 with the api metadata tag and /payments to the ones in dc2 with the payments tag.

Open your terminal and apply the changes with Terraform. Respond yes to the prompt to confirm the operation.

$ terraform apply

With these changes, any requests to the ALB on the /api path will be forwarded to the Nginx service running in the dc1 datacenter and served by the web application service running in the same datacenter. Requests to the /payments path will be forwarded to the Nginx and web application services running in dc2. Finally, any other requests will be split evenly between both Nginx services and their respective web application services – this is just used as an illustration and may not make sense in your application depending on the configuration of that application.

Run the curl command below which specifies the service path and note that now only certain clients respond based on the path in the request. Verify this by checking the node addresses in the output against the client list in the Nomad UI.

Query the /api path. Note the three unique addresses and how they match up to the Nomad clients in dc1.

$ while true; do curl $(terraform output -raw alb_address)/api; done
Welcome! You are on node 172.31.86.134:21854
Welcome! You are on node 172.31.23.186:30489
Welcome! You are on node 172.31.30.145:26789
Welcome! You are on node 172.31.86.134:21854
Welcome! You are on node 172.31.23.186:30489

Query the /payments path. Note the two unique addresses and how they match up to the Nomad clients in dc2.

$ while true; do curl $(terraform output -raw alb_address)/payments; done
Welcome! You are on node 172.31.80.235:24980
Welcome! You are on node 172.31.93.179:26052
Welcome! You are on node 172.31.80.235:24980
Welcome! You are on node 172.31.93.179:26052
Welcome! You are on node 172.31.80.235:24980
Welcome! You are on node 172.31.93.179:26052

Cleanup

Run terraform destroy to clean up your provisioned infrastructure. Respond yes to the prompt to confirm the operation.

$ terraform destroy
## …
aws_instance.server[0]: Destruction complete after 31s
aws_instance.server[2]: Destruction complete after 31s
aws_instance.server[1]: Still destroying... [id=i-0af70516a51d3fe56, 40s elapsed]
aws_instance.server[1]: Destruction complete after 41s
aws_iam_instance_profile.instance_profile: Destroying... [id=nomad20220216173959430200000002]
aws_security_group.primary: Destroying... [id=sg-03f80cb564451a27b]
aws_iam_instance_profile.instance_profile: Destruction complete after 0s
aws_iam_role.instance_role: Destroying... [id=nomad20220216173958373800000001]
aws_security_group.primary: Destruction complete after 0s
aws_security_group.server_lb: Destroying... [id=sg-0f0ede8ee1f14e9db]
aws_iam_role.instance_role: Destruction complete after 1s
aws_security_group.server_lb: Destruction complete after 1s

Destroy complete! Resources: 27 destroyed.

Your AWS account still has the AMI and its S3-stored snapshots, which you may be charged for depending on your other usage. Delete the AMI and snapshots stored in your S3 buckets.

In your us-east-1 AWS account, deregister the AMI by selecting it, clicking on the Actions button, then the Deregister AMI option, and finally confirm by clicking the Deregister AMI button in the confirmation dialog.

Delete the snapshots by selecting the snapshots, clicking on the Actions button, then the Delete snapshot option, and finally confirm by clicking the Delete button in the confirmation dialog.

Next steps

In this tutorial you created a Nomad cluster, deployed an example web application, deployed Nginx to balance requests to the web application, created an external ALB to forward traffic to Nginx, and modified the ALB to forward requests to different instances of Nginx based on the request path in the URL.

For more information, check out the folowing resources.

• Learn more about the benefits of an ALB
• Read more about the integration between Consul and Nomad
• Try swapping out Nginx for another internal load balancing application