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Alpha: External workloads (VMs)

Onboard external workloads, such as virtual or bare metal machines, to an Istio service mesh in your Gloo Mesh Enterprise environment.

warning

Onboarding external workloads to Gloo Mesh Enterprise is an alpha feature. As of 2.4.0, this feature is tested for onboarding VMs that run in Google Cloud Platform (GCP) and Amazon Web Services (AWS). Alpha features are likely to change, are not fully tested, and are not supported for production. For more information, see Gloo feature maturity.

Onboard external workloads, such as virtual machines, to an Istio service mesh in your Gloo Mesh Enterprise environment.

About

As you build your Gloo Mesh Enterprise environment, you might want to add a virtual machine to your setup. For example, you might run an app or service in a VM that must communicate with services in the Istio service mesh that runs in your Kubernetes cluster.

To onboard your VM into the service mesh, you deploy three agents to your VM: an Istio sidecar agent, a SPIRE agent, and an OpenTelemetry (OTel) collector agent.

Istio
By adding an Istio sidecar agent to your VM, you can achieve fully bi-directional communication between apps in your cluster’s service mesh, and apps in the VM. Because all communication between services in the workload cluster and services in the VM goes through the workload cluster’s east-west gateway, the communication is mTLS-secured. Additionally, you get the added benefit of applying Gloo resources to the apps on your VM, such as Gloo traffic policies.

SPIRE
To securely identify a virtual machine, Gloo Mesh Enterprise uses SPIRE, a production-ready implementation of the SPIFFE APIs. SPIRE issues SPIFFE Verifiable Identity Documents (SVIDs) to workloads and verifies the SVIDs of other workloads. In this guide, you deploy a SPIRE server to your workload cluster and a SPIRE agent to the VM. To onboard the VM into your Gloo setup, the SPIRE agent must authenticate and verify itself when it first connects to the server, which is known as node attestation. During node attestation, the agent and server together verify the identity of the node that the agent is deployed to. This process ensures that the workload cluster and your VM can securely connect to each other.

OTel
To ensure that metrics can be collected from the VM in the same way that they are collected from workload clusters, you deploy an OTel collector agent to the VM. The collector sends metrics through the workload cluster’s east-west gateway to the OTel gateway on the management cluster. Additionally, as part of this guide, you enable the collector agents to gather metadata about the compute instances that they are deployed to. This compute instance metadata helps you better visualize your Gloo Mesh Enterprise setup across your cloud provider infrastructure network. For more information about metrics collection in Gloo Platform, see Set up the Gloo OTel pipeline.

Before you begin

Install CLI tools

Install the following CLI tools.

helm, the Kubernetes package manager.
kubectl, the Kubernetes command line tool. Download the kubectl version that is within one minor version of the Kubernetes clusters you plan to use.
istioctl, the Istio command line tool. Important: Versions 1.17.4 through 1.18.7-patch3 are supported in Gloo Mesh Enterprise for onboarding VMs.
meshctl, the Gloo command line tool for bootstrapping Gloo Mesh Enterprise, registering clusters, describing configured resources, and more. Be sure to download version 2.4.16, which uses the latest Gloo Mesh installation values.
```
  curl -sL https://run.solo.io/meshctl/install | GLOO_MESH_VERSION=v2.4.16 sh -
export PATH=$HOME/.gloo-mesh/bin:$PATH
  
```
Install the following CLI tools, depending on your infrastructure platform.
- GCP: gcloud, the Google Cloud command line tool.
- AWS:
  - aws, the AWS command line tool.
  - eksctl, the Amazon EKS command line tool.

Overview

This guide walks you through the following general steps:

Create compute resources: In your cloud provider, create two Kubernetes clusters and a VM on the same network subnet. Additionally, configure IAM permissions for the SPIRE server you later deploy to the workload cluster.
Set up the management cluster: Deploy the Gloo management plane to the management cluster. The installation settings enable the onboarding of external workloads to the service mesh.
Set up the workload cluster: Set up your workload cluster to communicate with the management cluster and your VM, including deploying test apps, deploying Istio, and registering the workload cluster with the Gloo management plane. The registration settings include deploying a SPIRE server to the workload cluster, and using PostgreSQL as the default datastore for the SPIRE server.
Onboard the VM: Onboard the VM to your Gloo Mesh Enterprise environment by generating a bootstrap bundle that installs the Istio sidecar, OpenTelemetry (OTel) collector, and SPIRE agents on the VM.
Test connectivity: Verify that the onboarding process was successful by testing the bi-directional connection between the apps that run in the service mesh in your workload cluster and a test app on your VM.
Launch the UI (optional): To visualize the connection to your VM in your Gloo Mesh Enterprise setup, you can lauch the Gloo UI.

For more information about onboarding VMs to a service mesh, see the high-level architectural overview of Istio’s virtual machine integration.

Step 1: Create compute resources

In your cloud provider, create the virtual machine, management cluster, and at least one workload cluster, and configure IAM permissions for the SPIRE server.

Save your GCP project ID and the VPC name in environment variables.

  export PROJECT=<gcp_project_id>
export VPC=<gcp_network_of_the_vm>

Create or use existing Google Kubernetes Engine (GKE) clusters.
1. Create or use at least two clusters. In subsequent steps, you deploy the Gloo management plane to one cluster, and the Gloo data plane and an Istio service mesh to the other cluster.
  - Enable Workload Identity for the workload cluster. Workload Identity allows the Kubernetes service account for the SPIRE server in your workload cluster to act as a GCP IAM service account. The SPIRE server pod can then automatically authenticate as the IAM service account when accessing your VM.
  - Note: The cluster name must be alphanumeric with no special characters except a hyphen (-), lowercase, and begin with a letter (not a number).
  - For more information, see the System requirements.
2. Set the names of your clusters from your infrastructure provider.
```
  export ${MGMT_CLUSTER}=<mgmt-cluster-name>
export REMOTE_CLUSTER=<workload-cluster-name>
  
```
3. Save the kubeconfig contexts for your clusters. Run kubectl config get-contexts, look for your cluster in the CLUSTER column, and get the context name in the NAME column. Note: Do not use context names with underscores. The generated certificate that connects workload clusters to the management cluster uses the context name as a SAN specification, and underscores in SAN are not FQDN compliant. You can rename a context by running kubectl config rename-context "<oldcontext>" <newcontext>.
```
  export MGMT_CONTEXT=<management-cluster-context>
export REMOTE_CONTEXT=<workload-cluster-context>
  
```

Create a virtual machine to connect to your service mesh.

Create a virtual machine that meets the following requirements.
- Currently, Debian and RPM images are supported.
- The VM must be connected to the same subnet as your workload cluster.

For testing connectivity, allow all outbound traffic, and in the associated VPC firewall rules for your VM, permit inbound TCP traffic on ports 22 (SSH access), 80 (HTTP traffic), and 5000 (sample app). Example commands:

  gcloud compute --project=${PROJECT} firewall-rules create ${VPC}-allow-ssh --direction=INGRESS --priority=1000 --network=${VPC} --action=ALLOW --rules=tcp:22 --source-ranges=0.0.0.0/0 --target-tags=http-server
gcloud compute --project=${PROJECT} firewall-rules create ${VPC}-allow-http --direction=INGRESS --priority=1000 --network=${VPC} --action=ALLOW --rules=tcp:80 --source-ranges=0.0.0.0/0 --target-tags=http-server
gcloud compute --project=${PROJECT} firewall-rules create ${VPC}-allow-test-app --direction=INGRESS --priority=1000 --network=${VPC} --action=ALLOW --rules=tcp:5000 --source-ranges=0.0.0.0/0 --target-tags=http-server

Save the VM instance name and zone in an environment variable.

  export VM_NAME=<vm_instance_name>
export VM_ZONE=<vm_instance_zone>

Create an IAM service account in GCP to allow Gloo components to obtain credentials for authentication to Google Cloud API. This is required for Gloo Mesh Enterprise to be able to attest the identity of the compute instances before they join the mesh, and to collect instance metadata from VMs and Kubernetes node instances for telemetry to help you better visualize your Gloo setup across networks and heterogeneous environments. The IAM service account with required permissions must be attached to the VM instances, and be associated with select Gloo Kubernetes service accounts via workload identity.

Create an IAM service account in GCP named GlooMesh.

  gcloud iam service-accounts create GlooMesh --project ${PROJECT}

Create an IAM role that gives the permission to fetch a given VM instance and API access tokens in your project.

  gcloud iam roles create GlooComputeViewer --project ${PROJECT} \
  --title "Gloo compute viewer" \
  --description "read compute.instances.get" \
  --permissions compute.instances.get,iam.serviceAccounts.getAccessToken

Bind the role to the GlooMesh GCP IAM service account.

  gcloud projects add-iam-policy-binding ${PROJECT} \
  --role "projects/${PROJECT}/roles/GlooComputeViewer" \
  --member "serviceAccount:GlooMesh@${PROJECT}.iam.gserviceaccount.com"

Allow the Gloo Kubernetes service accounts to use workload identity, which allows it to act as the GCP IAM service account to fetch compute instances information and API access tokens.

  gcloud iam service-accounts add-iam-policy-binding GlooMesh@${PROJECT}.iam.gserviceaccount.com \
  --project ${PROJECT} \
  --role roles/iam.workloadIdentityUser \
  --member "serviceAccount:${PROJECT}.svc.id.goog[gloo-mesh/gloo-spire-server]"

gcloud iam service-accounts add-iam-policy-binding GlooMesh@${PROJECT}.iam.gserviceaccount.com \
  --project ${PROJECT} \
  --role roles/iam.workloadIdentityUser \
  --member "serviceAccount:${PROJECT}.svc.id.goog[gloo-mesh/gloo-telemetry-collector]"

Attach the GlooMesh service account to the VM instance.

If you did not create the VM yet, you can attach the service account with this command.

  gcloud compute instances create ${VM_NAME} \
  --zone ${VM_ZONE} \
  --service-account=GlooMesh@${PROJECT}.iam.gserviceaccount.com \
  --scopes=https://www.googleapis.com/auth/cloud-platform

If you already created the VM, be sure to stop the VM before you attach the service account. Then, restart the VM.

  gcloud compute instances stop ${VM_NAME} --zone ${VM_ZONE}

gcloud compute instances set-service-account ${VM_NAME} \
  --zone ${VM_ZONE} \
  --service-account=GlooMesh@${PROJECT}.iam.gserviceaccount.com  \
  --scopes=https://www.googleapis.com/auth/cloud-platform

gcloud compute instances start ${VM_NAME} --zone ${VM_ZONE}

Create or use existing Amazon Elastic Kubernetes Service (EKS) clusters.
1. Create or use at least two clusters. In subsequent steps, you deploy the Gloo management plane to one cluster, and the Gloo data plane and an Istio service mesh to the other cluster.
  - Note: The cluster name must be alphanumeric with no special characters except a hyphen (-), lowercase, and begin with a letter (not a number).
  - For more information, see the System requirements.
2. Set the names of your clusters from your infrastructure provider.
```
  export ${MGMT_CLUSTER}=<mgmt-cluster-name>
export REMOTE_CLUSTER=<workload-cluster-name>
  
```
3. Save the kubeconfig contexts for your clusters. Run kubectl config get-contexts, look for your cluster in the CLUSTER column, and get the context name in the NAME column. Note: Do not use context names with underscores. The generated certificate that connects workload clusters to the management cluster uses the context name as a SAN specification, and underscores in SAN are not FQDN compliant. You can rename a context by running kubectl config rename-context "<oldcontext>" <newcontext>.
```
  export MGMT_CONTEXT=<management-cluster-context>
export REMOTE_CONTEXT=<workload-cluster-context>
  
```
4. Create an IAM OIDC provider for the workload cluster. The OIDC provider allows the Kubernetes service account for the SPIRE server in your workload cluster to act as an AWS IAM service account. The SPIRE server pod can then automatically authenticate as the IAM service account when accessing your VM.

Install the required AWS add-ons in your workload cluster.

Save your AWS account ID in an environment variable.

  export ACCOUNT="$(aws sts get-caller-identity --query Account --output text)"

Install the EBS CSI driver required by the persistent volume that the PostgreSQL database uses.

  eksctl create iamserviceaccount \
  --name ebs-csi-controller-sa \
  --namespace kube-system \
  --cluster "${REMOTE_CLUSTER}" \
  --role-name AmazonEKS_EBS_CSI_DriverRole-${REMOTE_CLUSTER} \
  --role-only \
  --attach-policy-arn arn:aws:iam::aws:policy/service-role/AmazonEBSCSIDriverPolicy \
  --approve \
  --override-existing-serviceaccounts

eksctl create addon \
  --name aws-ebs-csi-driver \
  --cluster "${REMOTE_CLUSTER}" \
  --service-account-role-arn "arn:aws:iam::${ACCOUNT}:role/AmazonEKS_EBS_CSI_DriverRole-${REMOTE_CLUSTER}" \
  --force

Install the Load Balancer Controller required to expose load balancer services.

  curl -o /tmp/aws_lb_iam_policy.json https://raw.githubusercontent.com/kubernetes-sigs/aws-load-balancer-controller/v2.4.7/docs/install/iam_policy.json

aws iam create-policy --policy-name AWSLoadBalancerControllerIAMPolicy --policy-document file:///tmp/aws_lb_iam_policy.json

eksctl create iamserviceaccount \
  --name=aws-load-balancer-controller \
  --cluster="${REMOTE_CLUSTER}" \
  --namespace=kube-system \
  --role-name AmazonEKSLoadBalancerControllerRole \
  --attach-policy-arn="arn:aws:iam::${ACCOUNT}:policy/AWSLoadBalancerControllerIAMPolicy" \
  --approve

helm repo add eks https://aws.github.io/eks-charts
helm repo update

helm upgrade -i aws-load-balancer-controller eks/aws-load-balancer-controller \
  --kube-context "${REMOTE_CONTEXT}" \
  -n kube-system \
  --set clusterName="${REMOTE_CLUSTER}" \
  --set serviceAccount.create=false \
  --set serviceAccount.name=aws-load-balancer-controller

Create an EKS security group for the VM.

Get the ID of the AWS VPC that the workload cluster is attached to.

Create a security group for that VPC.

  aws ec2 create-security-group --description "VM test" --group-name <name> --vpc-id <eks_cluster_VPC_ID>

From the output, save the security group ID in an environment variable.
```
  export VM_SG_ID=<security group ID>
  
```

For testing connectivity, allow all outbound traffic, and permit TCP traffic on ports 22 (SSH access), 80 (HTTP traffic), and 5000 (sample app).

  aws ec2 authorize-security-group-ingress --group-id ${VM_SG_ID} --protocol tcp --port 22 --cidr 0.0.0.0/0
aws ec2 authorize-security-group-ingress --group-id ${VM_SG_ID} --protocol tcp --port 80 --cidr 0.0.0.0/0
aws ec2 authorize-security-group-ingress --group-id ${VM_SG_ID} --protocol tcp --port 5000 --cidr 0.0.0.0/0

Create the VM.

Create an EC2 instance that meets the following requirements:

Currently, Debian and RPM images are supported.
The VM must be connected to the same subnet as your workload cluster.

Example command:

  # Create a key pair for SSH
aws ec2 create-key-pair --key-name vmtest --query 'KeyMaterial' --output text > ~/vmtest.pem

# Create the EC2 instance
aws ec2 run-instances --image-id ami-03f65b8614a860c29  --instance-type t3.micro --count 1 --security-group-ids ${VM_SG_ID} --associate-public-ip-address --key-name vmtest --subnet-id <workload_cluster_subnet>

Update the security group for the EKS cluster nodegroup to permit traffic from the VM’s security group.

Create IAM permissions for the SPIRE server service account so that the server can perform node attestation of the VM instance.

Save the following policy configration files.

  cat >spire-server-delegate.json <<EOF
{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "SpireServerDelegate",
      "Effect": "Allow",
      "Action": [
        "ec2:DescribeInstances",
        "iam:GetInstanceProfile"
      ],
      "Resource": "*"
    }
  ]
}
EOF

cat >spire-trust.json <<EOF
{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "AWS": "arn:aws:iam::${ACCOUNT}:root"
      },
      "Action": "sts:AssumeRole",
      "Condition": {}
    }
  ]
}
EOF

cat >spire-server.json <<EOF
{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "SpireServer",
      "Effect": "Allow",
      "Action": "sts:AssumeRole",
      "Resource": "arn:aws:iam::${ACCOUNT}:role/SpireServerDelegate"
    }
  ]
}
EOF

Create an IAM role that allows the SPIRE server to describe the EC2 instances in your account.

  aws iam create-policy --policy-name SpireServerDelegate --policy-document file://spire-server-delegate.json
aws iam create-role --role-name SpireServerDelegate --assume-role-policy-document file://spire-trust.json
aws iam attach-role-policy --policy-arn arn:aws:iam::${ACCOUNT}:policy/SpireServerDelegate --role-name SpireServerDelegate

Create an IAM policy to bind the role to the SPIRE service account that you create in subsequent steps.
```
  aws iam create-policy --policy-name SpireServer --policy-document file://spire-server.json
  
```

Step 2: Set up the management cluster

Install the Gloo Platform management plane in the management cluster. Note that the installation settings included in these steps are tailored for basic setups. For more information about advanced settings, see the setup documentation.

Set your Gloo Mesh Enterprise license key as an environment variable. If you do not have one, contact an account representative. If you prefer to specify license keys in a secret instead, see Licensing. To check your license’s validity, you can run meshctl license check --key $(echo ${GLOO_MESH_LICENSE_KEY} | base64 -w0).
```
  export GLOO_MESH_LICENSE_KEY=<license_key>
  
```
info
If you plan to deploy an ingress gateway to manage ingress traffic to mesh workloads and you want to apply policies, such as rate limits, external authentication, or Web Application Firewalls to that gateway, you must also have a Gloo Mesh Gateway license. Without a Gloo Mesh Gateway license, you can only set up simple routing rules to match and forward traffic to mesh workloads. Save the Gloo Mesh Gateway license key as an additional environment variable.
```
  export GLOO_MESH_GATEWAY_LICENSE_KEY=<license-key>
  
```

Save the following settings in a mgmt-server.yaml Helm values file.

  cat >mgmt-server.yaml <<EOF
common:
  cluster: ${MGMT_CLUSTER}
glooMgmtServer:
  serviceOverrides:
    metadata:
      annotations:
        # Instruct GKE to create a backend service-based
        # external passthrough NLB
        cloud.google.com/l4-rbs: enabled
licensing:
  glooMeshLicenseKey: ${GLOO_MESH_LICENSE_KEY}
EOF

  cat >mgmt-server.yaml <<EOF
common:
  cluster: ${MGMT_CLUSTER}
glooMgmtServer:
  serviceOverrides:
    metadata:
      annotations:
        # AWS-specific annotations for load balancers
        service.beta.kubernetes.io/aws-load-balancer-cross-zone-load-balancing-enabled: "true"
        service.beta.kubernetes.io/aws-load-balancer-nlb-target-type: instance
        service.beta.kubernetes.io/aws-load-balancer-scheme: internet-facing
        service.beta.kubernetes.io/aws-load-balancer-type: external
licensing:
  glooMeshLicenseKey: ${GLOO_MESH_LICENSE_KEY}
EOF

Install the Gloo Platform management plane in your management cluster. This command uses a basic profile to create a gloo-mesh namespace, install the management plane components in your management cluster, such as the management server, and enable the ability to add external workloads to your Gloo environment.
```
  meshctl install \
  --kubecontext ${MGMT_CONTEXT} \
  --version 2.4.16 \
  --profiles mgmt-server \
  --chart-values-file mgmt-server.yaml \
  --set enabledExperimentalApi="{externalworkloads.networking.gloo.solo.io/v2alpha1,spireregistrationentries.internal.gloo.solo.io/v2alpha1}"
  
```

Verify that the management plane pods are running.

  kubectl get pods -n gloo-mesh --context ${MGMT_CONTEXT}

Save the external address and port that were assigned by your cloud provider to the Gloo OpenTelemetry (OTel) gateway load balancer service. The OTel collector agents that collect logs in the workload cluster and in the VM send metrics to this address.

  export TELEMETRY_GATEWAY_IP=$(kubectl get svc -n gloo-mesh gloo-telemetry-gateway --context ${MGMT_CONTEXT} -o jsonpath="{.status.loadBalancer.ingress[0]['hostname','ip']}")
export TELEMETRY_GATEWAY_PORT=$(kubectl -n gloo-mesh get service gloo-telemetry-gateway --context ${MGMT_CONTEXT} -o jsonpath='{.spec.ports[?(@.name=="otlp")].port}')
export TELEMETRY_GATEWAY_ADDRESS=${TELEMETRY_GATEWAY_IP}:${TELEMETRY_GATEWAY_PORT}
echo $TELEMETRY_GATEWAY_ADDRESS

  export TELEMETRY_GATEWAY_HOSTNAME=$(kubectl get svc -n gloo-mesh gloo-telemetry-gateway --context ${MGMT_CONTEXT} -o jsonpath='{.status.loadBalancer.ingress[0].hostname}')
export TELEMETRY_GATEWAY_PORT=$(kubectl -n gloo-mesh get service gloo-telemetry-gateway --context ${MGMT_CONTEXT} -o jsonpath='{.spec.ports[?(@.name=="otlp")].port}')
export TELEMETRY_GATEWAY_ADDRESS=${TELEMETRY_GATEWAY_HOSTNAME}:${TELEMETRY_GATEWAY_PORT}
echo $TELEMETRY_GATEWAY_ADDRESS

Create a workspace that includes relevant namespaces in all clusters, and create workspace settings that enable communication through the east-west gateway. If you do not want to include the gloo-mesh namespace in this demo workspace, create a separate admin workspace for the gloo-mesh namespace, and use the workspace import-export functionality to import the gloo-telemetry-collector Kubernetes service in the gloo-mesh namespace to the application workspace. For more information, see Organize team resources with workspaces.

  kubectl apply --context ${MGMT_CONTEXT} -f- <<EOF
apiVersion: admin.gloo.solo.io/v2
kind: Workspace
metadata:
  name: demo
  namespace: gloo-mesh
spec:
  workloadClusters:
    - name: '*'
      namespaces:
        - name: sleep
        - name: httpbin
        - name: vm-config
        - name: istio-eastwest
        - name: gloo-mesh
---
apiVersion: admin.gloo.solo.io/v2
kind: WorkspaceSettings
metadata:
  name: demo
  namespace: gloo-mesh
spec:
  options:
    eastWestGateways:
    - selector:
        labels:
          istio: eastwestgateway
EOF

Decide on the type of certificates for the Istio installations you deploy to your workload cluster in the next section.
- Default Istio certificates: To use the default self-signed certificates, no further steps are required. When you deploy Istio in the next section, the Istio components use the self-signed certificates by default.
- Custom Istio certificates: To set up your own certificates to deploy Istio, complete the following example steps. These steps show how to use Istio’s certificate generator tool to quickly generate self-signed root and intermediate CA certificates and keys. For more information and advanced certificate setup options, see Istio certificates.
  1. Create the istio-system namespace on the workload cluster, so that the certificate secret can be created in that namespace.
```
  kubectl create namespace istio-system --context ${REMOTE_CONTEXT}
  
```
  2. Navigate to the Istio certs directory.
```
  cd istio-${ISTIO_VERSION}/tools/certs
  
```
  3. Generate a self-signed root CA certificate and private key.
```
  make -f Makefile.selfsigned.mk \
ROOTCA_CN="Solo Root CA" \
ROOTCA_ORG=Istio \
root-ca
  
```
  4. Store the root CA certificate, private key and certificate chain in a Kubernetes secret on the management cluster.
```
  cp root-cert.pem ca-cert.pem
cp root-key.pem ca-key.pem
cp root-cert.pem cert-chain.pem

kubectl --context ${MGMT_CONTEXT} -n gloo-mesh create secret generic my-root-trust-policy.gloo-mesh \
--from-file=./ca-cert.pem \
--from-file=./ca-key.pem \
--from-file=./cert-chain.pem \
--from-file=./root-cert.pem
  
```
  5. Create the root trust policy in the management cluster and reference the root CA Kubernetes secret in the spec.config.mgmtServerCa.secretRef section. You can optionally customize the number of days the root and derived intermediate CA certificates are valid for by specifying the ttlDays in the mgmtServerCA (root CA) and intermediateCertOptions (intermediate CA) of your root trust policy.
    
    The following example policy sets up the root CA with the credentials that you stored in the my-root-trust-policy.gloo-mesh secret. The root CA certificate is valid for 730 days. The intermediate CA certificates that are automatically created by Gloo are valid for 1 day.
```
  kubectl apply --context ${MGMT_CONTEXT} -f- << EOF
apiVersion: admin.gloo.solo.io/v2
kind: RootTrustPolicy
metadata:
  name: root-trust-policy
  namespace: gloo-mesh
spec:
  config:
    intermediateCertOptions:
      secretRotationGracePeriodRatio: 0.1
      ttlDays: 1
    mgmtServerCa:
      generated:
        ttlDays: 730
      secretRef:
         name: my-root-trust-policy.gloo-mesh
         namespace: gloo-mesh
EOF
  
```
  6. Verify that the cacerts Kubernetes secret was created in the istio-system namespace on the workload cluster. This secret represents the intermediate CA and is used by the Istio control plane istiod to issue leaf certificates to the workloads in your service mesh.
```
  kubectl get secret cacerts -n istio-system --context ${REMOTE_CONTEXT}
  
```
  7. Verify the certificate chain for the intermediate CA. Because the intermediate CA was derived from the root CA, the root CA must be listed as the root-cert in the cacerts Kubernetes secret.
    1. Get the root CA certificate from the my-root-trust-policy.gloo-mesh secret on the management cluster.
      kubectl get secret my-root-trust-policy.gloo-mesh -n gloo-mesh -o jsonpath='{.data.ca-cert\.pem}' --context ${MGMT_CONTEXT}| base64 --decode
    2. In each workload cluster, get the root CA certificate that is listed as the root-cert in the cacerts Kubernetes secret.
      kubectl get secret cacerts -n istio-system --context ${REMOTE_CONTEXT} -o jsonpath='{.data.root-cert\.pem}' | base64 --decode
    3. Verify that the root CA certificate that is listed in the intermediate CA secret (8.2) matches the root CA certificate that was created by the Gloo root trust policy (8.1).

Step 3: Set up the workload cluster

Set up your workload cluster to communicate with the management cluster and your VM, including deploying test apps, deploying Istio, and registering the workload cluster with the Gloo management plane.

Deploy test apps

To verify connectivity from the VM to services that run in the workload cluster, deploy the sleep and test sample applications to your workload cluster.

Create the sleep app, and label the sleep namespace for Istio sidecar injection.

  kubectl --context ${REMOTE_CONTEXT} create namespace sleep
kubectl --context ${REMOTE_CONTEXT} label ns sleep istio-injection=enabled
kubectl --context ${REMOTE_CONTEXT} apply -n sleep -f https://raw.githubusercontent.com/istio/istio/1.18.7/samples/sleep/sleep.yaml

Create the httpbin app, and label the httpbin namespace for Istio sidecar injection.

  kubectl --context ${REMOTE_CONTEXT} create namespace httpbin
kubectl --context ${REMOTE_CONTEXT} label ns httpbin istio-injection=enabled
kubectl --context ${REMOTE_CONTEXT} apply -n httpbin -f https://raw.githubusercontent.com/istio/istio/1.18.7/samples/httpbin/httpbin.yaml

Get the IP address of the httpbin pod.

  kubectl --context ${REMOTE_CONTEXT} get pods -n httpbin -o wide

Log in to your VM, and curl the pod IP address. This ensures that the VM and workload cluster are available to each other on the same network subnet, before you deploy Istio sidecars to either.
```
  curl -s <httpbin_pod_ip>:80
  
```
Note: If the curl is unsuccessful, verify that the security rules that you created for the VM allow outbound traffic and permit TCP traffic on ports 22, 80, and 5000.

Deploy Istio

Set up the Istio control plane and gateways in the workload cluster. Note that the installation settings included in these steps are tailored for basic setups.

Create the following Istio namespaces, and label the istio-system namespace with topology.istio.io/network=${REMOTE_CLUSTER}.

  kubectl --context ${REMOTE_CONTEXT} create namespace istio-ingress
kubectl --context ${REMOTE_CONTEXT} create namespace istio-eastwest
kubectl --context ${REMOTE_CONTEXT} create namespace istio-system
kubectl --context ${REMOTE_CONTEXT} label namespace istio-system topology.istio.io/network=${REMOTE_CLUSTER}

Download the IstioOperator resource, which contains Istio installation settings that are required for onboarding a VM to the service mesh.

  curl -0L https://raw.githubusercontent.com/solo-io/gloo-mesh-use-cases/main/gloo-mesh/istio-install/vm-agent/gcp.yaml > gcp.yaml

  curl -0L https://raw.githubusercontent.com/solo-io/gloo-mesh-use-cases/main/gloo-mesh/istio-install/vm-agent/aws.yaml > aws.yaml

Update the file with your workload cluster name, and install the control plane and gateways.

  export CLUSTER_NAME=${REMOTE_CLUSTER}
envsubst < gcp.yaml | istioctl install --context ${REMOTE_CONTEXT} -y -f -

  export CLUSTER_NAME=${REMOTE_CLUSTER}
envsubst < aws.yaml | istioctl install --context ${REMOTE_CONTEXT} -y -f -

Verify that the Istio pods are healthy.

  kubectl --context ${REMOTE_CONTEXT} get pods -n istio-system

Verify that the load balancer service for the east-west gateway is created. Note that it might take a few minutes for an external IP address to be assigned. The LoadBalancer service that exposes the east-west gateway allows the VM to access the cluster’s service mesh and be onboarded into the mesh. After the VM is onboarded, all traffic sent to and from the VM goes through the east-west gateway.
```
  kubectl --context ${REMOTE_CONTEXT} get svc -n istio-eastwest
  
```

Rollout a restart to the test apps that you deployed prior to the Istio installation, so that they are re-deployed with an Istio sidecar.

  kubectl --context ${REMOTE_CONTEXT} rollout restart deploy/sleep -n sleep
kubectl --context ${REMOTE_CONTEXT} rollout restart deploy/httpbin -n httpbin

Enable telemetry for all workloads in the workload cluster.

  kubectl apply --context ${REMOTE_CONTEXT} -f - <<EOF
apiVersion: telemetry.istio.io/v1alpha1
kind: Telemetry
metadata:
  name: demo
  namespace: istio-system
spec:
  # no selector specified, applies to all workloads
  metrics:
  - providers:
    - name: prometheus
EOF

Register the workload cluster

Register the workload cluster with the Gloo management server. Note that the registration settings included in these steps are tailored for basic setups. For more information about advanced settings, see the setup documentation.

Save the settings that are required to deploy SPIRE and PostgreSQL when you register your workload cluster. The steps vary based on the certificates you used to deploy Istio.

Default Istio certificates: If you used the default Istio certificates and did not set up and manage your own certificates to deploy Istio, you can use the default certificates to also secure the SPIRE server.

Copy the Istio root CA secret for the SPIRE server and use it as the certificate authority for the SPIRE server.

  kubectl --context ${REMOTE_CONTEXT} create ns gloo-mesh
kubectl --context ${REMOTE_CONTEXT} get secret istio-ca-secret -n istio-system -o yaml | \
  grep -v '^\s*namespace:\s' | sed 's/istio-ca-secret/spire-ca/' | \
  kubectl --context ${REMOTE_CONTEXT} apply -n gloo-mesh -f -

Save the following settings for SPIRE and PostgreSQL in an agent.yaml Helm values file. Note that if you want to use a MySQL database instead, you can change the databaseType to mysql. For more infromation, see the SPIRE docs.

  cat >agent.yaml <<EOF
demo:
  manageAddonNamespace: true
glooSpireServer:
  controller:
    verbose: true
  enabled: true
  plugins:
    datastore:
      databaseType: postgres
      connectionString: "dbname=spire user=spire password=gloomesh host=postgresql sslmode=disable"
    nodeAttestor:
      gcp:
        allowedProjectIds:
          - "${PROJECT}"
        allowedLabelKeys:
          - app
        enabled: true
    upstreamAuthority:
      disk:
        certFilePath: /run/spire/certs/ca-cert.pem
        bundleFilePath: /run/spire/certs/ca-cert.pem
postgresql:
  enabled: true
  global:
    postgresql:
      auth:
        database: spire
        password: gloomesh
        username: spire
EOF

  cat >agent.yaml <<EOF
demo:
  manageAddonNamespace: true
glooSpireServer:
  controller:
    verbose: true
  enabled: true
  plugins:
    nodeAttestor:
      aws:
        assumeRole: "SpireServerDelegate"
        enabled: true
    upstreamAuthority:
      disk:
        certFilePath: /run/spire/certs/ca-cert.pem
        bundleFilePath: /run/spire/certs/ca-cert.pem
postgresql:
  enabled: true
  global:
    postgresql:
      auth:
        database: spire
        password: gloomesh
        username: spire
EOF

Custom Istio certificates: If you set up your own certificates to deploy Istio, you also can use these certificates to secure the SPIRE server.

Be sure that you created a RootTrustPolicy as part of the custom Istio certificate setup process that you followed. The root trust policy allows the Gloo agent to automatically create a spire-ca secret, which contains the Istio root CA for the SPIRE server to use as its certificate authority.

Save the following settings for SPIRE and PostgreSQL in an agent.yaml Helm values file.

  cat >agent.yaml <<EOF
demo:
  manageAddonNamespace: true
glooSpireServer:
  controller:
    verbose: true
  enabled: true
  plugins:
    nodeAttestor:
      gcp:
        allowedProjectIds:
          - "${PROJECT}"
        allowedLabelKeys:
          - app
        enabled: true
postgresql:
  enabled: true
  global:
    postgresql:
      auth:
        database: spire
        password: gloomesh
        username: spire
telemetryCollectorCustomization:
  enableCloudMetadataProcessing: true
EOF

  cat >agent.yaml <<EOF
demo:
  manageAddonNamespace: true
glooSpireServer:
  controller:
    verbose: true
  enabled: true
  plugins:
    nodeAttestor:
      aws:
        assumeRole: "SpireServerDelegate"
        enabled: true
postgresql:
  enabled: true
  global:
    postgresql:
      auth:
        database: spire
        password: gloomesh
        username: spire
telemetryCollectorCustomization:
  enableCloudMetadataProcessing: true
EOF

Register the workload cluster with the management server. This command uses basic profiles to install the Gloo agent, rate limit server, and external auth server, as well the values file to install the SPIRE and PostgreSQL deployments.

  meshctl cluster register ${REMOTE_CLUSTER} \
  --kubecontext ${MGMT_CONTEXT} \
  --remote-context ${REMOTE_CONTEXT} \
  --version 2.4.16 \
  --profiles agent,ratelimit,extauth \
  --telemetry-server-address ${TELEMETRY_GATEWAY_ADDRESS} \
  --gloo-mesh-agent-chart-values agent.yaml \
  --set enabledExperimentalApi="{externalworkloads.networking.gloo.solo.io/v2alpha1,spireregistrationentries.internal.gloo.solo.io/v2alpha1}"

Verify that the Gloo data plane components are healthy, and that your Gloo Mesh Enterprise setup is correctly installed.
```
  meshctl check --kubecontext ${REMOTE_CONTEXT}
meshctl check --kubecontext ${MGMT_CONTEXT}
  
```

Depending on your cloud provider, annotate the necessary Kubernetes service accounts in your workload cluster with the IAM service account that you created earlier.

Annotate the Kubernetes service account for the SPIRE server and OTel collector with their GCP IAM service account.

  kubectl annotate serviceaccount gloo-spire-server \
  --context ${REMOTE_CONTEXT} -n gloo-mesh \
  iam.gke.io/gcp-service-account=GlooMesh@${PROJECT}.iam.gserviceaccount.com

kubectl annotate serviceaccount gloo-telemetry-collector \
  --context ${REMOTE_CONTEXT} -n gloo-mesh \
  iam.gke.io/gcp-service-account=GlooMesh@${PROJECT}.iam.gserviceaccount.com

Restart the SPIRE deployment and OTel daemonset to apply the change.

  kubectl --context ${REMOTE_CONTEXT} rollout restart deploy/gloo-spire-server -n gloo-mesh

kubectl --context ${REMOTE_CONTEXT} rollout restart daemonset/gloo-telemetry-collector-agent -n gloo-mesh

Annotate the Kubernetes service account for the SPIRE server with its AWS IAM role.

In the workload cluster, create an EKS IAM service account, and attach the policy for the SPIRE server’s IAM role that you previously created.

  eksctl create iamserviceaccount \
  --name gloo-spire-server --namespace gloo-mesh \
  --cluster ${REMOTE_CLUSTER} --role-name SpireServer \
  --attach-policy-arn arn:aws:iam::${ACCOUNT}:policy/SpireServer \
  --override-existing-serviceaccounts --approve

Verify that the IAM role is associated with the SPIRE server’s service account.

  aws iam list-attached-role-policies --role-name SpireServer --query AttachedPolicies[].PolicyArn --output text

Example output:

  arn:aws:iam::802411188784:policy/SpireServer

Verify that the SPIRE Kubernetes service account is annotated with the IAM role.

  kubectl --context ${REMOTE_CONTEXT} describe sa gloo-spire-server -n gloo-mesh

Example output:

  Name:                gloo-spire-server
Namespace:           gloo-mesh
Labels:              app.kubernetes.io/managed-by=eksctl
Annotations:         eks.amazonaws.com/role-arn: arn:aws:iam::802411188784:role/SpireServer
Image pull secrets:  <none>
Mountable secrets:   <none>
Tokens:              <none>
Events:              <none>

Restart the SPIRE deployment to apply the change.

  kubectl --context ${REMOTE_CONTEXT} rollout restart deploy/gloo-spire-server -n gloo-mesh

Verify that the pods in your workload cluster are healthy.

  kubectl --context ${REMOTE_CONTEXT} get pods -n gloo-mesh

Example output:

  NAME                                   READY   STATUS    RESTARTS   AGE
gloo-mesh-agent-d689d4544-g8fzn        1/1     Running   0          4m29s
gloo-spire-server-cd88fb77d-jk7mr      2/2     Running   0          53s
gloo-telemetry-collector-agent-7jzl4   1/1     Running   0          4m29s
gloo-telemetry-collector-agent-86ktk   1/1     Running   0          4m28s
gloo-telemetry-collector-agent-l8c99   1/1     Running   0          4m29s
gloo-telemetry-collector-agent-pkh2v   1/1     Running   0          4m28s
gloo-telemetry-collector-agent-pmqrh   1/1     Running   0          4m29s
gloo-telemetry-collector-agent-wnq7d   1/1     Running   0          4m28s
postgresql-0                           1/1     Running   0          4m28s

Step 4: Onboard the VM

Onboard the VM to your Gloo Mesh Enterprise setup by installing the Istio sidecar, OpenTelemetry (OTel) collector, and SPIRE agents on the VM.

On the workload cluster, create a namespace for the VM configuration that you set up in subsequent steps.
```
  kubectl --context ${REMOTE_CONTEXT} create namespace vm-config
  
```

Save the following ExternalWorkload Gloo resource to create an identity for apps that run on the VM. The following example resource provisions an identity in the vm-config namespace of the workload cluster, for services that listen on port 5000 and that run on a VM of the specified identity selector. For more information and available options, see the API reference documentation.

check_circle

This example creates an identity for only the test app that you create on the VM in subsequent steps, which you select by specifying port 5000. If you run multiple apps on your VM that you want to include in the service mesh, you can specify multiple ports to select each app. Then, when you create a virtual destination for the test app in subsequent steps, you can create additional virtual destinations for each of your other apps.

  cat >externalworkload.yaml <<EOF
apiVersion: networking.gloo.solo.io/v2alpha1
kind: ExternalWorkload
metadata:
  labels:
    # Label to use later when you create a virtual destination for the test app
    app: vm-ext-workload
    version: v1
  name: vm-ext-workload
  namespace: vm-config
spec:
  connectedClusters:
    # Map of workload cluster name to VM configuration namespace
    ${REMOTE_CLUSTER}: vm-config
  identitySelector:
    gcp:
      # VM instance name
      - name: ${VM_NAME}
  # Port for each app to include
  ports:
    # Test app port
    - name: http
      number: 5000
EOF

  cat >externalworkload.yaml <<EOF
apiVersion: networking.gloo.solo.io/v2alpha1
kind: ExternalWorkload
metadata:
  labels:
    # Label to use later when you create a virtual destination for the test app
    app: vm-ext-workload
    version: v1
  name: vm-ext-workload
  namespace: vm-config
spec:
  connectedClusters:
    # Map of workload cluster name to VM configuration namespace
    ${REMOTE_CLUSTER}: vm-config
  identitySelector:
    aws:
      # ID of the security group for the VM
      - securityGroupId: ${VM_SG_ID}
  # Port for each app to include
  ports:
    # Test app port
    - name: http
      number: 5000
EOF

Create the ExternalWorkload resource in the workload cluster.

  kubectl apply --context ${REMOTE_CONTEXT} -f externalworkload.yaml

Confirm that a WorkloadGroup Istio resource is created in your VM configuration namespace. This resource summarizes all workloads on the VM that you selected by port number in the ExternalWorkload.
```
  kubectl --context ${REMOTE_CONTEXT} get workloadgroup -n vm-config
  
```
Example output:
```
  NAME               AGE
vm-ext-workload    10s
  
```

In the management cluster, use meshctl to generate the bootstrap bundle that is required to install the Istio sidecar, OTel collector, and SPIRE agents on the VM. The generated bundle, bootstrap.tar.gz, is created based on the ExternalWorkload configuration that you previously applied in your workload cluster. For more information about the options for this command, see the CLI reference.

  meshctl x external-workload generate-bootstrap-bundle \
   --kubecontext ${REMOTE_CONTEXT} \
   --cluster ${REMOTE_CLUSTER} \
   --cluster-gw-svc istio-eastwest/istio-eastwestgateway \
   --attestor gcp \
   -f externalworkload.yaml \
   -o /tmp/bootstrap.tar.gz

  meshctl x external-workload generate-bootstrap-bundle \
   --kubecontext ${REMOTE_CONTEXT} \
   --cluster ${REMOTE_CLUSTER} \
   --cluster-gw-svc istio-eastwest/istio-eastwestgateway \
   --attestor aws \
   -f externalworkload.yaml \
   -o /tmp/bootstrap.tar.gz

The output /tmp/bootstrap.tar.gz directory on your local machine contains the cluster.env, hosts, mesh.yaml, root-cert.pem, and spire-agent.conf files.

  INFO  ✅ Bootstrap bundle generated: /tmp/bootstrap.tar.gz

On the VM, create the gloo-mesh-config directory, and navigate to the directory.
```
  mkdir gloo-mesh-config
cd gloo-mesh-config
  
```

From your local machine, copy the bootstrap bundle and the bootstrap script to the ~/gloo-mesh-config/ directory on the VM.

  scp /tmp/bootstrap.tar.gz <username>@<instance_address>:~/gloo-mesh-config/
scp bootstrap.sh <username>@<instance_address>:~/gloo-mesh-config/

Get the URLs for the packages to install the Istio sidecar, OTel collector, and SPIRE agents on your VM, and save them as environment variables on the VM.
1. Log in to the Support Center and review the Solo packages for external workload integration support article.
2. Save the Istio package URL.
  1. For the same Istio version that you previously downloaded, open the link for the cloud storage bucket that has Solo distributions of Istio.
  2. In the storage bucket, open the -solo directory for the version you want to use, such as 1.18.7-patch3-solo/.
  3. Depending on your VM image type, open either the deb/ or rpm/ directory.
  4. On either the istio-sidecar or istio-sidecar-arm64 binary package, click the menu button, and click Copy Public URL.
  5. On your VM, save the URL as an environment variable.
```
  export ISTIO_URL=<istio_package_url>
  
```
3. Save the OTel package URL.
  1. Open the link for the Solo cloud storage bucket.
  2. In the storage bucket, open the directory for the Gloo version that you use.
  3. Open the otel/ directory.
  4. On the package for your VM type, click the menu button, and click Copy Public URL.
  5. On your VM, save the URL as an environment variable.
```
  export OTEL_URL=<otel_package_url>
  
```
4. Save the SPIRE package URL.
  1. Open the link for the Solo cloud storage bucket.
  2. In the storage bucket, open the directory for the Gloo version that you use.
  3. Open the spire/ directory.
  4. On the package for your VM type, click the menu button, and click Copy Public URL.
  5. On your VM, save the URL as an environment variable.
```
  export SPIRE_URL=<spire_package_url>
  
```

On the VM, install the Istio sidecar, OTEL collector, and SPIRE agents.

  sudo ./bootstrap.sh --istio-pkg ${ISTIO_URL} --otel-pkg ${OTEL_URL} --spire-pkg ${SPIRE_URL} -b bootstrap.tar.gz --install --start

Step 5: Test connectivity

Verify that the onboarding process was successful by testing the bi-directional connection between the apps that run in the service mesh in your workload cluster and a test app on your VM.

On your VM, deploy a simple HTTP server that listens on port 5000. This app is represented by the ExternalWorkload identity that you previously created.
```
  nohup python3 -m http.server 5000 &
  
```

From the VM, curl the httpbin service in your workload cluster. Note that this curl command uses the app’s cluster DNS name instead of its pod IP address, because the VM is now connected to the Istio service mesh that runs in your workload cluster.

  curl -s httpbin.httpbin:8000 -v

Example output:

  *   Trying 10.XX.XXX.XXX:8000...
* Connected to httpbin.httpbin (10.XX.XXX.XXX) port 8000 (#0)
> GET / HTTP/1.1
> Host: httpbin.httpbin:8000
> User-Agent: curl/7.74.0
> Accept: */*
>
* Mark bundle as not supporting multiuse
< HTTP/1.1 200 OK
< server: envoy
< date: Mon, 10 Jul 2023 18:00:32 GMT
< content-type: text/html; charset=utf-8
< content-length: 9593
< access-control-allow-origin: *
< access-control-allow-credentials: true
< x-envoy-upstream-service-time: 4
<
<!DOCTYPE html>
...

In the workload cluster, create a Gloo VirtualDestination resource so that apps in the service mesh can also access the HTTP server test app that runs on the VM through the testapp.vd hostname. Note that if you selected multiple apps that run on the VM in your ExternalWorkload resource, you can create a virtual destination for each app by using the app’s port that you specified.

  kubectl --context ${REMOTE_CONTEXT} apply -f - <<EOF
apiVersion: networking.gloo.solo.io/v2
kind: VirtualDestination
metadata:
  labels:
    app: testapp
  name: testapp-vd
  namespace: vm-config
spec:
  externalWorkloads:
  - labels:
      # Label that you gave to the ExternalWorkload resource
      app: vm-ext-workload
  hosts:
  # Hostname to use for the app
  - testapp.vd
  ports:
  # Port that you specified in the ExternalWorkload resource to select the test app
  - number: 5000
    protocol: HTTP
    targetPort:
      name: http
EOF

From the sleep app in your workload cluster, curl the HTTP server on the VM by using the testapp.vd hostname.

  kubectl --context ${REMOTE_CONTEXT} exec deploy/sleep -n sleep -- curl -s testapp.vd:5000 -v

Example output:

  *   Trying 244.XXX.XXX.XX:5000...
* Connected to testapp.vd (244.XXX.XXX.XX) port 5000 (#0)
> GET / HTTP/1.1
> Host: testapp.vd:5000
> User-Agent: curl/8.1.2
> Accept: */*
>
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN" "http://www.w3.org/TR/html4/strict.dtd">
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<title>Directory listing for /</title>
</head>
<body>
<h1>Directory listing for /</h1>
<hr>
<ul>
<li><a href=".bash_history">.bash_history</a></li>
<li><a href=".bash_logout">.bash_logout</a></li>
<li><a href=".bashrc">.bashrc</a></li>
<li><a href=".profile">.profile</a></li>
<li><a href=".ssh/">.ssh/</a></li>
<li><a href="gm-config/">gm-config/</a></li>
<li><a href="nohup.out">nohup.out</a></li>
</ul>
<hr>
</body>
</html>
< HTTP/1.1 200 OK
< server: envoy
< date: Mon, 10 Jul 2023 18:00:50 GMT
< content-type: text/html; charset=utf-8
< content-length: 600
< x-envoy-upstream-service-time: 3
<
{ [600 bytes data]
* Connection #0 to host testapp.vd left intact

Step 6 (optional): Launch the UI

To visualize the connection to your VM in your Gloo Mesh Enterprise setup, you can lauch the Gloo UI.

Access the Gloo UI.

  meshctl dashboard --kubecontext ${MGMT_CONTEXT}

Click the Graph tab to open the network visualization graph for your Gloo Mesh Enterprise setup.
From the footer toolbar, click Layout Settings.
Toggle Group By to INFRA to review the clusters, virtual machines, and Kubernetes namespaces that your app nodes are organized in. This view also shows details for the cloud provider infrastructure, such as the VPCs and subnets that your resources are deployed to.
Verify that you see your VM connection to your workload cluster. In this example graph, the VM instance connects to the httpbin app in the workload cluster.
You can also see more information about the VM instance by clicking on its icon, which opens the details pane for the connection. In this example details pane, the title helloworld -> httpbin demonstrates that an external workload named helloworld, which represents apps on the VM, connects to the httpbin app in the workload cluster.

Congratulations! Your VM is now registered with Gloo Mesh Enterprise. You can now create Gloo resources for the workloads that you run on the VM, such as Gloo traffic policies. For example, if you selected multiple apps in your ExternalWorkload resource and want to apply a policy to all of those apps, you can use the label on the ExternalWorkload in the policy selector. Or, for policies that apply to destinations, you can select only the virtual destination for one of the apps. For more information, see Policy enforcement.

Uninstall

On the VM:
1. Remove the Istio sidecar, OTel collector, and SPIRE agents.
```
  sudo ./bootstrap.sh --uninstall
  
```
2. Remove the bootstrap script and bundle, the agent packages, and the test app data.
```
  cd ..
rm -r gloo-mesh-config
  
```

On the workload cluster:

Delete the vm-config, sleep, and httpbin namespaces.

  kubectl --context ${REMOTE_CONTEXT} delete namespace vm-config
kubectl --context ${REMOTE_CONTEXT} delete namespace sleep
kubectl --context ${REMOTE_CONTEXT} delete namespace httpbin

Delete the Gateway and VirtualService resources from the istio-eastwest namespace.

  kubectl --context ${REMOTE_CONTEXT} delete Gateway istiod-gateway -n istio-eastwest
kubectl --context ${REMOTE_CONTEXT} delete Gateway spire-gateway -n istio-eastwest
kubectl --context ${REMOTE_CONTEXT} delete VirtualService istiod-vs -n istio-eastwest
kubectl --context ${REMOTE_CONTEXT} delete VirtualService spire-vs -n istio-eastwest

Continue to use your Gloo Mesh Enterprise setup, or uninstall it.
- To continue to use your Gloo Mesh Enterprise setup, you can optionally remove the SPIRE and PostgreSQL servers by following the upgrade guide to remove their settings from the Helm values for your workload cluster.
- To uninstall your Gloo Mesh Enterprise setup:
  1. Uninstall the Istio service mesh.
```
  istioctl uninstall --context ${REMOTE_CONTEXT} --purge
  
```
  2. Remove the Istio namespaces.
```
  kubectl delete ns --context ${REMOTE_CONTEXT} istio-system
kubectl delete ns --context ${REMOTE_CONTEXT} istio-ingress
kubectl delete ns --context ${REMOTE_CONTEXT} istio-eastwest
  
```
  3. Follow the steps in Uninstall Gloo Mesh Enterprise to deregister the workload cluster and uninstall the Gloo management plane.

Alpha: External workloads (VMs)

About link

Before you begin link

Install CLI tools link

Overview link

Step 1: Create compute resources link

Step 2: Set up the management cluster link

Step 3: Set up the workload cluster link

Deploy test apps link

Deploy Istio link

Register the workload cluster link

Step 4: Onboard the VM link

Step 5: Test connectivity link

Step 6 (optional): Launch the UI link

Uninstall link

About

Before you begin

Install CLI tools

Overview

Step 1: Create compute resources

Step 2: Set up the management cluster

Step 3: Set up the workload cluster

Deploy test apps

Deploy Istio

Register the workload cluster

Step 4: Onboard the VM

Step 5: Test connectivity

Step 6 (optional): Launch the UI

Uninstall