From edge to mesh: Exposing service mesh applications through GKE Ingress

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This tutorial shows how to combine Anthos Service Mesh with Cloud Load Balancing to expose applications in a service mesh to internet clients.

Anthos Service Mesh is a managed service mesh, based on Istio, that provides a security-enhanced, observable, and standardized communication layer for applications. Whether you use Anthos Service Mesh, Traffic Director, or Istio, a service mesh provides a holistic communications platform for clients that are communicating in the mesh. However, a challenge remains in how to connect clients that are outside the mesh to applications hosted in the mesh.

You can expose an application to clients in many ways, depending on where the client is. This tutorial shows you how to expose an application to clients by combining Cloud Load Balancing with Anthos Service Mesh in order to integrate load balancers with a service mesh. This tutorial is intended for advanced practitioners who run Anthos Service Mesh but it works for Istio on Google Kubernetes Engine too.

Mesh ingress gateway

Istio 0.8 introduced the mesh ingress gateway that provides a dedicated set of proxies whose ports are exposed to traffic coming from outside the service mesh. These mesh ingress proxies let you control L4 exposure behavior separately from application routing behavior. The proxies also let you apply routing and policy to mesh-external traffic before it arrives at an application sidecar. Mesh ingress defines the treatment of traffic when it reaches a node in the mesh, but external components must define how traffic first arrives at the mesh.

To manage this external traffic, you need a load balancer that is external to the mesh. This tutorial uses Google Cloud Load Balancing provisioned through GKE Ingress resources to automate deployment. The canonical example of this setup is an external load balancing service that (in the case of Google Cloud) deploys a public TCP/UDP load balancer. That load balancer points at the NodePorts of a GKE cluster. These NodePorts expose the Istio ingress gateway Pods, which route traffic to downstream mesh sidecar proxies. The following diagram illustrates this topology. Load balancing for internal private traffic looks similar to this architecture, except that you deploy an internal TCP/UDP load balancer instead.

An external load balancer routes external clients to the mesh through ingress gateway proxies.

Using L4 transparent load balancing with a mesh ingress gateway offers the following advantages:

  • This setup simplifies deploying the load balancer.
  • The load balancer provides a stable virtual IP (VIP), health checking, and reliable traffic distribution when cluster changes, node outages, or process outages occur.
  • All routing rules, TLS termination, and traffic policy is handled in a single location at the mesh ingress gateway.

GKE Ingress and Services

You can provide access to applications for clients that are outside the cluster in many ways. The following table lists the Kubernetes primitives available for deploying load balancers on Google Cloud. The type of load balancer you use to expose applications to clients depends largely on whether the clients are external or internal, what kind of protocol support is required, and whether the service mesh spans multiple GKE clusters or is contained in a single cluster.

Any of the load balancer types in the following table can expose mesh-hosted applications, depending on the use case.

GKE resource Cloud-based load balancer Characteristics
Ingress for External HTTP(S) Load Balancing External HTTP(S) load balancer

L7 proxies in Google edge points of presence (PoPs)

Public VIP

Globally scoped

Single cluster
Ingress for Internal HTTP(S) Load Balancing Internal HTTP(S) load balancer

L7 proxies inside virtual private cloud (VPC) network

Private VIP

Regionally scoped

Single cluster
External LoadBalancer Service External TCP/UDP load balancer

L4 pass-through at Google edge PoPs

Public VIP

Regionally scoped

Single cluster
Internal LoadBalancer Service Internal TCP/UDP load balancer

L4 pass-through in VPC routing network

Private VIP

Regionally scoped

Single cluster
Multi Cluster Ingress (multi-cluster, external ingress) External HTTP(S) load balancer

L7 proxies in Google edge PoPs

Public VIP

Globally scoped

Multi-cluster

Although the default load balancer for Anthos Service Mesh is the external TCP/UDP load balancer, this tutorial focuses on the external HTTP(S) load balancer that you deploy by using External HTTP(S) Load Balancing. The external HTTP(S) load balancer provides integration with edge services like Identity-Aware Proxy (IAP), Google Cloud Armor, and Cloud CDN, as well as a globally distributed network of edge proxies. The next section describes the architecture and advantages of using two layers of HTTP load balancing.

Cloud ingress and mesh ingress

Deploying external L7 load balancing outside of the mesh along with a mesh ingress layer offers significant advantages, especially for internet traffic. Even though Anthos Service Mesh and Istio ingress gateways provide advanced routing and traffic management in the mesh, some functions are better served at the edge of the network. Taking advantage of internet-edge networking through Google Cloud's External HTTP(S) Load Balancing might provide significant performance, reliability, or security-related benefits over mesh-based ingress. These benefits include the following:

This external layer of L7 load balancing is referred to as cloud ingress because it is built on cloud-managed load balancers rather than the self-hosted proxies that are used by mesh ingress. The combination of cloud ingress and mesh ingress utilizes complementary capabilities of the Google Cloud infrastructure and the mesh. The following diagram illustrates how you can combine cloud ingress and mesh ingress to serve as two load balancing layers for internet traffic.

Cloud ingress acts as the gateway for external traffic to the mesh through the VPC network.

In this topology, the cloud ingress layer sources traffic from outside of the service mesh and directs that traffic to the mesh ingress layer. The mesh ingress layer then directs traffic to the mesh-hosted application backends.

Cloud and mesh ingress topology

This section describes the complementary roles that each ingress layer fulfills when you use them together. These roles are not concrete rules, but rather guidelines that use the advantages of each layer. Variations of this pattern are likely, depending on your use case.

  • Cloud ingress. When paired with mesh ingress, the cloud ingress layer is best used for edge security and global load balancing. Because the cloud ingress layer is integrated with DDoS protection, cloud firewalls, authentication, and encryption products at the edge, this layer excels at running these services outside of the mesh. The routing logic is typically straightforward at this layer, but the logic can be more complex for multi-cluster and multi-region environments. Because of the critical function of internet-facing load balancers, the cloud ingress layer is likely managed by an infrastructure team that has exclusive control over how applications are exposed and secured on the internet. This control also makes this layer less flexible and dynamic than a developer-driven infrastructure, a consideration that may impact who and how you provide administrative access to this layer.
  • Mesh ingress. When paired with cloud ingress, the mesh ingress layer provides flexible routing that is close to the application. Because of this flexibility, the mesh ingress is better than cloud ingress for complex routing logic and application-level visibility. The separation between ingress layers also makes it easier for application owners to directly control this layer without impacting other teams. When you expose service mesh applications through an L4 load balancer instead of an L7 load balancer, you should terminate client TLS at the mesh ingress layer inside the mesh to help secure applications.

Health checking

One complexity of using two layers of L7 load balancing is health checking. You must configure each load balancer to check the health of the next layer to ensure that it can receive traffic. The topology in the following diagram shows how cloud ingress checks the health of the mesh ingress proxies, and the mesh, in return, checks the health of the application backends.

Cloud ingress checks the health of the mesh ingress, and the mesh ingress checks the health of the application backends.

This topology has the following considerations:

  • Cloud ingress. In this tutorial, you configure the Google Cloud load balancer through ingress to check the health of the mesh ingress proxies on their exposed health check ports. If a mesh proxy is down, or if the cluster, mesh, or region is unavailable, the Google Cloud load balancer detects this condition and doesn't send traffic to the mesh proxy.
  • Mesh ingress. In the mesh application, you perform health checks on the backends directly so that you can execute load balancing and traffic management locally.

Security

The preceding topology involves several elements of security. One of the most critical elements is in how you configure encryption and deploy certificates. Ingress for External HTTP(S) Load Balancing has deep integration with Google-managed certificates. This integration automatically provisions public certificates, attaches them to a load balancer, and renews and rotates certificates all through the declarative GKE Ingress interface. Internet clients authenticate against the public certificates and connect to the external load balancer as the first hop in the Virtual Private Cloud (VPC).

The next hop, which is between the Google Front End (GFE) and the mesh ingress proxy, is encrypted by default. Network-level encryption between the GFEs and their backends is applied automatically. However, if your security requirements dictate that the platform owner retain ownership of the encryption keys, then you can enable HTTP/2 with TLS encryption between the cluster ingress (the GFE) and the mesh ingress (the envoy proxy instance). When you enable HTTP/2 with TLS encryption for this path, you can use a self-signed or public certificate to encrypt traffic because the GFE doesn't authenticate against it. This additional layer of encryption is demonstrated in this guide. To help prevent the mishandling of certificates, do not use the public certificate for the public load balancer elsewhere. Instead, we recommend that you use separate certificates in the service mesh.

If the service mesh mandates TLS, then all traffic is encrypted between sidecar proxies and to the mesh ingress. The following diagram illustrates HTTPS encryption from the client to the Google Cloud load balancer, from the load balancer to the mesh ingress proxy, and from the ingress proxy to the sidecar proxy.

Security is implemented using managed certificates outside of the mesh and internal certificates inside the mesh.

Objectives

  • Deploy a Google Kubernetes Engine (GKE) cluster on Google Cloud.
  • Deploy an Istio-based Anthos Service Mesh on your GKE cluster.
  • Configure GKE Ingress to terminate public HTTPS traffic and direct that traffic to service mesh-hosted applications.
  • Deploy the Online Boutique application on the GKE cluster that you expose to clients on the internet.

Costs

This tutorial uses the following billable components of Google Cloud:

To generate a cost estimate based on your projected usage, use the pricing calculator. New Google Cloud users might be eligible for a free trial.

When you finish this tutorial, you can avoid continued billing by deleting the resources you created. For more information, see Clean up.

Before you begin

  1. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  2. Make sure that billing is enabled for your Cloud project. Learn how to check if billing is enabled on a project.

  3. In the Google Cloud console, activate Cloud Shell.

    Activate Cloud Shell

    You run all of the terminal commands for this tutorial from Cloud Shell.

  4. Upgrade to the latest version of the Google Cloud CLI:

    gcloud components update

  5. Set your default Google Cloud project:

    export PROJECT=PROJECT
export PROJECT_NUMBER=$(gcloud projects describe ${PROJECT} --format="value(projectNumber)")
gcloud config set project ${PROJECT}

    Replace PROJECT with the project ID that you want to use for this tutorial.

  6. Create a working directory:

    mkdir -p ${HOME}/edge-to-mesh
cd ${HOME}/edge-to-mesh
export WORKDIR=`pwd`

    After you finish the tutorial, you can delete the working directory.

Creating GKE clusters

The features that are described in this tutorial require a GKE cluster version 1.16 or later.

  1. In Cloud Shell, create a new kubeconfig file. This step ensures that you don't create a conflict with your existing (default) kubeconfig file.

    touch edge2mesh_kubeconfig
export KUBECONFIG=${WORKDIR}/edge2mesh_kubeconfig

  2. Define environment variables for the GKE cluster:

    export CLUSTER_NAME=edge-to-mesh
export CLUSTER_LOCATION=us-west1-a

  3. Enable the Google Kubernetes Engine API.

    gcloud

    gcloud services enable container.googleapis.com

    Config Connector

    This tutorial includes Config Connector resources. You can use these resources to complete the same tasks that you complete in the gcloud tab. To utilize these resources, install Config Connector and apply the resources in the way that works best for your environment.

    Use the following Services manifest:

    apiVersion: serviceusage.cnrm.cloud.google.com/v1beta1
kind: Service
metadata:
  annotations:
    cnrm.cloud.google.com/deletion-policy: "abandon"
    cnrm.cloud.google.com/disable-dependent-services: "false"
  name: container.googleapis.com
spec:
  resourceID: container.googleapis.com
  projectRef:
    external: PROJECT

  4. Create a GKE cluster.

    gcloud 

    gcloud container clusters create ${CLUSTER_NAME} \
    --machine-type=e2-standard-4 \
    --num-nodes=4 \
    --zone ${CLUSTER_LOCATION} \
    --enable-ip-alias \
    --workload-pool=${PROJECT}.svc.id.goog \
    --release-channel rapid \
    --addons HttpLoadBalancing \
    --labels mesh_id=proj-${PROJECT_NUMBER}

    Config Connector

    Use the following ContainerCluster and ContainerNodePool manifests:

    apiVersion: container.cnrm.cloud.google.com/v1beta1
kind: ContainerNodePool
metadata:
  annotations:
    cnrm.cloud.google.com/project-id: PROJECT
  name: edge-to-mesh
spec:
  clusterRef:
    name: edge-to-mesh
  location: us-west1-a
  nodeConfig:
    machineType: e2-standard-4
  nodeCount: 4
---
apiVersion: container.cnrm.cloud.google.com/v1beta1
kind: ContainerCluster
metadata:
  annotations:
    cnrm.cloud.google.com/project-id: PROJECT
    cnrm.cloud.google.com/remove-default-node-pool: "true"
  labels:
    mesh_id: proj-PROJECT_NUMBER
  name: edge-to-mesh
spec:
  addonsConfig:
    httpLoadBalancing:
      disabled: false
  location: us-west1-a
  initialNodeCount: 1
  releaseChannel:
    channel: RAPID
  workloadIdentityConfig:
    workloadPool: PROJECT.svc.id.goog

    Replace PROJECT_NUMBER with the value of the PROJECT_NUMBER environment variable retrieved earlier.

    To use a cloud ingress, you must have the HTTP load balancing add-on enabled. GKE clusters have HTTP load balancing enabled by default; you must not disable it.

    To use the managed Anthos Service Mesh, you must apply the mesh_id label on the cluster.

  5. Ensure that the cluster is running:

    gcloud container clusters list

    The output is similar to the following:

    NAME          LOCATION    MASTER_VERSION    MASTER_IP      MACHINE_TYPE   NODE_VERSION      NUM_NODES  STATUS
edge-to-mesh  us-west1-a  v1.22.6-gke.300   35.233.195.59  e2-standard-4  v1.22.6-gke.300   4          RUNNING

  6. Connect to the cluster:

    gcloud container clusters get-credentials ${CLUSTER_NAME} \
    --zone ${CLUSTER_LOCATION} \
    --project ${PROJECT}

Installing a service mesh

In this section, you configure the managed Anthos Service Mesh with fleet API.

  1. Enable the required APIs:

    gcloud

    gcloud services enable mesh.googleapis.com

    Config Connector

    Use the following Services manifest:

    apiVersion: serviceusage.cnrm.cloud.google.com/v1beta1
kind: Service
metadata:
  annotations:
    cnrm.cloud.google.com/deletion-policy: "abandon"
    cnrm.cloud.google.com/disable-dependent-services: "false"
  name: mesh.googleapis.com
spec:
  resourceID: mesh.googleapis.com
  projectRef:
    external: PROJECT

  2. Enable Anthos Service Mesh on the fleet:

    gcloud 

    gcloud container fleet mesh enable

    Config Connector

    Use the following GKEHubFeature manifest:

    apiVersion: gkehub.cnrm.cloud.google.com/v1beta1
kind: GKEHubFeature
metadata:
  name: servicemesh
spec:
  projectRef:
    external: PROJECT
  location: global
  resourceID: servicemesh

  3. Register the cluster to the fleet:

    gcloud 

    gcloud container fleet memberships register ${CLUSTER_NAME} \
    --gke-cluster ${CLUSTER_LOCATION}/${CLUSTER_NAME} \
    --enable-workload-identity

    Config Connector

    Use the following GKEHubMembership manifest:

    apiVersion: gkehub.cnrm.cloud.google.com/v1beta1
kind: GKEHubMembership
metadata:
  annotations:
    cnrm.cloud.google.com/project-id: PROJECT
  name: edge-to-mesh
spec:
  location: global
  authority:
    issuer: https://container.googleapis.com/v1/projects/PROJECT/locations/us-west1-a/clusters/edge-to-mesh
  endpoint:
    gkeCluster:
      resourceRef:
        name: edge-to-mesh

  4. Enable automatic control plane management and managed data plane:

    gcloud 

    gcloud container fleet mesh update \
    --management automatic \
    --memberships ${CLUSTER_NAME}

    Config Connector

    Use the following GKEHubFeatureMembership manifest:

    apiVersion: gkehub.cnrm.cloud.google.com/v1beta1
kind: GKEHubFeatureMembership
metadata:
  name: servicemesh-membership
spec:
  projectRef:
    external: PROJECT_ID
  location: global
  membershipRef:
    name: edge-to-mesh
  featureRef:
    name: servicemesh
  mesh:
    management: MANAGEMENT_AUTOMATIC

  5. After a few minutes, verify that the control plane status is ACTIVE:

    gcloud container fleet mesh describe

    The output is similar to the following:

    ...
membershipSpecs:
  projects/841956571429/locations/global/memberships/edge-to-mesh:
    mesh:
      management: MANAGEMENT_AUTOMATIC
membershipStates:
  projects/841956571429/locations/global/memberships/edge-to-mesh:
    servicemesh:
      controlPlaneManagement:
        details:
        - code: REVISION_READY
          details: 'Ready: asm-managed-rapid'
        state: ACTIVE
      dataPlaneManagement:
        details:
        - code: OK
          details: Service is running.
        state: ACTIVE
    state:
      code: OK
      description: 'Revision(s) ready for use: asm-managed-rapid.'
      updateTime: '2022-09-29T05:30:28.320896186Z'
name: projects/your-project/locations/global/features/servicemesh
resourceState:
  state: ACTIVE
...

Deploying GKE Ingress

In the following steps, you deploy the external HTTP(S) load balancer through GKE's Ingress controller. The Ingress resource automates the provisioning of the load balancer, its TLS certificates, and backend health checking. Additionally, you use Cloud Endpoints to automatically provision a public DNS name for the application.

Install an ingress gateway

As a security best practice, we recommend that you deploy the ingress gateway in a different namespace from the control plane.

  1. In Cloud Shell, create a dedicated asm-ingress namespace:

    kubectl create namespace asm-ingress

  2. Add a namespace label to the asm-ingress namespace:

    kubectl label namespace asm-ingress istio-injection=enabled

    The output is similar to the following:

    namespace/asm-ingress labeled

    Labeling the asm-ingress namespace with istio-injection=enabled instructs Anthos Service Mesh to automatically inject Envoy sidecar proxies when an application is deployed.

  3. Run the following command to create the Deployment manifest as ingress-deployment.yaml:

    cat <<EOF > ingress-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: asm-ingressgateway
  namespace: asm-ingress
spec:
  selector:
    matchLabels:
      asm: ingressgateway
  template:
    metadata:
      annotations:
        # This is required to tell Anthos Service Mesh to inject the gateway with the
        # required configuration.
        inject.istio.io/templates: gateway
      labels:
        asm: ingressgateway
    spec:
      securityContext:
        fsGroup: 1337
        runAsGroup: 1337
        runAsNonRoot: true
        runAsUser: 1337
      containers:
      - name: istio-proxy
        securityContext:
          allowPrivilegeEscalation: false
          capabilities:
            drop:
            - all
          privileged: false
          readOnlyRootFilesystem: true
        image: auto # The image will automatically update each time the pod starts.
        resources:
          limits:
            cpu: 2000m
            memory: 1024Mi
          requests:
            cpu: 100m
            memory: 128Mi
      serviceAccountName: asm-ingressgateway
---
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: asm-ingressgateway
spec:
  maxReplicas: 5
  minReplicas: 3
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 50
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: asm-ingressgateway
---
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  name: asm-ingressgateway
  namespace: asm-ingress
rules:
- apiGroups: [""]
  resources: ["secrets"]
  verbs: ["get", "watch", "list"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: asm-ingressgateway
  namespace: asm-ingress
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: Role
  name: asm-ingressgateway
subjects:
  - kind: ServiceAccount
    name: asm-ingressgateway
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: asm-ingressgateway
  namespace: asm-ingress
EOF

    This Deployment has its own ServiceAccount with associated Role and RoleBinding allowing the gateway to access certificates.

  4. Deploy ingress-deployment.yaml in your cluster to create the Deployment resource:

    kubectl apply -f ingress-deployment.yaml

    The output is similar to the following:

    deployment.apps/asm-ingressgateway configured
role.rbac.authorization.k8s.io/asm-ingressgateway configured
rolebinding.rbac.authorization.k8s.io/asm-ingressgateway configured
serviceaccount/asm-ingressgateway created

    Ensure that all deployments are up and running:

    kubectl wait --for=condition=available --timeout=600s deployment --all -n asm-ingress

    The output is similar to the following:

    deployment.apps/asm-ingressgateway condition met

  5. Run the following command to create the Service manifest as ingress-service.yaml:

    cat <<EOF > ingress-service.yaml
apiVersion: v1
kind: Service
metadata:
  name: asm-ingressgateway
  namespace: asm-ingress
  annotations:
    cloud.google.com/neg: '{"ingress": true}'
    cloud.google.com/backend-config: '{"default": "ingress-backendconfig"}'
    cloud.google.com/app-protocols: '{"https":"HTTP2"}' # HTTP/2 with TLS encryption
  labels:
    asm: ingressgateway
spec:
  ports:
  # status-port exposes a /healthz/ready endpoint that can be used with GKE Ingress health checks
  - name: status-port
    port: 15021
    protocol: TCP
    targetPort: 15021
  # Any ports exposed in Gateway resources should be exposed here.
  - name: http2
    port: 80
    targetPort: 8080
  - name: https
    port: 443
    targetPort: 8443
  selector:
    asm: ingressgateway
  type: ClusterIP
EOF

    This Service has the following annotations that set parameters for the Ingress load balancer when it's deployed:

    • cloud.google.com/backend-config refers to the name of a custom resource called BackendConfig. The Ingress controller uses BackendConfig to set parameters on the Google Cloud BackendService resource. You use this resource in the next step to define custom parameters of the Google Cloud health check.
    • cloud.google.com/neg: '{"ingress": true}' enables the Ingress backends (the mesh ingress proxies in this case) for container-native load balancing. For more efficient and stable load balancing, these backends use network endpoint groups (NEGs) instead of instance groups.
    • cloud.google.com/app-protocols: '{"https":"HTTP2"}' directs the GFE to connect to the service mesh's ingress gateway using HTTP2 with TLS as described in Ingress for External HTTP(S) Load Balancing and External HTTP(S) Load Balancing overview, for an additional layer of encryption.

  6. Deploy ingress-service.yaml in your cluster to create the Service resource:

    kubectl apply -f ingress-service.yaml

    The output is similar to the following:

    service/asm-ingressgateway created

Apply backend Service settings

  1. In Cloud Shell, run the following command to create the BackendConfig manifest as ingress-backendconfig.yaml:

    cat <<EOF > ingress-backendconfig.yaml
apiVersion: cloud.google.com/v1
kind: BackendConfig
metadata:
  name: ingress-backendconfig
  namespace: asm-ingress
spec:
  healthCheck:
    requestPath: /healthz/ready
    port: 15021
    type: HTTP
  securityPolicy:
    name: edge-fw-policy
EOF

    BackendConfig is a Custom Resource Definition (CRD) that defines backend parameters for Ingress load balancing. For a complete list of the backend and frontend parameters that you can configure through GKE Ingress, see Ingress features.

    In this tutorial, the BackendConfig manifest specifies custom health checks for the mesh ingress proxies. Anthos Service Mesh and Istio expose their sidecar proxy health checks on port 15021 at the /healthz/ready path. Custom health check parameters are required because the serving port (443) of mesh ingress proxies is different from their health check port (15021). GKE Ingress uses the following health check parameters in BackendConfig to configure the Google Cloud load balancer health checks. A security policy that helps protect load balancing traffic from different kinds of network attacks is also referenced.

    • healthCheck.port defines the port that receives a health check by the Google Cloud load balancer on each Pod's IP address.
    • healthCheck.requestPath defines the HTTP path that receives a health check on the specified port.
    • type defines the protocol of the health check (in this case, HTTP).
    • securityPolicy.name refers to the name of a Cloud Armor security policy.

  2. Deploy ingress-backendconfig.yaml in your cluster to create the BackendConfig resource:

    kubectl apply -f ingress-backendconfig.yaml

    The output is similar to the following:

    backendconfig.cloud.google.com/ingress-backendconfig created

    The BackendConfig parameters and the asm-ingressgateway Service annotations are not applied to a Google Cloud load balancer until the Ingress resource is deployed. The Ingress deployment ties all of these resources together.

Define security policies

Google Cloud Armor provides DDoS defense and customizable security policies that you can attach to a load balancer through Ingress resources. In the following steps, you create a security policy that uses preconfigured rules to block cross-site scripting (XSS) attacks. This rule helps block traffic that matches known attack signatures but allows all other traffic. Your environment might use different rules depending on what your workload is.

gcloud

  1. In Cloud Shell, create a security policy that is called edge-fw-policy:

    gcloud compute security-policies create edge-fw-policy \
    --description "Block XSS attacks"

  2. Create a security policy rule that uses the preconfigured XSS filters:

    gcloud compute security-policies rules create 1000 \
    --security-policy edge-fw-policy \
    --expression "evaluatePreconfiguredExpr('xss-stable')" \
    --action "deny-403" \
    --description "XSS attack filtering"

Config Connector

Use the following ComputeSecurityPolicy manifest:

apiVersion: compute.cnrm.cloud.google.com/v1beta1
kind: ComputeSecurityPolicy
metadata:
  annotations:
    cnrm.cloud.google.com/project-id: PROJECT_ID
  name: edge-fw-policy
spec:
  rule:
  - action: allow
    description: "Default rule"
    match:
      versionedExpr: SRC_IPS_V1
      config:
        srcIpRanges:
        - "*"
    priority: 2147483647
  - action: deny-403
    description: "XSS attack filtering"
    match:
      expr:
        expression: "evaluatePreconfiguredExpr('xss-stable')"
    priority: 1000

The edge-fw-policy was referenced by ingress-backendconfig in the previous section. When the Ingress resource is deployed, it binds this security policy with the load balancer to help protect any backends of the asm-ingressgateway Service.

Configure IP addressing and DNS

  1. In Cloud Shell, create a global static IP for the Google Cloud load balancer:

    gcloud 

    gcloud compute addresses create ingress-ip --global

    Config Connector

    Use the following ComputeAddress manifest:

    apiVersion: compute.cnrm.cloud.google.com/v1beta1
kind: ComputeAddress
metadata:
  annotations:
    cnrm.cloud.google.com/project-id: PROJECT_ID
  name: ingress-ip
spec:
  location: global

    This static IP is used by the Ingress resource and allows the IP to remain the same, even if the external load balancer changes.

  2. Get the static IP address:

    export GCLB_IP=$(gcloud compute addresses describe ingress-ip --global --format "value(address)")
echo ${GCLB_IP}

    To create a stable, human-friendly mapping to your Ingress IP, you must have a public DNS record. You can use any DNS provider and automation that you want. This tutorial uses Endpoints instead of creating a managed DNS zone. Endpoints provides a free Google-managed DNS record for a public IP.

  3. Run the following command to create the YAML specification file named dns-spec.yaml:

    cat <<EOF > dns-spec.yaml
swagger: "2.0"
info:
  description: "Cloud Endpoints DNS"
  title: "Cloud Endpoints DNS"
  version: "1.0.0"
paths: {}
host: "frontend.endpoints.${PROJECT}.cloud.goog"
x-google-endpoints:
- name: "frontend.endpoints.${PROJECT}.cloud.goog"
  target: "${GCLB_IP}"
EOF

    The YAML specification defines the public DNS record in the form of frontend.endpoints.${PROJECT}.cloud.goog, where ${PROJECT} is your unique project number.

  4. Deploy the dns-spec.yaml file in your Cloud project:

    gcloud endpoints services deploy dns-spec.yaml

    The output is similar to the following:

    Operation finished successfully. The following command can describe the Operation details:
 gcloud endpoints operations describe operations/rollouts.frontend.endpoints.edge2mesh.cloud.goog:442b2b38-4aee-4c60-b9fc-28731657ee08

Service Configuration [2021-11-14r0] uploaded for service [frontend.endpoints.edge2mesh.cloud.goog]

    Now that the IP and DNS are configured, you can generate a public certificate to secure the Ingress frontend. GKE Ingress supports Google-managed certificates as Kubernetes resources, which lets you provision them through declarative means.

Provision a TLS certificate

  1. In Cloud Shell, run the following command to create the ManagedCertificate manifest as managed-cert.yaml:

    cat <<EOF > managed-cert.yaml
apiVersion: networking.gke.io/v1
kind: ManagedCertificate
metadata:
  name: gke-ingress-cert
  namespace: asm-ingress
spec:
  domains:
    - "frontend.endpoints.${PROJECT}.cloud.goog"
EOF

    This YAML file specifies that the DNS name created through Endpoints is used to provision a public certificate. Because Google fully manages the lifecycle of these public certificates, they are automatically generated and rotated on a regular basis without direct user intervention.

  2. Deploy the managed-cert.yaml file in your GKE cluster:

    kubectl apply -f managed-cert.yaml

    The output is similar to the following:

    managedcertificate.networking.gke.io/gke-ingress-cert created

  3. Inspect the ManagedCertificate resource to check the progress of certificate generation:

    kubectl describe managedcertificate gke-ingress-cert -n asm-ingress

    The output is similar to the following:

    Name:         gke-ingress-cert
Namespace:    asm-ingress
Labels:       <none>
Annotations:  kubectl.kubernetes.io/last-applied-configuration:
                {"apiVersion":"networking.gke.io/v1","kind":"ManagedCertificate","metadata":{"annotations":{},"name":"gke-ingress-cert","namespace":"...
API Version:  networking.gke.io/v1
Kind:         ManagedCertificate
Metadata:
  Creation Timestamp:  2020-08-05T20:44:49Z
  Generation:          2
  Resource Version:    1389781
  Self Link:           /apis/networking.gke.io/v1/namespaces/asm-ingress/managedcertificates/gke-ingress-cert
  UID:                 d74ec346-ced9-47a8-988a-6e6e9ddc4019
Spec:
  Domains:
    frontend.endpoints.edge2mesh.cloud.goog
Status:
  Certificate Name:    mcrt-306c779e-8439-408a-9634-163664ca6ced
  Certificate Status:  Provisioning
  Domain Status:
    Domain:  frontend.endpoints.edge2mesh.cloud.goog
    Status:  Provisioning
Events:
  Type    Reason  Age   From                            Message
  ----    ------  ----  ----                            -------
  Normal  Create  44s   managed-certificate-controller  Create SslCertificate mcrt-306c779e-8439-408a-9634-163664ca6ced

    When the certificate is ready, the Certificate Status is Active.

Deploy the Ingress resource

  1. In Cloud Shell, run the following command to create the Ingress manifest as ingress.yaml:

    cat <<EOF > ingress.yaml
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: gke-ingress
  namespace: asm-ingress
  annotations:
    kubernetes.io/ingress.allow-http: "false"
    kubernetes.io/ingress.global-static-ip-name: "ingress-ip"
    networking.gke.io/managed-certificates: "gke-ingress-cert"
    kubernetes.io/ingress.class: "gce"
spec:
  defaultBackend:
    service:
      name: asm-ingressgateway
      port:
        number: 443
  rules:
  - http:
      paths:
      - path: /*
        pathType: ImplementationSpecific
        backend:
          service:
            name: asm-ingressgateway
            port:
              number: 443
EOF

    This manifest defines an Ingress resource that ties all of the previous resources together. The manifest specifies the following fields:

    • kubernetes.io/ingress.allow-http: "false" disables HTTP traffic on port 80 of the Google Cloud load balancer. This effectively prevents any clients connecting with unencrypted traffic because port 443 only listens for HTTPS, and port 80 is disabled.
    • kubernetes.io/ingress.global-static-ip-name: "ingress-ip" links the previously created IP address with the load balancer. This link allows the IP address to be created separately from the load balancer so that it can be reused separately from the load balancer lifecycle.
    • networking.gke.io/managed-certificates: "gke-ingress-cert" links this load balancer with the previously created Google-managed SSL Certificate resource.

  2. Deploy ingress.yaml in your cluster:

    kubectl apply -f ingress.yaml

  3. Inspect the Ingress resource to check the progress of the load balancer deployment:

    kubectl describe ingress gke-ingress -n asm-ingress

    The output is similar to the following:

    ...
Annotations:
  ingress.kubernetes.io/https-forwarding-rule:       k8s2-fs-fq3ng2uk-asm-ingress-gke-ingress-qm3qqdor
  ingress.kubernetes.io/ssl-cert:                    mcrt-306c779e-8439-408a-9634-163664ca6ced
  networking.gke.io/managed-certificates:            gke-ingress-cert
  kubernetes.io/ingress.global-static-ip-name:  ingress-ip
  ingress.gcp.kubernetes.io/pre-shared-cert:    mcrt-306c779e-8439-408a-9634-163664ca6ced
  ingress.kubernetes.io/backends:               {"k8s-be-31610--07bdde06b914144a":"HEALTHY","k8s1-07bdde06-asm-ingress-asm-ingressgateway-443-228c1881":"HEALTHY"}
  ingress.kubernetes.io/forwarding-rule:        k8s2-fr-fq3ng2uk-asm-ingress-gke-ingress-qm3qqdor
  ingress.kubernetes.io/https-target-proxy:     k8s2-ts-fq3ng2uk-asm-ingress-gke-ingress-qm3qqdor
  ingress.kubernetes.io/target-proxy:           k8s2-tp-fq3ng2uk-asm-ingress-gke-ingress-qm3qqdor
  ingress.kubernetes.io/url-map:                k8s2-um-fq3ng2uk-asm-ingress-gke-ingress-qm3qqdor
...

    The Ingress resource is ready when the ingress.kubernetes.io/backends annotations indicate that the backends are HEALTHY. The annotations also show the names of different Google Cloud resources that are provisioned, including backend services, SSL certificates, and HTTPS target proxies.

Install the self-signed ingress gateway certificate

In the following steps, you generate and install a certificate (as a Kubernetes secret resource) that enables the GFE to establish a TLS connection to the service mesh's ingress gateway. For more details about the requirements of the ingress gateway certificate, see the secure backend protocol considerations guide.

  1. In Cloud Shell, create the private key and certificate using openssl:

    openssl req -new -newkey rsa:4096 -days 365 -nodes -x509 \
 -subj "/CN=frontend.endpoints.${PROJECT}.cloud.goog/O=Edge2Mesh Inc" \
 -keyout frontend.endpoints.${PROJECT}.cloud.goog.key \
 -out frontend.endpoints.${PROJECT}.cloud.goog.crt

  2. Create the Secret in the asm-ingress namespace:

    kubectl -n asm-ingress create secret tls edge2mesh-credential \
 --key=frontend.endpoints.${PROJECT}.cloud.goog.key \
 --cert=frontend.endpoints.${PROJECT}.cloud.goog.crt

Configure the ingress gateway for external load balancing

In the following steps, you create a shared Gateway resource in the asm-ingress namespace. Gateways are generally owned by the platform admins or network admins team. Therefore, the Gateway resource is created in the asm-ingress namespace owned by the platform admin and could be use in other namespaces via their own VirtualService entries.

  1. In Cloud Shell, run the following command to create the Gateway manifest as ingress-gateway.yaml:

    cat <<EOF > ingress-gateway.yaml
apiVersion: networking.istio.io/v1alpha3
kind: Gateway
metadata:
    name: asm-ingressgateway
    namespace: asm-ingress
spec:
  selector:
    asm: ingressgateway
  servers:
  - port:
      number: 443
      name: https
      protocol: HTTPS
    hosts:
    - "*" # IMPORTANT: Must use wildcard here when using SSL, see note below
    tls:
      mode: SIMPLE
      credentialName: edge2mesh-credential
EOF

    Note that you must use the wildcard * entry in the hosts field in the Gateway. GCLB does not use SNI extension to the backends. Using the wildcard entry sends the encrypted packet (from GCLB) to the ASM ingress gateway. ASM Ingress gateway decrypts the packet and uses the HTTP Host Header (in the decrypted packet) to make routing decisions (based on VirtualService entries).

  2. Deploy ingress-gateway.yaml in your cluster:

    kubectl apply -f ingress-gateway.yaml

    The output is similar to the following:

    gateway.networking.istio.io/asm-ingressgateway created

Installing the Online Boutique sample app

  1. In Cloud Shell, create a dedicated onlineboutique namespace:

    kubectl create namespace onlineboutique

  2. Add a namespace label to the onlineboutique namespace:

    kubectl label namespace onlineboutique istio-injection=enabled

    The output is similar to the following:

    namespace/onlineboutique labeled

    Labeling the onlineboutique namespace with istio-injection=enabled instructs Anthos Service Mesh to automatically inject Envoy sidecar proxies when an application is deployed.

  3. Download the Kubernetes YAML files for the Online Boutique sample app:

    curl -LO \
    https://raw.githubusercontent.com/GoogleCloudPlatform/microservices-demo/main/release/kubernetes-manifests.yaml

  4. Deploy the Online Boutique app:

    kubectl apply -f kubernetes-manifests.yaml -n onlineboutique

    The output is similar to the following:

    deployment.apps/frontend created
service/frontend created
service/frontend-external created
...

  5. Ensure that all deployments are up and running:

    kubectl get pods -n onlineboutique

    The output is similar to the following:

    NAME                                     READY   STATUS    RESTARTS   AGE
adservice-d854d8786-fjb7q                2/2     Running   0          3m
cartservice-85b5d5b4ff-8qn7g             2/2     Running   0          2m59s
checkoutservice-5f9bf659b8-sxhsq         2/2     Running   0          3m1s
...

  6. Run the following command to create the VirtualService manifest as frontend-virtualservice.yaml:

    cat <<EOF > frontend-virtualservice.yaml
apiVersion: networking.istio.io/v1alpha3
kind: VirtualService
metadata:
  name: frontend-ingress
  namespace: onlineboutique
spec:
  hosts:
  - "frontend.endpoints.${PROJECT}.cloud.goog"
  gateways:
  - asm-ingress/asm-ingressgateway
  http:
  - route:
    - destination:
        host: frontend
        port:
          number: 80
EOF

    Note that the VirtualService is created in the application namespace (onlineboutique). Typically, the application owner decides and configures how and what traffic gets routed to the frontend application so VirtualService is deployed by the app owner.

  7. Deploy frontend-virtualservice.yaml in your cluster:

    kubectl apply -f frontend-virtualservice.yaml

    The output is similar to the following:

    virtualservice.networking.istio.io/frontend-virtualservice created

  8. Access the following link:

    echo "https://frontend.endpoints.${PROJECT}.cloud.goog"

    Your Online Boutique frontend is displayed.

    Products shown on Online Boutique home page.

  9. To display the details of your certificate, click View site information in your browser's address bar, and then click Certificate (Valid).

    The certificate viewer displays details for the managed certificate, including the expiration date and who issued the certificate.

You now have a global HTTPS load balancer serving as a frontend to your service mesh-hosted application.

Clean up

After you've finished the tutorial, you can clean up the resources you created on Google Cloud so you won't be billed for them in the future. You can either delete the project entirely or delete cluster resources and then delete the cluster.

Delete the project

  1. In the Google Cloud console, go to the Manage resources page.

    Go to Manage resources

  2. In the project list, select the project that you want to delete, and then click Delete.
  3. In the dialog, type the project ID, and then click Shut down to delete the project.

Delete the individual resources

If you want to keep the Cloud project you used in this tutorial, delete the individual resources:

  1. Delete the Ingress resource:

    kubectl delete -f ingress.yaml

  2. Delete the managed certificate:

    kubectl delete -f managed-cert.yaml

  3. Delete the Endpoints DNS entry:

    gcloud endpoints services delete "frontend.endpoints.${PROJECT}.cloud.goog"

    The output is similar to the following:

    Are you sure? This will set the service configuration to be deleted, along
with all of the associated consumer information. Note: This does not
immediately delete the service configuration or data and can be undone using
the undelete command for 30 days. Only after 30 days will the service be
purged from the system.

  4. When you are prompted to continue, enter Y.

    The output is similar to the following:

    Waiting for async operation operations/services.frontend.endpoints.edge2mesh.cloud.goog-5 to complete...
Operation finished successfully. The following command can describe the Operation details:
 gcloud endpoints operations describe operations/services.frontend.endpoints.edge2mesh.cloud.goog-5

  5. Delete the static IP address:

    gcloud compute addresses delete ingress-ip --global

    The output is similar to the following:

    The following global addresses will be deleted:

 - [ingress-ip]

  6. When you are prompted to continue, enter Y.

    The output is similar to the following:

    Deleted
[https://www.googleapis.com/compute/v1/projects/edge2mesh/global/addresses/ingress-ip].

  7. Delete the GKE cluster:

    gcloud container clusters delete $CLUSTER_NAME --zone $CLUSTER_LOCATION

What's next