Deploy Fusion 5 on Amazon Elastic Kubernetes Service (EKS)

Fusion supports deployment on Amazon Elastic Kubernetes Service (EKS). This topic explains how to deploy a Fusion cluster on EKS using the setup_f5_eks.sh script in the fusion-cloud-native repository.

Prerequisites

This section covers prerequisites and background knowledge needed to help you understand the structure of this document and how the Fusion installation process works with Kubernetes.

Release Name and Namespace

Before installing Fusion, you need to choose a Kubernetes namespace to install Fusion into. Think of a K8s namespace as a virtual cluster within a physical cluster. You can install multiple instances of Fusion in the same cluster in separate namespaces. However, please do not install more than one Fusion release in the same namespace.

NOTE: All Fusion services must run in the same namespace, i.e. you should not try to split a Fusion cluster across multiple namespaces.

Use a short name for the namespace, containing only letters, digits, or dashes (no dots or underscores). The setup scripts in this repo use the namespace for the Helm release name by default.

Install Helm

Helm is a package manager for Kubernetes that helps you install and manage applications on your Kubernetes cluster. Regardless of which Kubernetes platform you’re using, you need to install helm as it is required to install Fusion for any K8s platform. On MacOS, you can do:

brew install kubernetes-helm

If you already have helm installed, make sure you’re using the latest version:

brew upgrade kubernetes-helm

For other OS, please refer to the Helm installation docs: https://helm.sh/docs/using_helm/

The Fusion helm chart requires that helm is greater than version 3.0.0; check your Helm version by running helm version --short.

Helm User Permissions

If you require that fusion is installed by a user with minimal permissions, instead of an admin user, then the role and cluster role that will have to be assigned to the user within the namespace that you wish to install fusion in are documented in the install-roles directory.

To use these role in a cluster, as an admin user first create the namespace that you wish to install fusion into:

k create namespace fusion-namespace

Apply the role.yaml and cluster-role.yaml files to that namespace

k apply -f cluster-role.yaml
k apply -f --namespace fusion-namespace role.yaml

Then bind the rolebinding and clusterolebinding to the install user:

k create --namespace fusion-namespace rolebinding fusion-install-rolebinding --role fusion-installer --user <install_user>
k create clusterrolebinding fusion-install-rolebinding --clusterrole fusion-installer --user <install_user>

You will then be able to run the helm install command as the <install_user>

Clone fusion-cloud-native from Github

You should clone this repo from github as you’ll need to run the scripts on your local workstation:

git clone https://github.com/lucidworks/fusion-cloud-native.git

You should get into the habit of pulling this repo for the latest changes before performing any maintenance operations on your Fusion cluster to ensure you have the latest updates to the scripts.

cd fusion-cloud-native
git pull

Cloning the github repo is preferred so that you can pull in updates to the scripts, but if you are not a git user, then you can download the project: https://github.com/lucidworks/fusion-cloud-native/archive/master.zip. Once downloaded, extract the zip and cd into the fusion-cloud-native-master directory.

The setup_f5_eks.sh script provided in this repo is strictly optional. The script is mainly to help those new to Kubernetes and/or Fusion get started quickly. If you’re already familiar with K8s, Helm, and EKS, then you use Helm directly to install Fusion into an existing cluster or one you create yourself using the process described here.

If you’re new to Amazon Web Services (AWS), then please visit the Amazon Web Services Getting Started Center to set up an account.

If you’re new to Kubernetes and EKS, then we recommend going through Amazon’s EKS Workshop before proceeding with Fusion.

Set up the AWS CLI tools

Before launching an EKS cluster, you need to install and configure kubectl, aws, eksctl, aws-iam-authenticator using the links provided below:

Required AWS Command-line Tools:
  1. kubectl: Install kubectl

  2. aws: Installing the AWS CLI

  3. eksctl: Getting Started with eksctl

  4. aws-iam-authenticator: AWS IAM Authenticator for Kubernetes

Run aws configure to configure a profile for authenticating to AWS. You’ll use the profile name you configure in this step, which defaults to default, as the -p argument to the setup_f5_eks.sh script in the next section.

Note
When working in Ubuntu, avoid using the eksctl snap version. Alternative sources can have different versions that could cause command failures.

Set up Fusion on EKS

To create a cluster in EKS the following IAM policies are required:

  • AmazonEC2FullAccess

  • AWSCloudFormationFullAccess

Table 1. EKS Permissions

eks:DeleteCluster

eks:UpdateClusterVersion

eks:ListUpdates

eks:DescribeUpdate

eks:DescribeCluster

eks:ListClusters

eks:CreateCluster

Table 2. VPC Permissions

ec2:DeleteSubnet

ec2:DeleteVpcEndpoints

ec2:CreateVpc

ec2:AttachInternetGateway

ec2:DetachInternetGateway

ec2:DisassociateSubnetCidrBlock

ec2:DescribeVpcAttribute

ec2:AssociateVpcCidrBlock

ec2:ModifySubnetAttribute

ec2:DisassociateVpcCidrBlock

ec2:CreateVpcEndpoint

ec2:DescribeVpcs

ec2:CreateInternetGateway

ec2:AssociateSubnetCidrBlock

ec2:ModifyVpcAttribute

ec2:DeleteInternetGateway

ec2:DeleteVpc

ec2:CreateSubnet

ec2:DescribeSubnets

ec2:ModifyVpcEndpoint

Table 3. IAM Permissions

iam:CreateInstanceProfile

iam:DeleteInstanceProfile

iam:GetRole

iam:GetPolicyVersion

iam:UntagRole

iam:GetInstanceProfile

iam:GetPolicy

iam:TagRole

iam:RemoveRoleFromInstanceProfile

iam:DeletePolicy

iam:CreateRole

iam:DeleteRole

iam:AttachRolePolicy

iam:PutRolePolicy

iam:ListInstanceProfiles

iam:AddRoleToInstanceProfile

iam:CreatePolicy

iam:ListInstanceProfilesForRole

iam:PassRole

iam:DetachRolePolicy

iam:DeleteRolePolicy

iam:CreatePolicyVersion

iam:GetRolePolicy

iam:DeletePolicyVersion

Download and run the setup_f5_eks.sh script to install Fusion 5.x in a EKS cluster. To create a new cluster and install Fusion, simply do:

./setup_f5_eks.sh -c <cluster_name> -p <aks_resource_group>

If you want the script to create a cluster for you (the default behavior), then you need to pass the --create option with either demo or multi_az. If you don’t want the script to create a cluster, then you need to create a cluster before running the script and simply pass the name of the existing cluster using the -c parameter.

Use the --help option to see full script usage.

WARNING If using Helm V2, the setup_f5_eks.sh script installs Helm’s tiller component into your EKS cluster with the cluster admin role. If you don’t want this, then please upgrade to Helm v3.

WARNING The setup_f5_eks.sh script creates a service account that provides S3 read-only permissions to the created pods.

After running the setup_f5_eks.sh script, proceed to the Verifying the Fusion Installation section below.

EKS cluster overview

The EKS cluster is created using eksctl (https://eksctl.io/). By default it will setup the following resources in your AWS account:

  • A dedicated VPC for the EKS cluster in the specified region with CIDR: 192.168.0.0/16

  • 3 Public and 3 Private subnets within the created VPC, each with a /19 CIDR range, along with the corresponding route tables.

  • A NAT gateway in each Public subnet

  • An Auto Scaling Group of the instance type specified by the script, which defaults to m5.2xlarge, with 3 instances spanning the public subnets.

See https://eksctl.io/usage/vpc-networking/ for more information on the networking setup.

EKS Ingress

The setup_f5_eks.sh script exposes the Fusion proxy service on an external DNS name provided by an ELB over HTTP. This is done for demo or getting started purposes. However, you’re strongly encouraged to configure a K8s Ingress with TLS termination in front of the proxy service. See: https://aws.amazon.com/premiumsupport/knowledge-center/terminate-https-traffic-eks-acm/

Our EKS script creates a classic ELB for exposing fusion proxy service. In case you need to change this behavior and use AWS ALB Ingress Controller instead you can use the following parameters when running the setup_f5_eks.sh script:

--deploy-alb     # Tells the script to deploy an ALB
--alb-namespace  # Namespace to deploy the ALB, if it is not specicified the namespace for fusion would be used.

In case you need to deploy an internal ALB you can use the --internal-alb option. This will create the nodes in the internal subnets. Fusion will be reachable from an AWS instance located in any of the external subnets on the same VPC.

The ALB is configured by default with --set autoDiscoverAwsRegion=true and --set autoDiscoverAwsVpcID=true. To use an ALB also an ingress with a DNS name is required, you can use the -h option to create an ingress with the required DNS name.

Finally, use Route 53 or your DNS provider for creating an A ALIAS DNS record for your DNS name pointing to the ingress ADRESS. You can get the address listing the ingress using the command kubectl get ing.

Provide access to the EKS cluster to other users

Initially, only the user that created the Amazon EKS cluster has system:masters permissions to configure the cluster. In order to extend the permissions, a ConfigMap should be created to allow access to IAM users or roles.

For providing these permissions, use the following yaml file as a template, replacing the required values:

aws-auth.yaml

apiVersion: v1
kind: ConfigMap
metadata:
  name: aws-auth
  namespace: kube-system
data:
  mapRoles: |
    - rolearn: <node_instance_role_arn>
      username: system:node:{{EC2PrivateDNSName}}
      groups:
        - system:bootstrappers
        - system:nodes
  mapUsers: |
    - userarn: arn:aws:iam::<account_id>:user/<username>
      username: <username>
      groups:
        - system:masters

Use the following command for applying the yaml file: kubectl apply -f aws-auth.yaml

Remove EKS cluster

In case you have deployed an ALB ingress controller, you would need to remove the policy that was created for managing the ALB before removing the cluster. You can use the following command for it:

aws iam --profile <profile-name> delete-policy --policy-arn arn:aws:iam::<account_id>:policy/eksctl-<cluster-name>-alb-policy

Also you can remove it manually using the AWS IAM console, searching for eksctl-<cluster-name>-alb-policy.

After that you should remove the ALB with helm delete, list the current releases with helm list.

The EKS cluster is created using Cloudformation stacks so you need to remove them to delete the cluster, you can check them in the AWS Cloudformation Console, check for the following stacks:

  • eksctl-<cluster-name>-nodegroup-standard-workers

  • eksctl-<cluster-name>-cluster

The eksctl-<cluster-name>-nodegroup-standard-workers stack should be the first to be removed. After that we can remove the eksctl-<cluster-name>-cluster stack.

Also you can use the following commands>:

aws cloudformation --profile <profile-name> delete-stack --stack-name eksctl-<cluster-name>-nodegroup-standard-workers
aws cloudformation --profile <profile-name> delete-stack --stack-name eksctl-<cluster-name>-cluster

Verifying the Fusion Installation

In this section, we provide some tips on how to verify the Fusion installation. First, let’s review some useful kubectl commands.

Enhance the K8s Command-line Experience

When working with Kubernetes on the command-line, it’s useful to create a shell alias for kubectl, e.g.:

alias k=kubectl

Here is a list of tools we found useful for improving your command-line experience with Kubernetes:

Useful kubectl commands

Set the namespace for kubectl if not using the default:

kubectl config set-context --current --namespace=<NAMESPACE>

This saves you from having to pass -n with every command.

Get a list of running pods: k get pods

Get logs for a pod using a label: k logs –l app.kubernetes.io/component=query-pipeline

Get pod deployment spec and details: k get pods <pod_id> -o yaml

Get details about a pod events: k describe po <pod_id>

Port forward to a specific pod: k port-forward <pod_id> 8983:8983

SSH into a pod: k exec -it <pod_id> — /bin/bash

CPU/Memory usage report for pods: k top pods

Forcefully kill a pod: k delete po <pod_id> --force --grace-period 0

Scale up (or down) a deployment: k scale deployment.v1.apps/<id> --replicas=N

Get a list of pod versions: k get po -o jsonpath='{..image}' | tr -s '' '\n' | sort | uniq

Check Fusion Pods and Services

Once the install script completes, you can check that all pods and services are available using:

kubectl get pods

If all goes well, you should see a list of pods similar to:

NAME                                                        READY   STATUS    RESTARTS   AGE
seldon-controller-manager-6675874894-qxwrv                  1/1     Running   0          8m45s
f5-admin-ui-74d794f4f8-m5jms                                1/1     Running   0          8m45s
f5-ambassador-fd6b9b5dc-7ghf6                               1/1     Running   0          8m43s
f5-api-gateway-6b9998b9c-tmchk                              1/1     Running   0          8m45s
f5-auth-ui-7565564b4c-rdc74                                 1/1     Running   0          8m42s
f5-classic-rest-service-0                                   1/1     Running   3          8m44s
f5-devops-ui-77bb867ffb-fbzxd                               1/1     Running   0          8m42s
f5-fusion-admin-78b8f8fc7f-4d7l8                            1/1     Running   0          8m42s
f5-fusion-indexing-599c8d448-xzsvm                          1/1     Running   0          8m44s
f5-insights-665fd9f6fc-g5psw                                1/1     Running   0          8m43s
f5-job-launcher-84dd4c5c96-p8528                            1/1     Running   0          8m44s
f5-job-rest-server-6d44d964b8-xtnxw                         1/1     Running   0          8m45s
f5-logstash-0                                               1/1     Running   0          8m45s
f5-ml-model-service-6987dc94c9-9ppp8                        2/2     Running   1          8m45s
f5-monitoring-grafana-5d499dbb58-pzw72                      1/1     Running   0          10m
f5-monitoring-prometheus-kube-state-metrics-54d6678dv9h7h   1/1     Running   0          10m
f5-monitoring-prometheus-pushgateway-7d65c65b85-vwrwf       1/1     Running   0          10m
f5-monitoring-prometheus-server-0                           2/2     Running   0          10m
f5-pm-ui-86cbc5bb65-nd2n8                                   1/1     Running   0          8m44s
f5-pulsar-bookkeeper-0                                      1/1     Running   0          8m45s
f5-pulsar-broker-b56cc776f-56msx                            1/1     Running   0          8m45s
f5-query-pipeline-5d75d7d5f4-l2mdf                          1/1     Running   0          8m43s
f5-rest-service-7bb6cfc65f-7wfs2                            1/1     Running   0          8m42s
f5-rpc-service-987fdc648-dldwv                              1/1     Running   0          8m45s
f5-rules-ui-6b9d55b78f-9hzzj                                1/1     Running   0          8m43s
f5-solr-0                                                   1/1     Running   0          8m44s
f5-solr-exporter-c4687c785-jsm7x                            1/1     Running   0          8m45s
f5-ui-6cdbcc68c6-rj9cq                                      1/1     Running   0          8m45s
f5-webapps-6d6bb9bfd-hm4qx                                  1/1     Running   0          8m45s
f5-workflow-controller-7b66679fb7-sjbvp                     1/1     Running   0          8m44s
f5-zookeeper-0                                              1/1     Running   0          8m45s

The number of pods per deployment / statefulset will vary based on your cluster size and replicaCount settings in your custom values YAML file. Also, don’t worry if you see some pods having been restarted as that just means they were too slow to come up and Kubernetes killed and restarted them. You do want to see at least one pod running for every service. If a pod is not running after waiting a sufficient amount of time, use kubectl logs <pod_id> to see the logs for that pod; to see the logs for previous versions of a pod, use: kubectl logs <pod_id> -p. You can also look at the actions Kubernetes performed on the pod using kubectl describe po <pod_id>.

To see a list of Fusion services, do:

kubectl get svc

For an overview of the various Fusion 5 microservices, see: https://doc.lucidworks.com/fusion-server/5.0/deployment/kubernetes/microservices.html

Once you’re ready to build a Fusion cluster for production, please see the Fusion 5 Survival Guide in this repo.

Upgrading with Zero Downtime

One of the most powerful features provided by Kubernetes and a cloud-native microservices architecture is the ability to do a rolling update on a live cluster. Fusion 5 allows customers to upgrade from Fusion 5.x.y to a later 5.x.z version on a live cluster with zero downtime or disruption of service.

When Kubernetes performs a rolling update to an individual microservice, there will be a mix of old and new services in the cluster concurrently (only briefly in most cases) and requests from other services will be routed to both versions. Consequently, Lucidworks ensures all changes we make to our service do not break the API interface exposed to other services in the same 5.x line of releases. We also ensure stored configuration remains compatible in the same 5.x release line.

Lucidworks releases minor updates to individual services frequently, so our customers can pull in those upgrades using Helm at their discretion.

To upgrade your cluster at any time, use the --upgrade option with our setup scripts in this repo.

The scripts in this repo automatically pull in the latest chart updates from our Helm repository and deploy any updates needed by doing a diff of your current installation and the latest release from Lucidworks. To see what would be upgraded, you can pass the --dry-run option to the script.

Grafana Dashboards

Get the initial Grafana password from a K8s secret by doing:

kubectl get secret --namespace "${NAMESPACE}" ${RELEASE}-monitoring-grafana \
  -o jsonpath="{.data.admin-password}" | base64 --decode ; echo

With Grafana, you can either setup a temporary port-forward to a Grafana pod or expose Grafana on an external IP using a K8s LoadBalancer. To define a LoadBalancer, do (replace ${RELEASE} with your Helm release label):

kubectl expose deployment ${RELEASE}-monitoring-grafana --type=LoadBalancer --name=grafana --port=3000 --target-port=3000

You can use kubectl get services --namespace <namespace> to determine when the load balancer is setup and its IP address. Direct your browser to http://<GrafanaIP>:3000 and enter the username admin@localhost and the password that was returned in the previous step.

This will log you into the application. It is recommended that you create another administrative user with a more desirable password.

The dashboards and datasoure will be setup for you in grafana, simply navigate to DashboardsManage to view the vailable dashboards