Deploy Fusion 5 on Other Kubernetes Platforms

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.

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:

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

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.

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

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.

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.

You should upgrade to the latest version of Helm v3 for working with Fusion. If you need to keep Helm V2 for other clusters, ensure Helm V3 is ahead of Helm V2 in your working shell’s PATH before proceeding.

We can deploy Fusion in an existing OpenShift cluster. This cluster should be created using OpenShift Infrastructure Provider. A Red Hat Customer Portal account is required. OpenShift Online services are not supported.

The easiest way to install on OpenShift is to run the setup_f5_k8s.sh script for your existing cluster; use the --help option to see script usage. For instance, the following command will install Fusion 5 into the specified namespace (-n) and OpenShift cluster (-c):

Tip: kubectl should work with your OpenShift cluster (see: https://docs.openshift.com/container-platform/4.1/cli_reference/usage-oc-kubectl.html) and Lucidworks recommends installing the latest kubectl for your workstation instead of using oc for installing Fusion 5. However, if you do not have kubectl installed, then you’ll need to update the upgrade script created by setup_f5_k8s.sh to use oc instead of kubectl (search and replace on the BASH script using a text editor).

When you’re ready to deploy Fusion to a production-like environment, refer to the Planning section of the Survival Guide.

Lucidworks recommends using Helm v3, but in case Tiller is required for Helm v2, the cluster security needs to be relaxed to allow images to run with different UIDs:

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

kubectl reference: https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands

Set the namespace for kubectl if not using the default:

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

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

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

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:

For an overview of the various Fusion 5 microservices, see: https://doc.lucidworks.com/fusion/5.3/149/fusion-microservices

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

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.

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

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):

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 Dashboards → Manage to view the vailable dashboards