
Create Kubernetes services for Elasticsearch in the production namespace using a cluster IP for internal access, configuring Elasticsearch and Elastic Discovery via a YAML manifest.
Create a persistent volume claim using Azure managed premium storage to provision a 10 GB disk for Elasticsearch, then attach it to pods in the production namespace.
Create and deploy a kibana manifest to Azure Kubernetes Service, wiring Kibana to Elasticsearch, exposing it with a load balancer and persistent volumes.
Explore how logstash collects data from multiple sources, transforms it, and ships it to Elasticsearch, with hands-on steps to create and deploy a logstash pipeline in cabana.
Discover Lens, an open source tool to manage multiple Kubernetes clusters via a visual user interface, import kube configs, connect/disconnect clusters, view pods, logs, and helm charts.
Learn to deploy and manage Kubernetes resources with K8s Lens, apply manifests, scale deployments and replicas, inspect logs, and create daemon sets and secrets for an Elasticsearch cluster.
Kubernetes is a buzz word, whosoever deals managing multiple containers and think of better orchestrating the containers. Kubernetes is the platform, however Kubernetes is not an easy to learn, this course has been tailor made to keep the course really simple and easy.
This course helps you learn Kubernetes fundamentals right from scratch, Azure Kubernetes Service (AKS) makes deploying and managing containerised applications easy. It offers serverless Kubernetes, backed by power of Azure leveraging features like Active Directory to control fine grained access on who has access to what.
How the course is shaped?
We start off writing terraform script to spin up Azure kubernetes Service along with Azure Container Registry.
Generate secrets for AKS to get deployed.
Deploy Kubernetes Cluster on Azure
Introduction to Kubernetes Dashboard
Deploy dashboard on Azure Kubernetes Service
We push docker images to Azure Container Registry
We start with the fundamentals of kubernetes like namespaces, deployment, services, statefulsets, pods, configmaps
and then the fun part where we start off with deploying workloads on AKS just like you would do it on a production system.
we join the services and get the Kibana UI up and running.
We use rolling update and replica sets to keep the service highly available.
Use a static public IP address and DNS label with the Azure Kubernetes Service (AKS) load balancer
This course is one of the few in the marketplace, where it is being regularly updated almost realtime basis as soon as the publisher launch any new set of feature, we make sure learner enrolling into the course get the best out of the content.
We also as a team strive be customer focused by making sure whatever queries are being put on direct messages or in community, we try to get back to the learner within 24 hours if not early, there have been scenarios where in our instructors have been on screen sharing session with the users and helped them solving the problems.