Kubernetes is a portable, extensible, and open-source platform for managing containerized workloads and services that facilitate declarative configuration and automation. It allows us to run distributed systems resiliently, with scaling data and failover for applications. It provides Self-Healing for crash data, Automatic Binpaching, Service discovery, load balancing, storage orchestration, secret and configuration management, Batch execution, horizontal scaling, and automatic rollbacks and rollouts.
Here we are discussing Elastic Cloud on Kubernetes.
It is a container orchestrator that helps its users to make sure that each container is supposed to be active and that the containers can work together.
Challenges of Running on Kubernetes
There is a certain number of resources a user needs to manage on their Elastic Cloud on Kubernetes.
- Secrets, Services
- Persistent Volumes ConfigMaps
- Deployments, Statefulsets
- Configuration change
- Version Upgrade
- Elasticsearch is an essential part of Kubernetes monitoring. It is a search engine and consists of some distributed database running on multiple servers, so it requires dealing with availability and consistency when changes are required on topology. For example, when a user needs to add new nodes or remove nodes, they need the Elasticsearch cluster to stay available.
- The user also needs to deal with volume management to manage terabytes of data on their cluster.
It also provides a micro-service model with scaling benefits for databases to manage and transform data and memory space more accurately without wasting space idle. The individual services can scale to match their traffic without over-provisioning.
Having one machine for each service would require many resources and a whole bunch of machines and be costly. That’s why Kubernetes’s containers are a perfect choice. Containers allow teams to package up their services accurately with all the applications, their dependencies, and any necessary configuration gets delivered together.
How does Kubernetes help with Container Upgrading?
Upgrading a container is also easy since the user can create a new version of the container deploy it in place of the old one. But how can upgrades be done without downtime is a problem? And how can an application developer debug the issue and observe what’s happening?
Here Kubernetes API is all about managing the containers on virtual machines or nodes. The nodes in the containers are run grouped as a cluster, and each container has an endpoint, DNS, Storage, and scalability. The Kubernetes automates most of the repetition and inefficiencies of doing everything by hand.
Elasticsearch Cloud on Kubernetes (ECK)
Elastic Cloud on Kubernetes automates the deployment, provisioning, management, and orchestration of Elasticsearch, Kibana, APM Server, Enterprise Search, and Beats on Kubernetes based on the operator pattern. ECK is a Kubernetes operator; the operators are the clients of the Kubernetes API; they will communicate with Kubernetes API.
The ECK allows us to deploy the entire Elastic Stack, Elasticsearch, Kibana, APM Servers, Enterprise Search, and Beats on the Kubernetes cluster. ECK is also compatible with most Kubernetes distributions, including Openshift, Vanilla, etc. It is built on the Kubernetes Operator pattern and extends Kubernetes orchestration capabilities to support the setup and management of Elasticsearch and Kibana on Kubernetes.
Moreover, it supports orchestrating Elasticsearch with advanced topologies such as Hot / Warm / Clod nodes deployment. The Hot nodes would have high-speed underlying storage.
Deploy and Manage
Elasticsearch, Kibana, and APM Server, and more.
Supports Multiple Kubernetes Distros
Azure Kubernetes Service (AKS), Elastic Kubernetes Service (EKS), Google Kubernetes Engine (GKE), Vanilla Kubernetes, and Red Hat Openshift.
It allows us to deploy one or dozens of clusters.
All clusters have security and TLS configured.
Scale-up, scale down, rolling upgrades with no downtime nor data loss.
Hot-warm-cold deployments, dedicated masters / ingest, and machine learning.
Author: SVCIT Editorial Copyright
Silicon Valley Cloud IT, LLC.