How to deploy Elasticsearch, Fluentd and Kibana (EFK) in Kubernetes?

Logging Operator EFK(Elasticsearch, Fluentd, and Kibana)

Logging Operator is an operator created in Golang to set up and manage EFK(Elasticsearch, Fluentd, and Kibana) cluster inside Kubernetes and Openshift environment. This operator is capable of setting up each individual component of EFK cluster separately.

Supported Features

• Setup of elasticsearch cluster with different nodes type:- master, data, ingestion, and client.
• Customizable configuration for elasticsearch, fluentd stack.
• Setup of fluentd as light-weight log-shipper as Daemonset.
• Kibana will be set up as visualization tool for elastic stack.
• Seamless upgrades of elasticsearch, fluentd, and kibana.
• Security best practices support for complete stack such as TLS, elastic security.
• Kubernetes resources objects support like:- resources, securityContext, affinity, tolerations, etc.
• Elasticsearch plugins and keystore seamless support with operator

URL – https://operatorhub.io/operator/logging-operator

Elasticsearch (ECK) Operator

Elastic Cloud on Kubernetes (ECK) is the official operator by Elastic for automating the deployment, provisioning, management, and orchestration of Elasticsearch, Kibana, APM Server, Beats, Enterprise Search, Elastic Agent, Elastic Maps Server, and Logstash on Kubernetes.

Current features:

• Elasticsearch, Kibana, APM Server, Enterprise Search, Beats, Elastic Agent, Elastic Maps Server, and Logstash deployments
• TLS Certificates management
• Safe Elasticsearch cluster configuration and topology changes
• Persistent volumes usage
• Custom node configuration and attributes
• Secure settings keystore updates

URL – https://operatorhub.io/operator/elastic-cloud-eck

Elasticsearch, Fluentd and Kibana (EFK) Using Helm

Elasticsearch using Helm

URL – https://artifacthub.io/packages/helm/elastic/elasticsearch

Kibana using Helm

URL – https://artifacthub.io/packages/helm/elastic/kibana

fluentd using Helm

URL – https://artifacthub.io/packages/helm/bitnami/fluentd

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Rajesh Kumar

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