20 docs tagged with "Kubernetes"

This topic explains Redpanda's tips and recommendations for Kubernetes deployments.

Expose your Redpanda cluster to clients outside of your Kubernetes cluster using a NodePort Service.

Expose your Redpanda cluster to clients outside of your Kubernetes cluster using LoadBalancer Services.

Customize the advertised ports for each listener on all Redpanda brokers, or disable listeners altogether.

Use the Simple Authentication and Security Layer (SASL) framework to provide authentication between Redpanda brokers and clients.

Configure the Helm chart to use PersistentVolumes, hostPath volumes, or emptyDir volumes.

Use TLS to authenticate Redpanda brokers and encrypt communication between clients and brokers.

You can customize the Redpanda Helm chart to configure the cluster and the Kubernetes components that the chart deploys.

Set up data archiving to back up topics to cloud storage.

This topic describes how to use the Redpanda Helm chart to deploy a Redpanda cluster in Kubernetes.

Enable rack awareness to place partition replicas across different failure zones.

This topic is a checklist with the prerequisites and system requirements for installing production Redpanda in a Kubernetes cluster using the Helm chart.

Configure your Pod resources such as memory, CPU, and storage.

Learn how internal and external connectivity works when Redpanda is running in Kubernetes.

The production deployment tasks involve Kubernetes administrators (admins) as well as Kubernetes users.

Kubernetes is a container orchestration tool that helps you to manage Redpanda cluster deployments using declarative configuration files called manifests.

Create read-only topics (Remote Read Replica topics) that mirror topics on a different cluster.

Configure your Redpanda cluster to offload log segments to cloud storage and save storage costs.

Find advice on how to diagnose and troubleshoot problems with Redpanda in Kubernetes.

To get the best performance from your hardware, set Redpanda to production mode on each worker node and run the autotuner tool. The autotuner identifies the hardware configuration on your worker node and optimizes the Linux kernel to give you the best performance.