Deploying Redpanda for Production

This guide will take you through what is needed to setup a production cluster of Redpanda.

If you just want to try out Redpanda, check out our Getting Started Guides for Linux, MacOS, Docker, or Kubernetes.

Before you set up your Redpanda cluster, refer to the Performance and storage tuning documentation for guidelines on cluster creation, such as avoiding out-of-disk outages.

Prepare infrastructure

For the best performance, we need to provision the hardware according to these hardware requirements:

  • XFS for the data directory of Redpanda (/var/lib/redpanda/data)

  • A kernel that is at least 3.10.0-514, but a 4.18 or newer kernel is preferred

  • Local NVMe, RAID-0 when using multiple disks

  • 2GB of memory per core

  • TCP ports:

    • 33145 - Internal RPC Port

    • 9092 - Kafka API Port

    • 8082 - Pandaproxy Port

    • 8081 - Schema Registry Port

    • 9644 - Prometheus and HTTP admin port

If you want, you can use Terraform to deploy Redpanda.

Install Redpanda

After the hardware is provisioned, install Redpanda and configure it for production use.

You can also install Redpanda using an Ansible playbook.

Step 1: Install the binary

On Fedora/RedHat Systems:

curl -1sLf '' | \
sudo -E bash && sudo yum install redpanda -y

On Debian Systems:

curl -1sLf '' | \
sudo -E bash && sudo apt install redpanda -y

Step 2: Set Redpanda production mode

By default Redpanda is installed in development mode, which turns off hardware optimization. To enable hardware optimization, set Redpanda to run in production mode:

sudo rpk redpanda mode production

We then need to tune the hardware, which can be done by running the following on each node:

sudo rpk redpanda tune all
Optional: Benchmark your SSD

On taller machines it is recommended benchmarking your SSD. This can be done with rpk iotune. You only need to run this once. For reference, a decent local NVMe SSD should yield around 1GB/s sustained writes. rpk iotune will capture SSD wear and tear and give accurate measurements of what your hardware is actually capable of delivering. It is recommended you run this before benchmarking.

If you are on AWS, GCP or Azure, creating a new instance and upgrading to an image with a recent Linux Kernel version is often the easiest way to work around bad devices.

sudo rpk iotune # takes 10mins

Step 3: Configure and start the root node

Now that the software is installed we need to configure it. The first step is to setup the root node. The root node will start as a standalone node, and every other one will join it, forming a cluster along the way.

For the root node we’ll choose 0 as its ID. --self tells the node which interface address to bind to. Usually you want that to be its private IP.

sudo rpk config bootstrap --id 0 --self <ip> && \
sudo systemctl start redpanda-tuner redpanda

Step 4: Configure and start the other nodes

For every other node, we just have to choose a unique integer id for it and let it know where to reach the root node.

sudo rpk config bootstrap --id <unique id> \
--self <private ip>                        \
--ips <root node ip> &&                    \
sudo systemctl start redpanda-tuner redpanda

Step 5: Verify the installation

You can verify that the cluster is up and running by checking the logs:

journalctl -u redpanda

You should also be able to create a topic with the following command:

rpk topic create panda