Convert Figma logo to code with AI

kubernetes-sigs logokubespray

Deploy a Production Ready Kubernetes Cluster

16,045
6,447
16,045
140
View on GitHub

Top Related Projects

kubernetes's avatar

kops

15,907

Kubernetes Operations (kOps) - Production Grade k8s Installation, Upgrades and Management

rancher's avatar

rke

3,215

Rancher Kubernetes Engine (RKE), an extremely simple, lightning fast Kubernetes distribution that runs entirely within containers.

eksctl-io's avatar

eksctl

4,910

The official CLI for Amazon EKS

Azure's avatar

aks-engine

1,028

AKS Engine: legacy tool for Kubernetes on Azure (see status)

openshift's avatar

openshift-ansible

2,177

Install and config an OpenShift 3.x cluster

Quick Overview

Kubespray is an open-source project that provides a set of Ansible playbooks for deploying and managing Kubernetes clusters. It aims to be a production-ready solution for creating and maintaining highly available Kubernetes clusters on various cloud providers, bare metal, and virtualized environments.

Pros

  • Supports multiple operating systems and cloud providers
  • Highly customizable and configurable
  • Regularly updated to support the latest Kubernetes versions
  • Provides a consistent deployment experience across different environments

Cons

  • Steeper learning curve compared to managed Kubernetes solutions
  • Requires knowledge of Ansible for advanced customization
  • May require more manual intervention for upgrades and maintenance
  • Documentation can be overwhelming for beginners

Getting Started

To get started with Kubespray, follow these steps:

  1. Clone the Kubespray repository:

    git clone https://github.com/kubernetes-sigs/kubespray.git
cd kubespray

  2. Install dependencies:

    pip install -r requirements.txt

  3. Copy the sample inventory and customize it for your environment:

    cp -rfp inventory/sample inventory/mycluster

  4. Review and update the inventory/mycluster/group_vars files to configure your cluster.

  5. Deploy the cluster:

    ansible-playbook -i inventory/mycluster/hosts.yaml cluster.yml -b -v

For more detailed instructions and advanced configuration options, refer to the official Kubespray documentation.

Competitor Comparisons

kubernetes logo

kops

15,907

Kubernetes Operations (kOps) - Production Grade k8s Installation, Upgrades and Management

Pros of kops

  • Designed specifically for AWS, offering deep integration and optimization
  • Supports automatic upgrades and rolling updates of Kubernetes clusters
  • Provides built-in DNS management and integration with Route53

Cons of kops

  • Limited multi-cloud support compared to Kubespray's versatility
  • Steeper learning curve for users not familiar with AWS ecosystem
  • Less flexibility in customizing the underlying infrastructure

Code Comparison

Kubespray (using Ansible):

- name: Deploy Kubernetes cluster
  hosts: all
  roles:
    - { role: kubernetes/preinstall }
    - { role: kubernetes/node }
    - { role: etcd }

kops (using CLI):

kops create cluster \
  --name=mycluster.example.com \
  --zones=us-east-1a \
  --kubernetes-version=1.21.0
kops update cluster --yes

Key Differences

  1. Deployment approach: Kubespray uses Ansible for configuration management, while kops relies on its CLI and templates.
  2. Cloud support: Kubespray is more versatile across different cloud providers, whereas kops excels in AWS environments.
  3. Customization: Kubespray offers more flexibility in cluster configuration, while kops provides streamlined AWS-specific options.
  4. Maintenance: kops has built-in upgrade and update features, while Kubespray requires manual intervention for upgrades.
  5. Learning curve: kops may be easier for AWS users, while Kubespray's Ansible-based approach might be more familiar to system administrators.
rancher logo

rke

3,215

Rancher Kubernetes Engine (RKE), an extremely simple, lightning fast Kubernetes distribution that runs entirely within containers.

Pros of RKE

  • Simpler setup process with fewer dependencies
  • Tighter integration with Rancher ecosystem
  • Faster deployment times for small to medium-sized clusters

Cons of RKE

  • Less flexibility in customization compared to Kubespray
  • Limited support for advanced networking configurations
  • Smaller community and ecosystem compared to Kubespray

Code Comparison

RKE configuration example:

nodes:
  - address: 1.2.3.4
    user: ubuntu
    role: [controlplane,worker,etcd]

Kubespray inventory example:

all:
  hosts:
    node1:
      ansible_host: 1.2.3.4
      ip: 1.2.3.4
      access_ip: 1.2.3.4
    node2:
      ansible_host: 1.2.3.5
      ip: 1.2.3.5
      access_ip: 1.2.3.5

RKE focuses on a more streamlined configuration approach, while Kubespray offers more granular control over node roles and network settings. RKE's configuration is typically more concise, making it easier to set up and maintain for smaller deployments. Kubespray's inventory allows for more detailed node specifications and role assignments, which can be beneficial for larger, more complex cluster architectures.

eksctl-io logo

eksctl

4,910

The official CLI for Amazon EKS

Pros of eksctl

  • Specifically designed for Amazon EKS, offering seamless integration and optimized workflows
  • Simpler setup process with fewer dependencies, ideal for AWS-centric deployments
  • Supports GitOps-style cluster management through eksctl-managed add-ons

Cons of eksctl

  • Limited to Amazon EKS, lacking flexibility for multi-cloud or on-premises deployments
  • Less customization options compared to Kubespray's extensive configuration capabilities
  • Steeper learning curve for users not familiar with AWS-specific concepts and terminology

Code Comparison

eksctl:

apiVersion: eksctl.io/v1alpha5
kind: ClusterConfig
metadata:
  name: my-cluster
  region: us-west-2

Kubespray:

all:
  vars:
    ansible_user: ubuntu
    ansible_become: true
    kube_version: v1.21.0
    cluster_name: my-cluster

Both tools use YAML for configuration, but eksctl focuses on AWS-specific parameters, while Kubespray offers more general Kubernetes deployment options. eksctl's syntax is more concise and tailored for EKS, whereas Kubespray provides greater flexibility for various environments and configurations.

Azure logo

aks-engine

1,028

AKS Engine: legacy tool for Kubernetes on Azure (see status)

Pros of aks-engine

  • Specifically designed for Azure, offering deep integration with Azure services
  • Provides ARM templates for easy deployment and management of AKS clusters
  • Supports advanced Azure-specific features like Azure AD integration and Azure CNI

Cons of aks-engine

  • Limited to Azure cloud platform, lacking multi-cloud support
  • Requires more Azure-specific knowledge compared to Kubespray's platform-agnostic approach
  • May have a steeper learning curve for users not familiar with Azure ecosystem

Code Comparison

aks-engine (cluster definition):

{
  "apiVersion": "vlabs",
  "properties": {
    "orchestratorProfile": {
      "orchestratorType": "Kubernetes"
    },
    "masterProfile": {
      "count": 1,
      "dnsPrefix": "myaks",
      "vmSize": "Standard_D2_v3"
    }
  }
}

Kubespray (inventory file):

all:
  hosts:
    node1:
      ansible_host: 192.168.1.10
      ip: 192.168.1.10
      access_ip: 192.168.1.10
    node2:
      ansible_host: 192.168.1.11
      ip: 192.168.1.11
      access_ip: 192.168.1.11

Both tools aim to simplify Kubernetes cluster deployment, but they cater to different use cases. aks-engine is tailored for Azure, offering seamless integration with Azure services, while Kubespray provides a more flexible, platform-agnostic approach suitable for various environments.

openshift logo

openshift-ansible

2,177

Install and config an OpenShift 3.x cluster

Pros of openshift-ansible

  • Tailored specifically for OpenShift, providing a more integrated and optimized deployment experience
  • Includes additional features and components specific to OpenShift, such as built-in CI/CD pipelines and developer tools
  • Offers more extensive enterprise-grade security features and compliance options

Cons of openshift-ansible

  • Less flexible for customizing the underlying Kubernetes infrastructure compared to Kubespray
  • Steeper learning curve due to OpenShift-specific concepts and components
  • Generally requires more resources and has higher system requirements

Code Comparison

openshift-ansible:

- name: Install OpenShift
  hosts: masters
  tasks:
    - name: Run OpenShift installer
      command: openshift-install create cluster --dir=/path/to/install

Kubespray:

- name: Install Kubernetes
  hosts: kube-master
  tasks:
    - name: Deploy Kubernetes master components
      include_role:
        name: kubernetes/master

The code snippets demonstrate the different approaches:

  • openshift-ansible uses OpenShift-specific installer commands
  • Kubespray utilizes more generic Ansible roles for Kubernetes deployment

Both projects use Ansible for automation, but their focus and implementation details differ based on their target platforms (OpenShift vs. vanilla Kubernetes).

Convert Figma logo designs to code with AI

Visual Copilot

Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.

Try Visual Copilot

README

Deploy a Production Ready Kubernetes Cluster

Kubernetes Logo

If you have questions, check the documentation at kubespray.io and join us on the kubernetes slack, channel #kubespray. You can get your invite here

  • Can be deployed on AWS, GCE, Azure, OpenStack, vSphere, Equinix Metal (bare metal), Oracle Cloud Infrastructure (Experimental), or Baremetal
  • Highly available cluster
  • Composable (Choice of the network plugin for instance)
  • Supports most popular Linux distributions
  • Continuous integration tests

Quick Start

Below are several ways to use Kubespray to deploy a Kubernetes cluster.

Ansible

Usage

Install Ansible according to Ansible installation guide then run the following steps:

# Copy ``inventory/sample`` as ``inventory/mycluster``
cp -rfp inventory/sample inventory/mycluster

# Update Ansible inventory file with inventory builder
declare -a IPS=(10.10.1.3 10.10.1.4 10.10.1.5)
CONFIG_FILE=inventory/mycluster/hosts.yaml python3 contrib/inventory_builder/inventory.py ${IPS[@]}

# Review and change parameters under ``inventory/mycluster/group_vars``
cat inventory/mycluster/group_vars/all/all.yml
cat inventory/mycluster/group_vars/k8s_cluster/k8s-cluster.yml

# Clean up old Kubernetes cluster with Ansible Playbook - run the playbook as root
# The option `--become` is required, as for example cleaning up SSL keys in /etc/,
# uninstalling old packages and interacting with various systemd daemons.
# Without --become the playbook will fail to run!
# And be mind it will remove the current kubernetes cluster (if it's running)!
ansible-playbook -i inventory/mycluster/hosts.yaml  --become --become-user=root reset.yml

# Deploy Kubespray with Ansible Playbook - run the playbook as root
# The option `--become` is required, as for example writing SSL keys in /etc/,
# installing packages and interacting with various systemd daemons.
# Without --become the playbook will fail to run!
ansible-playbook -i inventory/mycluster/hosts.yaml  --become --become-user=root cluster.yml

Note: When Ansible is already installed via system packages on the control node, Python packages installed via sudo pip install -r requirements.txt will go to a different directory tree (e.g. /usr/local/lib/python2.7/dist-packages on Ubuntu) from Ansible's (e.g. /usr/lib/python2.7/dist-packages/ansible still on Ubuntu). As a consequence, the ansible-playbook command will fail with:

ERROR! no action detected in task. This often indicates a misspelled module name, or incorrect module path.

This likely indicates that a task depends on a module present in requirements.txt.

One way of addressing this is to uninstall the system Ansible package then reinstall Ansible via pip, but this not always possible and one must take care regarding package versions. A workaround consists of setting the ANSIBLE_LIBRARY and ANSIBLE_MODULE_UTILS environment variables respectively to the ansible/modules and ansible/module_utils subdirectories of the pip installation location, which is the Location shown by running pip show [package] before executing ansible-playbook.

A simple way to ensure you get all the correct version of Ansible is to use the pre-built docker image from Quay. You will then need to use bind mounts to access the inventory and SSH key in the container, like this:

git checkout v2.26.0
docker pull quay.io/kubespray/kubespray:v2.26.0
docker run --rm -it --mount type=bind,source="$(pwd)"/inventory/sample,dst=/inventory \
  --mount type=bind,source="${HOME}"/.ssh/id_rsa,dst=/root/.ssh/id_rsa \
  quay.io/kubespray/kubespray:v2.26.0 bash
# Inside the container you may now run the kubespray playbooks:
ansible-playbook -i /inventory/inventory.ini --private-key /root/.ssh/id_rsa cluster.yml

Collection

See here if you wish to use this repository as an Ansible collection

Vagrant

For Vagrant we need to install Python dependencies for provisioning tasks. Check that Python and pip are installed:

python -V && pip -V

If this returns the version of the software, you're good to go. If not, download and install Python from here https://www.python.org/downloads/source/

Install Ansible according to Ansible installation guide then run the following step:

vagrant up

Documents

Supported Linux Distributions

Note: Upstart/SysV init based OS types are not supported.

Supported Components

Container Runtime Notes

  • The cri-o version should be aligned with the respective kubernetes version (i.e. kube_version=1.20.x, crio_version=1.20)

Requirements

  • Minimum required version of Kubernetes is v1.29
  • Ansible v2.14+, Jinja 2.11+ and python-netaddr is installed on the machine that will run Ansible commands
  • The target servers must have access to the Internet in order to pull docker images. Otherwise, additional configuration is required (See Offline Environment)
  • The target servers are configured to allow IPv4 forwarding.
  • If using IPv6 for pods and services, the target servers are configured to allow IPv6 forwarding.
  • The firewalls are not managed, you'll need to implement your own rules the way you used to. in order to avoid any issue during deployment you should disable your firewall.
  • If kubespray is run from non-root user account, correct privilege escalation method should be configured in the target servers. Then the ansible_become flag or command parameters --become or -b should be specified.

Hardware: These limits are safeguarded by Kubespray. Actual requirements for your workload can differ. For a sizing guide go to the Building Large Clusters guide.

  • Master
    • Memory: 1500 MB
  • Node
    • Memory: 1024 MB

Network Plugins

You can choose among ten network plugins. (default: calico, except Vagrant uses flannel)

  • flannel: gre/vxlan (layer 2) networking.

  • Calico is a networking and network policy provider. Calico supports a flexible set of networking options designed to give you the most efficient networking across a range of situations, including non-overlay and overlay networks, with or without BGP. Calico uses the same engine to enforce network policy for hosts, pods, and (if using Istio and Envoy) applications at the service mesh layer.

  • cilium: layer 3/4 networking (as well as layer 7 to protect and secure application protocols), supports dynamic insertion of BPF bytecode into the Linux kernel to implement security services, networking and visibility logic.

  • weave: Weave is a lightweight container overlay network that doesn't require an external K/V database cluster. (Please refer to weave troubleshooting documentation).

  • kube-ovn: Kube-OVN integrates the OVN-based Network Virtualization with Kubernetes. It offers an advanced Container Network Fabric for Enterprises.

  • kube-router: Kube-router is a L3 CNI for Kubernetes networking aiming to provide operational simplicity and high performance: it uses IPVS to provide Kube Services Proxy (if setup to replace kube-proxy), iptables for network policies, and BGP for ods L3 networking (with optionally BGP peering with out-of-cluster BGP peers). It can also optionally advertise routes to Kubernetes cluster Pods CIDRs, ClusterIPs, ExternalIPs and LoadBalancerIPs.

  • macvlan: Macvlan is a Linux network driver. Pods have their own unique Mac and Ip address, connected directly the physical (layer 2) network.

  • multus: Multus is a meta CNI plugin that provides multiple network interface support to pods. For each interface Multus delegates CNI calls to secondary CNI plugins such as Calico, macvlan, etc.

  • custom_cni : You can specify some manifests that will be applied to the clusters to bring you own CNI and use non-supported ones by Kubespray. See tests/files/custom_cni/README.md and tests/files/custom_cni/values.yamlfor an example with a CNI provided by a Helm Chart.

The network plugin to use is defined by the variable kube_network_plugin. There is also an option to leverage built-in cloud provider networking instead. See also Network checker.

Ingress Plugins

  • nginx: the NGINX Ingress Controller.

  • metallb: the MetalLB bare-metal service LoadBalancer provider.

Community docs and resources

Tools and projects on top of Kubespray

CI Tests

Build graphs

CI/end-to-end tests sponsored by: CNCF, Equinix Metal, OVHcloud, ELASTX.

See the test matrix for details.