According to a report by The Cloud Native Computing Foundation (CNCF), Kubernetes remains the most widely adopted container orchestration tool, holding approximately 92% of the market share. When setting up a deployment, you have to choose between bare metal and VM (virtual machine)-based Kubernetes. However, the former has several advantages over his VM, making it a popular choice for many.
This article provides a comprehensive guide to bare metal Kubernetes deployments. This description includes how it works, its benefits, associated challenges, and a step-by-step implementation process. Let’s start with some basics.
Bare metal Kubernetes involves running clusters and containers directly on physical servers, bypassing virtual machines. In a traditional Kubernetes deployment, virtual machines act as intermediaries between the hardware and containers. However, on bare metal, Kubernetes runs directly on the server hardware. Containers have direct access to the underlying hardware, which is not the case with VM-based clusters.
Bare-metal Kubernetes allows applications to interact directly with physical hardware without abstracting hypervisor or virtualization layers. This direct access to computing resources can improve system performance and reduce network latency by up to 3x compared to VM-based setups. This is a common choice for performance-critical or latency-sensitive applications.
Major features
- Direct access to hardware: In bare metal deployments, containers have direct access to the underlying server hardware.
- No hypervisor layer: Unlike VM-based Kubernetes, which relies on a hypervisor to manage VMs, bare metal setups skip this middle layer.
Use Case
Common uses include:
- Performance-critical applications: Bare metal configurations are suitable for applications where performance is paramount, such as high-frequency trading systems, real-time analytics, and scientific computing.
- Latency-sensitive workloads: Applications that require very low network latency, such as online gaming or telecommunications services, can benefit from reduced latency in a bare metal setup.
- Resource-intensive workloads: Bare metal can be advantageous for resource-intensive applications that require direct access to physical hardware, such as GPU-accelerated workloads.
Optimized performance
Bare metal deployments are better at optimizing system performance and reducing network latency. This is achieved by providing direct access to hardware devices and allowing containerized applications to interact with the underlying physical servers without going through a hypervisor or virtualization layer. The absence of this abstraction layer significantly improves performance.
Reduced waiting time
Bare metal Kubernetes can also reduce network latency by up to 3x. This makes it an ideal choice for workloads with demanding performance requirements, such as big data processing, live video streaming, machine learning analytics, and the deployment of 5G stacks in communications where low latency is paramount. In these scenarios, bare metal allows applications to take full advantage of the hardware’s capabilities and deliver fast, responsive results.
Reduce migration costs
Bare metal servers are ideal for core business processes and offer significant cost savings. Organizations with established on-premises applications find it more affordable to run Kubernetes on their existing bare metal infrastructure than to move to the cloud. Additionally, this deployment eliminates hypervisor overhead and allows resources to be dedicated to his Kubernetes cluster, potentially reducing total cost of ownership.
enhanced control
Bare metal gives organizations extensive control over their infrastructure. This control allows administrators to customize hardware configurations to precisely match performance and reliability requirements.
Effective load balancing
Ensuring consistent access to applications is important, and load balancing is essential to achieving this goal. In bare metal environments, load balancers such as MetalLB and kube-vip play an important role. They facilitate effective distribution of network traffic and ensure that applications remain accessible and responsive.
assignment
Some of the challenges you can face when deploying bare metal Kubernetes include:
Setup and configuration
Setting up a bare metal server can be more complex than deploying a virtual machine. Instead of using VM images, you must configure each bare metal machine individually. Tools such as Canonical MAAS and Tinkerbell Cluster API Provider can help, but they can still be more complex than a VM-based cluster setup.
Backup and migration
Without virtualization, creating backups of bare metal servers or migrating bare metal servers to different hardware can be more difficult. You cannot rely on VM snapshots or image-based backups for this purpose.
node failure
A bare metal configuration treats each server as a standalone node. If one server fails (such as an operating system kernel panic), all containers on that node can be affected. In contrast, virtual machines allow for better isolation, and failure of one VM does not necessarily affect other VMs.
Operational complexity
Running Kubernetes on bare metal adds operational complexity. Without a hypervisor layer, tasks typically handled by a hypervisor must be managed manually. This requires a steep learning curve and a significant investment of time and resources. Interestingly, his VM-based Kubernetes setup can introduce complications, especially when managing dual orchestration layers of VMs and Kubernetes pods.
Implementing best practices
Bare metal provides a clean slate and takes responsibility for implementing best practices for security, performance, and reliability. This requires a deep understanding of both Kubernetes and the specific hardware, which adds complexity.
Prerequisites
Before proceeding with the steps below, you must have the following ready:
- Two or more Linux servers running Ubuntu 18.04.
- Access a user account with sudo or root privileges on each server.
- A proper package manager.
- Terminal window or command line access. We recommend using Kubectl, a command-line tool designed explicitly for Kubernetes.
Once you have the above, follow these steps:
Step 1: Installation
First, install Docker and related packages on all Kubernetes nodes. Use the following command:
sudo apt-get install docker.io
Enable Docker to start at boot time.
sudo systemctl enable docker
Add a Kubernetes software repository
sudo apt-get update \
&& sudo apt-get install -y apt-transport-https \
&& curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add
If curl is not installed, add it using the following command:
sudo apt-get install curl
Run package updates
echo "deb http://apt.kubernetes.io/ kubernetes-xenial main" \
| sudo tee -a /etc/apt/sources.list.d/kubernetes.list \
&& sudo apt-get update
Perform all of the above steps on each server node.
Step 2: Kubernetes installation tools:
Install kubelet, kubeadm, and Kubernetes-cni using the following commands:
sudo apt-get update \
&& sudo apt-get install -yq \
kubelet \
kubeadm \
kubernetes-cni
Step 3: Deployment
Disable swap memory on each server
Assign a unique hostname to each server node.
Use the following commands for each:
sudo hostnamectl set-hostname master-node
Worker nodes (each with a different name):
sudo hostnamectl set-hostname worker01
Step 4: Create a directory for your cluster.
Run the following command on the master node:
sudo kubeadm init --pod-network-cidr=10.244.0.0/16
After running the above command, be sure to note the kubeadm join message provided.
Step 5: Join worker nodes in the cluster
Connect each worker node to the cluster using the kubeadm join message obtained in the previous step.
Switch to each worker node, enter the kubeadm join command, and repeat for all worker nodes.
To check the status of the node, return to the master server and run the following command:
Step 6: Connect related components to each other via a pod network.
Deploy a pod network to enable communication between nodes. Run the following command, choosing from the available options:
kubectl apply -f [podnetwork].yaml
best practice
Here are some of the best practices you should follow for effective deployment.
- Choose your machine wisely. Not all bare metal nodes are equal. Consider your hardware specifications and server location. Servers in the public cloud can lack control and long-term cost advantages compared to self-owned servers. Tailor your server selection to your workload type and use case.
- Update and upgrade your hardware regularly. It’s important to keep your hardware up to date. Regular upgrades allow you to take advantage of technological advances and ensure security and performance are maintained.
- Don’t overestimate performance. Bare metal improves performance, but gains can be limited. VMs can provide near-bare metal efficiency for many workloads. Set realistic expectations to avoid disappointment.
- Employ monitoring solutions and automated alerts. Employ monitoring solutions and automated alerts to track cluster performance and get proactive notifications of potential issues. This approach helps maintain cluster performance and reliability.
- Automate node provisioning. Automation is especially important when provisioning bare metal nodes. Tools like MAAS and Tinkerbell can automate this process using the Kubernetes Cluster API. Manual configuration is not scalable.
- Avoid OS sprawl. Maintaining a consistent operating system and configuration is even more difficult with bare metal nodes. Special effort is required to ensure software consistency across the infrastructure.
- Consider using VMs and bare metal at the same time. You don’t have to choose exclusively between VMs and bare metal. Most Kubernetes distributions support both. Consider using a combination of VMs and bare metal nodes in different clusters or within the same cluster if it suits your workload requirements.
conclusion
Bare metal Kubernetes has grown in popularity in recent years, and for good reason. Enterprises choose VMs over VMs due to benefits such as increased control, enhanced data security and access controls, reduced migration costs, and optimized performance and latency.
However, deploying Kubernetes on bare metal servers comes with some challenges, such as operational and configuration complexities and node failures, that you need to understand before getting started. To overcome these challenges, it’s important to follow the best practices described in the previous sections of this article.
If you’re ready to set up a deployment, consider looking into a dedicated server hosting package. In addition to giving you the flexibility to choose your preferred hardware, we also offer the option to choose a server region such as the US or EU.
FAQ
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