Kubernetes vs OpenNebula

Overview

Kubernetes

Stacks61.2K

Followers52.8K

Votes685

OpenNebula

Stacks33

Followers120

Votes0

GitHub Stars1.6K

Forks514

Kubernetes vs OpenNebula: What are the differences?

Introduction

Kubernetes and OpenNebula are both popular open-source container orchestration platforms that provide tools for managing and deploying applications. However, there are several key differences between the two.

Architecture: Kubernetes follows a container-centric approach, where applications are deployed in containers, grouped into pods, and managed by a cluster of nodes. On the other hand, OpenNebula takes a virtual machine-centric approach, where applications are deployed within virtual machines that are managed by a cluster of hypervisors. This fundamental difference in architecture leads to variations in the way these platforms handle resource allocation, scalability, and workload management.
Focus: Kubernetes primarily aims at managing containers and microservices-based applications, providing features like auto-scaling, load balancing, and service discovery, making it more suitable for cloud-native and distributed environments. OpenNebula, on the other hand, focuses on managing virtual machines and provides features such as multi-tenancy, virtual network management, and hybrid cloud integration, making it well-suited for diverse workloads and hybrid cloud deployments.
Community and Ecosystem: Kubernetes has a larger and more active community compared to OpenNebula, resulting in a broader range of supported features, extensive documentation, and a vast ecosystem of tools and integrations. This active community and ecosystem provide better support, faster bug fixes, and more frequent updates, making Kubernetes a preferred choice for many organizations.
Ease of Use: Kubernetes has a steeper learning curve due to its complex architecture and extensive set of features. It requires a good understanding of networking, containerization, and distributed systems concepts. OpenNebula, on the other hand, follows a simpler and more intuitive approach, making it easier to learn and use, especially for users who are familiar with traditional virtualization technologies.
Scalability and Resource Management: Kubernetes offers powerful auto-scaling features and fine-grained resource management capabilities, allowing efficient utilization of compute resources and dynamic scaling based on application needs. OpenNebula provides similar capabilities but focuses more on optimizing virtual machine resource allocation and scheduling, making it suitable for scenarios that require precise control over resource allocation and management.
Deployment Flexibility: Kubernetes is designed to be cloud-agnostic and can be deployed on a variety of cloud providers or on-premises infrastructure. It also supports more advanced deployment options like multi-cluster and multi-region setups. OpenNebula, on the other hand, provides a unified management interface for hybrid cloud deployments, allowing users to seamlessly manage resources across public and private clouds, making it a good choice for organizations with diverse infrastructure requirements.

In summary, Kubernetes and OpenNebula differ in their underlying architecture, focus, community support, ease of use, scalability and resource management capabilities, and deployment flexibility. Understanding these differences is crucial for choosing the right platform that aligns with specific application requirements and infrastructure goals.

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Advice on Kubernetes, OpenNebula

Simon

Senior Fullstack Developer at QUANTUSflow Software GmbH

Apr 27, 2020

Decidedon

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Markdown

Our whole DevOps stack consists of the following tools:

@{GitHub}|tool:27| (incl. @{GitHub Pages}|tool:683|/@{Markdown}|tool:1147| for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
Respectively @{Git}|tool:1046| as revision control system
@{SourceTree}|tool:1599| as @{Git}|tool:1046| GUI
@{Visual Studio Code}|tool:4202| as IDE
@{CircleCI}|tool:190| for continuous integration (automatize development process)
@{Prettier}|tool:7035| / @{TSLint}|tool:5561| / @{ESLint}|tool:3337| as code linter
@{SonarQube}|tool:2638| as quality gate
@{Docker}|tool:586| as container management (incl. @{Docker Compose}|tool:3136| for multi-container application management)
@{VirtualBox}|tool:774| for operating system simulation tests
@{Kubernetes}|tool:1885| as cluster management for docker containers
@{Heroku}|tool:133| for deploying in test environments
@{nginx}|tool:1052| as web server (preferably used as facade server in production environment)
@{SSLMate}|tool:2752| (using @{OpenSSL}|tool:3091|) for certificate management
@{Amazon EC2}|tool:18| (incl. @{Amazon S3}|tool:25|) for deploying in stage (production-like) and production environments
@{PostgreSQL}|tool:1028| as preferred database system
@{Redis}|tool:1031| as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
Scalability: All-in-one framework for distributed systems.
Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.

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Detailed Comparison

Kubernetes	OpenNebula
Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.	It provides a simple but feature-rich and flexible solution for the comprehensive management of virtualized data centers to enable on-premise enterprise clouds in existing infrastructures. It can be primarily used as a virtualization tool to manage your virtual infrastructure in the data-center or cluster, which is usually referred as Private Cloud. It supports Hybrid Cloud to combine local infrastructure with public cloud-based infrastructure, enabling highly scalable hosting environments.
Lightweight, simple and accessible;Built for a multi-cloud world, public, private or hybrid;Highly modular, designed so that all of its components are easily swappable	Flexible;Robust;Powerful Auto-Scaling; Service Deployment
Statistics
GitHub Stars -	GitHub Stars 1.6K
GitHub Forks -	GitHub Forks 514
Stacks 61.2K	Stacks 33
Followers 52.8K	Followers 120
Votes 685	Votes 0
Pros & Cons
Pros 166 Leading docker container management solution 130 Simple and powerful 108 Open source 76 Backed by google 58 The right abstractions Cons 16 Steep learning curve 15 Poor workflow for development 8 Orchestrates only infrastructure 4 High resource requirements for on-prem clusters 2 Too heavy for simple systems	No community feedback yet
Integrations
Vagrant Docker Rackspace Cloud Servers Microsoft Azure Google Compute Engine Ansible Google Kubernetes Engine	Java Ruby CloudFlare Zoho Dropbox

What are some alternatives to Kubernetes, OpenNebula?

Rancher

Rancher is an open source container management platform that includes full distributions of Kubernetes, Apache Mesos and Docker Swarm, and makes it simple to operate container clusters on any cloud or infrastructure platform.

Docker Compose

With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.

Docker Swarm

Swarm serves the standard Docker API, so any tool which already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts: Dokku, Compose, Krane, Deis, DockerUI, Shipyard, Drone, Jenkins... and, of course, the Docker client itself.

Tutum

Tutum lets developers easily manage and run lightweight, portable, self-sufficient containers from any application. AWS-like control, Heroku-like ease. The same container that a developer builds and tests on a laptop can run at scale in Tutum.

Portainer

It is a universal container management tool. It works with Kubernetes, Docker, Docker Swarm and Azure ACI. It allows you to manage containers without needing to know platform-specific code.

OpenStack

OpenStack is a cloud operating system that controls large pools of compute, storage, and networking resources throughout a datacenter, all managed through a dashboard that gives administrators control while empowering their users to provision resources through a web interface.

Apache CloudStack

CloudStack is open source software designed to deploy and manage large networks of virtual machines, as a highly available, highly scalable Infrastructure as a Service (IaaS) cloud computing platform.

Codefresh

Automate and parallelize testing. Codefresh allows teams to spin up on-demand compositions to run unit and integration tests as part of the continuous integration process. Jenkins integration allows more complex pipelines.

Scalr

Scalr is a remote state & operations backend for Terraform with access controls, policy as code, and many quality of life features.

CAST.AI

It is an AI-driven cloud optimization platform for Kubernetes. Instantly cut your cloud bill, prevent downtime, and 10X the power of DevOps.

Related Comparisons

Kubernetes vs OpenNebula: What are the differences?

Introduction

Architecture: Kubernetes follows a container-centric approach, where applications are deployed in containers, grouped into pods, and managed by a cluster of nodes. On the other hand, OpenNebula takes a virtual machine-centric approach, where applications are deployed within virtual machines that are managed by a cluster of hypervisors. This fundamental difference in architecture leads to variations in the way these platforms handle resource allocation, scalability, and workload management.
Focus: Kubernetes primarily aims at managing containers and microservices-based applications, providing features like auto-scaling, load balancing, and service discovery, making it more suitable for cloud-native and distributed environments. OpenNebula, on the other hand, focuses on managing virtual machines and provides features such as multi-tenancy, virtual network management, and hybrid cloud integration, making it well-suited for diverse workloads and hybrid cloud deployments.
Community and Ecosystem: Kubernetes has a larger and more active community compared to OpenNebula, resulting in a broader range of supported features, extensive documentation, and a vast ecosystem of tools and integrations. This active community and ecosystem provide better support, faster bug fixes, and more frequent updates, making Kubernetes a preferred choice for many organizations.
Ease of Use: Kubernetes has a steeper learning curve due to its complex architecture and extensive set of features. It requires a good understanding of networking, containerization, and distributed systems concepts. OpenNebula, on the other hand, follows a simpler and more intuitive approach, making it easier to learn and use, especially for users who are familiar with traditional virtualization technologies.
Scalability and Resource Management: Kubernetes offers powerful auto-scaling features and fine-grained resource management capabilities, allowing efficient utilization of compute resources and dynamic scaling based on application needs. OpenNebula provides similar capabilities but focuses more on optimizing virtual machine resource allocation and scheduling, making it suitable for scenarios that require precise control over resource allocation and management.
Deployment Flexibility: Kubernetes is designed to be cloud-agnostic and can be deployed on a variety of cloud providers or on-premises infrastructure. It also supports more advanced deployment options like multi-cluster and multi-region setups. OpenNebula, on the other hand, provides a unified management interface for hybrid cloud deployments, allowing users to seamlessly manage resources across public and private clouds, making it a good choice for organizations with diverse infrastructure requirements.

Kubernetes vs OpenNebula

Overview

Kubernetes vs OpenNebula: What are the differences?