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  1. Stackups
  2. Application & Data
  3. Infrastructure as a Service
  4. Virtualization Platform
  5. Kubernetes vs VMware vSphere

Kubernetes vs VMware vSphere

OverviewDecisionsComparisonAlternatives

Overview

VMware vSphere
VMware vSphere
Stacks608
Followers550
Votes30
Kubernetes
Kubernetes
Stacks61.2K
Followers52.8K
Votes685

Kubernetes vs VMware vSphere: What are the differences?

Kubernetes and VMware vSphere are both popular platforms used for managing and orchestrating containerized applications and virtualized infrastructure, respectively. Let's explore the key differences between them.

  1. Architecture: Kubernetes is a container orchestration platform that allows for the deployment, scaling, and management of containerized applications across a cluster of machines. It follows a master-worker architecture, where a cluster consists of a master node that manages the cluster state and multiple worker nodes that run the application workloads. On the other hand, VMware vSphere is a virtualization platform that enables the creation and management of virtual machines (VMs) on physical servers. It utilizes a hypervisor-based architecture, where a host hypervisor runs on the hardware and manages the virtualization of resources.

  2. Focus: Kubernetes primarily focuses on the management of containerized applications, providing features such as service discovery, load balancing, and automatic scaling. It is widely used in cloud-native environments and supports multiple cloud providers as well as on-premises deployments. On the contrary, VMware vSphere is designed for virtualization of infrastructure and offers a wide range of features for managing VMs such as resource allocation, high availability, and live migration. It is commonly used in traditional enterprise environments and data centers.

  3. Portability: Kubernetes promotes an application-centric approach and favors portable, cloud-agnostic deployments. Applications can be deployed and run consistently across different Kubernetes clusters, regardless of the underlying infrastructure or cloud provider. This portability allows for easier migration and avoids vendor lock-in. In contrast, VMware vSphere is tightly integrated with VMware's ecosystem and is primarily designed for on-premises deployments. While it can be used with some public cloud providers, the level of integration and portability may vary.

  4. Containerization: Kubernetes is specifically built to manage containerized applications using container runtimes like Docker. It provides features for running and managing containers, including networking, storage, and lifecycle management. VMware vSphere, on the other hand, supports the virtualization of entire operating systems using hypervisors. It allows for the creation and management of VMs that can run various operating systems and applications, not limited to containers.

  5. Scalability: Kubernetes is known for its ability to scale applications and handle large-scale deployments. It supports horizontal scaling, where additional instances of an application can be added or removed dynamically based on demand. Kubernetes also integrates with monitoring and auto-scaling tools to automatically adjust resources. In contrast, VMware vSphere provides vertical scaling, allowing a single VM to scale up or down in terms of resources like CPU and memory. It is more suitable for scaling individual VMs rather than the entire application.

  6. Community and Ecosystem: Kubernetes has a vibrant and growing community with a rich ecosystem of tools and extensions. It is an open-source project supported by the Cloud Native Computing Foundation (CNCF). This community-driven development ensures continuous improvement, innovation, and collaboration. VMware vSphere, being a proprietary software, is backed by VMware and has its own ecosystem and community. However, the level of community participation and diversity of tools may not be as extensive as Kubernetes.

In summary, Kubernetes and VMware vSphere have different architectural focuses, with Kubernetes primarily targeting containerized applications and VMware vSphere focusing on virtualization of infrastructure. Kubernetes promotes portability and is designed for cloud-native environments, while VMware vSphere is geared towards on-premises deployments. Kubernetes is well-suited for large-scale deployments and offers a broader community and ecosystem support compared to VMware vSphere.

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Advice on VMware vSphere, Kubernetes

Simon
Simon

Senior Fullstack Developer at QUANTUSflow Software GmbH

Apr 27, 2020

DecidedonGitHubGitHubGitHub PagesGitHub PagesMarkdownMarkdown

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.
12.8M views12.8M
Comments
Anis
Anis

Founder at Odix

Nov 7, 2020

Review

I recommend this : -Spring reactive for back end : the fact it's reactive (async) it consumes half of the resources that a sync platform needs (so less CPU -> less money). -Angular : Web Front end ; it's gives you the possibility to use PWA which is a cheap replacement for a mobile app (but more less popular). -Docker images. -Kubernetes to orchestrate all the containers. -I Use Jenkins / blueocean, ansible for my CI/CD (with Github of course) -AWS of course : u can run a K8S cluster there, make it multi AZ (availability zones) to be highly available, use a load balancer and an auto scaler and ur good to go. -You can store data by taking any managed DB or u can deploy ur own (cheap but risky).

You pay less money, but u need some technical 2 - 3 guys to make that done.

Good luck

115k views115k
Comments

Detailed Comparison

VMware vSphere
VMware vSphere
Kubernetes
Kubernetes

vSphere is the world’s leading server virtualization platform. Run fewer servers and reduce capital and operating costs using VMware vSphere to build a cloud computing infrastructure.

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.

Powerful Server Virtualization;Network Services;Efficient Storage;Consistent Automation;High Availability;Robust Security
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
Statistics
Stacks
608
Stacks
61.2K
Followers
550
Followers
52.8K
Votes
30
Votes
685
Pros & Cons
Pros
  • 8
    Strong host isolation
  • 6
    Industry leader
  • 5
    Great VM management (HA,FT,...)
  • 4
    Easy to use
  • 2
    Feature rich
Cons
  • 9
    Price
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
Integrations
No integrations available
Vagrant
Vagrant
Docker
Docker
Rackspace Cloud Servers
Rackspace Cloud Servers
Microsoft Azure
Microsoft Azure
Google Compute Engine
Google Compute Engine
Ansible
Ansible
Google Kubernetes Engine
Google Kubernetes Engine

What are some alternatives to VMware vSphere, Kubernetes?

VirtualBox

VirtualBox

VirtualBox is a powerful x86 and AMD64/Intel64 virtualization product for enterprise as well as home use. Not only is VirtualBox an extremely feature rich, high performance product for enterprise customers, it is also the only professional solution that is freely available as Open Source Software under the terms of the GNU General Public License (GPL) version 2.

Rancher

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

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

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

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

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.

Codefresh

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.

Proxmox VE

Proxmox VE

It is a complete open-source platform for all-inclusive enterprise virtualization that tightly integrates KVM hypervisor and LXC containers, software-defined storage and networking functionality on a single platform, and easily manages high availability clusters and disaster recovery tools with the built-in web management interface.

CAST.AI

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.

k3s

k3s

Certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. Supports something as small as a Raspberry Pi or as large as an AWS a1.4xlarge 32GiB server.

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