Hire KVM (for Kernel-based Virtual Machine) Developer

KVM (for Kernel-based Virtual Machine)

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KVM (for Kernel-based Virtual Machine)
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Ciklum
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Hire KVM (for Kernel-based Virtual Machine) Developers and Engineers

Bohdan R., KVM (for Kernel-based Virtual Machine) Developer

- Have good hands-on experience in implementing core DevOps concepts such as virtualization, version control, cloud computing, load balancing, etc. by using a wide variety of technologies. - I am a team player, communicable, hardworking, and open-minded person. I like getting new skills and knowledge. - Upper-Intermediate English. - Available ASAP.

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)

AWS (Amazon Web Services)

AWS (Amazon Web Services)

Aliaksandr Z., KVM (for Kernel-based Virtual Machine) Developer

- Experienced System Software Engineer with 12+ years of experience designing and implementing firmware-level and system-level security solutions, sophisticated OS-kernel extensions and device drivers, hi-loaded systems development, and data processing. - Solid foundation in building secure, real-time operating systems and extending Linux kernel capabilities, with strong proficiency in both C and C++. - Instrumental in architecting and implementing UEFI hypervisors and firmware for Class B medical devices, emphasizing security features like CryptoCell for secure communications. - Proven capabilities in vulnerability analysis, leveraging tools like Angr and AFL for automated firmware testing. - Played a key role in SDLC, driving modern software architecture practices and security foundations in projects across medical and information security industries. - Upper-Intermediate English

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)   5 yr.

C/C++/C#

C/C++/C#   10 yr.

Linux

Linux   5 yr.

Viktoria P., KVM (for Kernel-based Virtual Machine) Developer

- Highly motivated manual QA tester with over 1,5 year of experience with safety-critical systems. - Quality Assurance: Functional & Non-functional testing, SDLC, GitFlow, Mobile testing, Test design - Upper-intermediate English. - Native Bulgarian - Available ASAP.

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)

QA

QA

Oleksandr, KVM (for Kernel-based Virtual Machine) Developer

DevOps Engineer with over 3 years of experience in support, adept at installing, configuring, and maintaining development environments across AWS, GCP, and other cloud services. With an educational background in Automation and Computer Technologies, the candidate has a solid grounding in UNIX systems and possesses programming skills in Python, Ruby, and other languages. Demonstrates strong expertise in Docker, Kubernetes, CI/CD pipelines through Jenkins, CircleCI, and more. Played a key role in a 2+ year project involving system containerization, role management integration, and DevOps practices in a team setting. Technically proficient in cloud structures, with a concrete understanding of the software development lifecycle and the implementation of modular application architectures.

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)

GCP AI

GCP AI

Linux

Linux

Docker

Docker

AWS Security Groups

AWS Security Groups

Andrey B, KVM (for Kernel-based Virtual Machine) Developer

$35/hr, $5600/month

Senior System Administrator with over 9+ years exp. Has experience with DevOps for over 7 years. Also has experience with Kubernetes, Grafana, Terraform. Experience in working with highly loaded projects, not afraid of complex tasks. Knowledge of Python programming languages for over 4 years.

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)

Nagios

Nagios

Zabbix

Zabbix

Prometheus

Prometheus

Grafana

Grafana

Elastic Search Platform

Elastic Search Platform

Rolan A., KVM (for Kernel-based Virtual Machine) Developer

$50/hr

- More than 10 years’ experience of software development - Data science skills. Computer Vision, multiple view geometry, camera calibration, LIDAR, object detection, semantic segmentation, instance segmentation, time series, dynamic programming - Software Engineering skills. Experience of IoT (Internet of Things) and Embedded development - Solution-oriented scientist focused on R&D and product delivery with 9 years of experience on the outsource domain - Accustomed to self-education and independent problem solution - My inspiration is exiting by challengeable and reasonable engineering tasks. Pitching skills from years of conferences attendance and strong understanding of business needs are my strengths - Intermediate English. - Availability starting from ASAP

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)

Python

Python

Yaroslav M., KVM (for Kernel-based Virtual Machine) Developer

- Highly motivated Systems Engineer and DevOps with 13+ years of experience in Linux and FreeBSD systems administration, scripting, automation, and configuration management; - Experienced in troubleshooting and root-cause analysis of complex infrastructure issues; - Proficient in cloud platforms such as AWS, Azure, and GCP, as well as CI/CD tools like GitLab CI and Jenkins; - Skilled in containerization with Docker and Kubernetes, and monitoring tools like Grafana and Prometheus; - Strong background in database management with MariaDB, MySQL, PostgreSQL, and more; - Proficient in programming languages such as Groovy, Bash, and PowerShell; - Experienced in virtualization technologies like VMware ESXi and Proxmox, as well as hardware infrastructure planning and maintenance.

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)

AWS (Amazon Web Services)

AWS (Amazon Web Services)

Mykhaylo R., KVM (for Kernel-based Virtual Machine) Developer

- Over 20 years in IT with a master's degree in Cybernetics - Proficient in Ansible: Extensive experience in deploying and managing Ansible-driven infrastructure, particularly highlighted in roles as SRE/Architect (Aug 2018 – Present) and Senior DevOps Engineer/Lead Sysadmin (Aug 2020 – May 2021), where Ansible was pivotal in scaling a learning platform from 1,000 to over 100,000 students and in key migration projects. - Expertise in Windows Environments: Demonstrated strong skills in managing Windows environments, especially as an SRE/Architect (Aug 2018 – Present) and CTO (2013 – Mar 2022), involving Windows AD+MSSQL backoffice management and ITIL Service Management framework implementation on Windows platforms. - Versatile IT Roles with Ansible and Windows: Across various roles including IT Service Manager, Senior DevOps Engineer, and CTO, consistently applied Ansible and Windows technologies in large-scale infrastructure projects and day-to-day operations, showing versatility and depth in these areas. - Managing the growth of the learning platform from 1,000+ to 100k+ active students - ITIL v3 Foundations Certificate - More than 5 years of experience in leading ITIL Service Management capability and implementing end-to-end ITIL Service Management framework - Strong experience in using ServiceNow and Jira Service Desk for ITSM - Experienced IT/Telecom Specialist - UNIX and UNIX-Like OS (FreeBSD, Linux, SunOS, MacOS X) background - Over 20 years of Windows/windows server family. From NT4.0 /win3.1 up to Server2019. As well as upgrading Up to 15 years with server HW, and 13 years with storage solutions - Infrastructure problem-solver with a strong view on reliability, performance, and disaster recovery - Fluent English

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)

Bash

Bash   10 yr.

Shell Scripts

Shell Scripts   10 yr.

MySQL

MySQL   10 yr.

Ansible

Ansible

Ansible Playbook

Ansible Playbook

Viktor I., KVM (for Kernel-based Virtual Machine) Developer

- DevOps with more than 15 years of experience. I can build or establish an existing infrastructure from scratch, organize the CI / CD process, and provide backup and monitoring. In my work I adhere to the principle of expedient use of resources, both technical and human. - I am a team player, communicable, hardworking, and open-minded person. I like getting new skills and knowledge. - Upper-Intermediate English

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)

AWS (Amazon Web Services)

AWS (Amazon Web Services)

Azure (Microsoft Azure)

Azure (Microsoft Azure)

Michael A., KVM (for Kernel-based Virtual Machine) Developer

- IT and Telecom specialist - Specialities: UNIX and UNIX-Like OSes (FreeBSD, Linux, SunOS, MacOS X) - Over 20years of Windows/windows server family. From NT4.0 /win3.1 up to Server2019. As well as upgrading Up to 15 years with server hw, 13 years with storage solutions. - 6 years with Microsoft 365 - Esx server/vsphere 5.0-7.0, hyper-v, freebsd bhyve - Able to translate configs between cisco/extreme/juniper/openbgpd etc. - ITILv3 associate, strong in ITIL/ITSM - Linux/macos (as well as server)/ FreeBSD/HP-UX - Available ASAP - Upper-Intermediate English

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)

SRE

SRE   15 yr.

Oleksandr, KVM (for Kernel-based Virtual Machine) Developer

$40/hr

- 15+ years of professional experience - Infrastructure planning and implementation. - Planning and setting up the environment and performing migration of an application multisite the environment into AWS EC2 cluster with a load balancer - Managing autoscaling and AMI-separating applications with shared network storage. - Upper-intermediate English - Available ASAP

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)

SO, DevOps with KVM (for Kernel-based Virtual Machine), AWS RDS (Amazon Relational Database Service), Redis, AWS SQS, AWS SNS, AWS CloudWatch

SO, KVM (for Kernel-based Virtual Machine) Developer

AWS CLOUD (RDS,REDIS,SQS,SNS,CloudWatch), UNIX_OS (AIX/LINUX), VIRT ( VMware, Linux KVM), Monitoring (NAGIOS/DataDog/AWS_CloudWatch, Zabbix, Prhometheus, Grafana, Kibana), BASH/PYTHON scripting, Kubernetes, data bases (postgres,mysql) Confluence, JIRA, ElasticSearch, AZURE CLOUD, IaC(aws-terraform), SAN (FDC_swiches/IBM_storages). Hardening LINUX

KVM (for Kernel-based Virtual Machine)

KVM (for Kernel-based Virtual Machine)

AWS RDS (Amazon Relational Database Service)

AWS RDS (Amazon Relational Database Service)

Redis

Redis

AWS SQS

AWS SQS

AWS SNS

AWS SNS

AWS CloudWatch

AWS CloudWatch

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Table of Contents

Pros & cons of KVM (for Kernel-based Virtual Machine)

Pros & cons

9 Pros of KVM (for Kernel-based Virtual Machine)

  • KVM is built directly into the Linux kernel, making it highly efficient and providing optimal performance.
  • It offers excellent hardware support, allowing it to run on a wide range of systems and take advantage of hardware virtualization features.
  • KVM supports a variety of guest operating systems, including Linux, Windows, macOS, and more.
  • It provides strong security features, such as isolation between virtual machines and secure virtualized device drivers.
  • KVM supports live migration, allowing virtual machines to be moved to different physical hosts without downtime.
  • It offers good scalability, enabling the simultaneous execution of multiple virtual machines on a single host.
  • KVM integrates well with other Linux technologies, making it easy to manage and monitor virtual machines using existing tools.
  • It has a large and active community of users and developers, ensuring continuous improvement and support.
  • KVM is an open-source solution, which means it is free to use and can be customized to meet specific requirements.

9 Cons of KVM (for Kernel-based Virtual Machine)

  • KVM requires a Linux host, limiting its compatibility with other operating systems.
  • It can be more complex to set up and configure compared to some other virtualization solutions.
  • Since KVM relies on the Linux kernel, any vulnerabilities or issues in the kernel can potentially impact the virtual machines.
  • Managing KVM environments may require advanced Linux skills and knowledge.
  • KVM may not have the same level of performance as bare-metal solutions for certain workloads.
  • It may require additional hardware virtualization support, such as Intel VT or AMD-V, to achieve optimal performance.
  • While KVM supports a wide range of guest operating systems, some proprietary or less common operating systems may have limited support.
  • Scaling KVM environments to a large number of virtual machines may require additional management tools or platforms.
  • As an open-source solution, commercial support options for KVM may be limited compared to proprietary virtualization platforms.

Cases when KVM (for Kernel-based Virtual Machine) does not work

Does not work
  1. Unsupported hardware: KVM relies on hardware virtualization extensions such as Intel VT-x or AMD-V to efficiently run virtual machines. If your CPU does not support these extensions, KVM will not work. Before attempting to use KVM, it is essential to ensure that your hardware supports virtualization.
  2. Inadequate BIOS settings: KVM requires specific BIOS settings to be enabled in order to function properly. If these settings are not enabled or are incorrectly configured, KVM may encounter issues. It is crucial to review your system’s BIOS settings and ensure that virtualization support is enabled.
  3. Incompatible host operating system: KVM is tightly integrated with the Linux kernel and primarily designed to run on Linux-based operating systems. While there are efforts to port KVM to other platforms, its native support and optimal performance are limited to Linux. Attempting to use KVM on a non-Linux host operating system may result in compatibility issues or reduced functionality.
  4. Outdated software: KVM is continuously developed and improved, with new features and bug fixes being introduced regularly. Using outdated versions of KVM, the Linux kernel, or associated tools may lead to compatibility issues or unexpected behavior. It is recommended to keep your software stack up to date to benefit from the latest enhancements and fixes.
  5. Insufficient system resources: Running virtual machines using KVM requires a certain amount of system resources, including CPU, memory, and disk space. If your system does not meet the minimum requirements or if the available resources are already heavily utilized, KVM may not work as expected. It is important to assess your system’s resources and ensure they meet the necessary criteria.

TOP 10 KVM (for Kernel-based Virtual Machine) Related Technologies

Related Technologies
  • Programming Languages

    The most popular programming languages for KVM software development are C, C++, and Python. C is widely used for its low-level capabilities and efficient memory management. C++ offers object-oriented programming features and is suited for complex software projects. Python is known for its simplicity, readability, and extensive library support, making it a popular choice for scripting and automation tasks.

  • Libvirt

    Libvirt is a toolkit that provides a stable and robust API for managing virtualization technologies, including KVM. It offers a wide range of capabilities, such as creating, configuring, and monitoring virtual machines. Libvirt supports multiple programming languages, including C, Python, and Java, making it a flexible choice for KVM software development.

  • QEMU

    QEMU is an open-source machine emulator and virtualizer that works with KVM to provide hardware virtualization. It allows running virtual machines with different architectures and emulates various devices. QEMU provides a comprehensive set of APIs for managing virtual machines, networking, and storage. It is often used in conjunction with KVM for building complex virtualization solutions.

  • OpenStack

    OpenStack is a widely adopted open-source cloud computing platform that supports KVM as one of its hypervisors. It provides a set of services for building and managing private and public clouds. OpenStack includes components like Nova (compute service), Neutron (networking service), and Cinder (block storage service), which integrate with KVM to deliver scalable and flexible cloud infrastructure.

  • Ansible

    Ansible is a powerful automation tool that can be used for deploying and managing KVM-based virtual machines. It allows defining infrastructure as code and automating various tasks, such as provisioning, configuration management, and orchestration. Ansible uses a simple YAML-based syntax and can be easily integrated into existing KVM software development workflows.

  • Docker

    Docker is a popular containerization platform that provides a lightweight and isolated environment for running applications. While KVM focuses on full virtualization, Docker uses containerization techniques to achieve efficient resource utilization. Docker can be used alongside KVM to create hybrid environments and enable the deployment of containerized applications within virtual machines.

  • Kubernetes

    Kubernetes is an open-source container orchestration platform that allows managing and scaling containerized applications across clusters of machines. While not directly tied to KVM, Kubernetes can be used in conjunction with KVM-based virtual machines to create highly scalable and resilient infrastructure. It provides features like automatic scaling, load balancing, and service discovery.

What are top KVM (for Kernel-based Virtual Machine) instruments and tools?

Instruments and tools
  • QEMU: QEMU is an open-source virtualization software that provides full hardware virtualization for a variety of platforms, including x86, ARM, PowerPC, and more. It was first released in 2003 and has since become one of the most widely used KVM tools. QEMU supports a wide range of guest operating systems and is known for its rich feature set and flexible architecture.
  • Libvirt: Libvirt is a toolkit for managing and interacting with various virtualization technologies, including KVM. It provides a common API and a set of command-line tools for managing virtual machines, storage, and network configurations. Libvirt abstracts the underlying virtualization technologies and allows for easy integration and management of KVM-based virtualization environments.
  • virt-manager: virt-manager is a graphical user interface (GUI) tool for managing virtual machines on KVM-based hypervisors. It provides an intuitive interface for creating, configuring, and monitoring virtual machines, as well as managing virtual networks and storage. virt-manager is widely used by both beginners and advanced users due to its simplicity and comprehensive feature set.
  • Kimchi: Kimchi is a lightweight HTML5-based management tool for KVM. It offers a web-based interface for managing virtual machines, storage, and network resources. Kimchi is known for its user-friendly design and ease of use, making it a popular choice for managing KVM environments.
  • VirtIO: VirtIO is a collection of para-virtualized device drivers that enhance the performance and efficiency of KVM-based virtual machines. These drivers provide a high-performance communication channel between the guest operating system and the hypervisor, resulting in improved I/O performance and reduced CPU overhead. VirtIO has been widely adopted and is supported by various operating systems.
  • oVirt: oVirt is an open-source virtualization management platform that is built on top of KVM. It provides a centralized management interface for creating, configuring, and monitoring virtual machines, as well as managing storage and networking resources. oVirt is known for its scalability and advanced features, making it suitable for both small-scale deployments and large-scale virtualization infrastructures.
  • Proxmox VE: Proxmox VE is a complete open-source virtualization platform based on KVM and container virtualization. It offers a web-based management interface and supports the creation and management of virtual machines, containers, storage, and networking. Proxmox VE is widely recognized for its stability, ease of use, and enterprise-grade features, making it a popular choice for both small businesses and large enterprises.
  • Vagrant: Vagrant is a tool for creating and managing development environments. It supports various virtualization providers, including KVM, and allows developers to define and provision virtual machines using a simple configuration file. Vagrant enables developers to easily set up reproducible development environments, making it a valuable tool for software development and testing.

Soft skills of a KVM (for Kernel-based Virtual Machine) Developer

Soft skills

Soft skills of a KVM (Kernel-based Virtual Machine) Developer are essential for their success in the field. These skills complement their technical expertise and enable them to work effectively in collaborative environments and meet project goals.

Junior

  • Communication: Ability to effectively communicate technical concepts and ideas to team members and stakeholders.
  • Problem-solving: Aptitude for identifying and resolving issues related to KVM development.
  • Adaptability: Capacity to quickly learn and adapt to new technologies and methodologies in the virtualization domain.
  • Teamwork: Willingness to collaborate with colleagues to achieve common objectives.
  • Time Management: Ability to prioritize tasks and meet deadlines in a fast-paced development environment.

Middle

  • Leadership: Capability to take ownership of projects and guide junior developers in KVM development.
  • Analytical Thinking: Proficiency in analyzing complex problems and formulating effective solutions.
  • Mentoring: Willingness to share knowledge and provide guidance to less experienced team members.
  • Conflict Resolution: Skill in resolving conflicts and fostering a positive team dynamic.
  • Project Management: Competence in planning, organizing, and executing KVM development projects.
  • Attention to Detail: Ability to pay meticulous attention to the intricacies of KVM development.
  • Critical Thinking: Capacity to evaluate and assess different approaches to KVM development challenges.

Senior

  • Innovation: Ability to think creatively and propose innovative solutions to enhance KVM development processes.
  • Strategic Thinking: Aptitude for envisioning long-term goals and aligning KVM development strategies accordingly.
  • Collaboration: Skill in fostering collaboration between different teams and departments involved in KVM development.
  • Client Management: Competence in understanding client requirements and delivering KVM solutions that meet their needs.
  • Technical Leadership: Capability to lead technical discussions and provide guidance on KVM development best practices.
  • Cross-functional Knowledge: Proficiency in understanding and collaborating with other virtualization technologies beyond KVM.
  • Business Acumen: Understanding of the business implications and impact of KVM development decisions.
  • Continuous Learning: Commitment to staying updated with the latest advancements in KVM development.

Expert/Team Lead

  • Strategic Planning: Proficiency in devising long-term KVM development strategies and roadmaps.
  • Decision Making: Ability to make informed decisions that align with the organization’s goals and vision.
  • Team Management: Skill in managing and coordinating a team of KVM developers to achieve project objectives.
  • Influencing Skills: Capability to influence stakeholders and gain support for KVM development initiatives.
  • Conflict Management: Expertise in resolving conflicts within the team and ensuring a harmonious work environment.
  • Technical Vision: Ability to envision and communicate a clear technical vision for KVM development projects.
  • Strategic Partnerships: Proficiency in establishing and nurturing strategic partnerships with key stakeholders.
  • Quality Assurance: Commitment to ensuring high-quality KVM development deliverables through rigorous testing and review processes.
  • Resource Management: Skill in optimizing resource allocation and utilization for efficient KVM development.
  • Continuous Improvement: Dedication to continuously improving KVM development processes and practices.
  • Industry Knowledge: In-depth understanding of industry trends and emerging technologies in the virtualization domain.

Let’s consider Difference between Junior, Middle, Senior, Expert/Team Lead developer roles.

Seniority NameYears of experienceResponsibilities and activitiesAverage salary (USD/year)
Junior Developer0-2 yearsWorks on simple and well-defined tasks under close supervision. Assists in coding, testing, and debugging. Learns and follows coding standards and best practices. Collaborates with more experienced team members.$50,000 – $70,000
Middle Developer2-5 yearsTakes on more complex tasks and projects, often with some level of independence. Develops and maintains software applications. Collaborates with team members to design and implement solutions. Participates in code reviews and provides feedback.$70,000 – $90,000
Senior Developer5+ yearsLeads the development of complex software projects. Mentors junior and middle developers. Designs and implements scalable solutions. Collaborates with stakeholders to gather and refine requirements. Conducts code reviews and ensures adherence to best practices.$90,000 – $120,000
Expert/Team Lead Developer8+ yearsLeads a team of developers and oversees multiple projects. Defines technical strategies and roadmaps. Provides guidance on architecture and design. Manages resources and ensures successful project delivery. Collaborates with cross-functional teams and stakeholders.$120,000 – $150,000+

How and where is KVM (for Kernel-based Virtual Machine) used?

How and where
Case NameCase Description
Server ConsolidationKVM allows for efficient server consolidation by running multiple virtual machines (VMs) on a single physical server. This reduces hardware costs, power consumption, and data center space requirements. For example, a company can run multiple web servers, database servers, and application servers on a single physical server using KVM.
Development and Testing EnvironmentsKVM provides an ideal platform for creating development and testing environments. Developers can quickly set up multiple VMs to simulate different operating systems, software configurations, and network environments. This allows for easy testing and debugging without impacting the production environment.
High Availability and FailoverKVM supports high availability and failover capabilities, ensuring business continuity. By using live migration, VMs can be seamlessly moved from one physical host to another, minimizing downtime during hardware maintenance or failures. This feature is crucial for mission-critical applications that require uninterrupted service.
Desktop VirtualizationKVM enables desktop virtualization, where multiple virtual desktops can be hosted on a single physical machine. This allows for centralized management, enhanced security, and simplified software deployment across the organization. Desktop virtualization also provides flexibility for remote workers who can access their virtual desktops from any device.
Disaster RecoveryKVM facilitates disaster recovery by replicating VMs to remote servers or backup storage. In the event of a system failure or data loss, the replicated VMs can be quickly activated, minimizing downtime and ensuring data integrity. KVM’s flexibility and scalability make it an ideal choice for implementing robust disaster recovery solutions.
Cloud ComputingKVM is widely used in cloud computing environments to provide virtualized infrastructure services. Cloud service providers rely on KVM to create and manage virtual machines for their customers. KVM’s performance, security, and scalability make it a preferred choice for building private, public, and hybrid cloud platforms.
Software Defined Networking (SDN)KVM integrates well with SDN technologies, allowing for efficient network virtualization and management. By leveraging KVM’s capabilities, organizations can create virtual networks and easily allocate resources to different applications or services. This improves network agility, scalability, and reduces operational costs.
Big Data and AnalyticsKVM supports the deployment of big data and analytics workloads, which often require significant computational resources. By running these workloads on virtual machines, organizations can optimize resource utilization and scale their infrastructure as needed. KVM’s performance and flexibility enable efficient processing of large datasets and complex analytics algorithms.
Education and TrainingKVM is widely used in educational institutions for teaching and training purposes. By leveraging KVM, instructors and students can create virtualized environments to simulate real-world scenarios, experiment with different configurations, and gain hands-on experience without the need for physical hardware. This enhances learning opportunities and reduces costs.
Internet of Things (IoT) DeploymentsKVM plays a crucial role in IoT deployments by providing a secure and scalable virtualization platform. IoT devices can be virtualized as VMs, allowing for centralized management, security enhancements, and efficient resource allocation. KVM’s ability to handle diverse workloads makes it well-suited for IoT applications across various industries.

TOP 15 Facts about KVM (for Kernel-based Virtual Machine)

Facts about
  • KVM (Kernel-based Virtual Machine) is an open-source virtualization technology that allows multiple operating systems to run concurrently on a single host machine.
  • KVM was first introduced in 2006 and has become a popular choice for virtualization due to its performance, flexibility, and integration with the Linux kernel.
  • Unlike other virtualization technologies, KVM is included as part of the Linux kernel, which means it benefits from continuous development and improvements from the open-source community.
  • KVM provides full virtualization, which allows guest operating systems to run unmodified, providing better compatibility and performance compared to paravirtualization.
  • With KVM, each virtual machine (VM) is treated as a regular Linux process and has its own virtual CPU, memory, and other resources allocated by the host machine.
  • KVM supports a wide range of guest operating systems, including Linux distributions, Windows, BSD, Solaris, and more.
  • KVM uses hardware virtualization extensions such as Intel VT-x and AMD-V to enhance performance and security.
  • Live migration is a key feature of KVM, which allows virtual machines to be moved from one physical host to another without interrupting their operation, ensuring high availability and load balancing.
  • KVM provides excellent performance with near-native speeds, thanks to its efficient use of hardware resources and direct access to the host’s CPU and memory.
  • As an open-source technology, KVM offers cost savings compared to proprietary virtualization solutions, as there are no licensing fees associated with its usage.
  • KVM integrates well with other Linux tools and technologies, such as libvirt, QEMU, and virt-manager, providing a comprehensive virtualization ecosystem.
  • KVM supports advanced features like virtual machine snapshots, which enable administrators to capture and restore the state of a VM at a specific point in time.
  • KVM provides security isolation between virtual machines, preventing one VM from accessing or affecting the resources of another, enhancing overall system security.
  • KVM has a large and active community of developers and users, ensuring ongoing support, bug fixes, and new features.
  • KVM is widely used in various industries, including cloud computing, data centers, enterprise environments, and virtual desktop infrastructure (VDI) deployments.

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Maria Lapko
Global Partnership Manager