Virtual Machines in Cloud Computing

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Virtual Machines in Cloud Computing

In this article, I will discuss Virtual Machines in Cloud Computing. Please read our previous article, where we discussed What is Cloud Computing. But before understanding Virtual Machines, let us first understand the state of IT before Virtual Machines came into existence.

Application without Virtual Machines:

In today’s world, almost every industry and business, including hotels, banks, airlines, tourism, shopping malls, online portals, and hardware, rely on applications to power and operate their businesses. A reliable, high-performing, and scalable application is essential for any business to succeed and thrive in a competitive market.

It can be said that applications are crucial to running a business smoothly in today’s world. Additionally, there are two important factors to consider when looking at applications:

1. First, Designing and developing the business application
2. Second, Host the application on a server to make it available for the business.

Now, let’s discuss how we hosted the application before Virtual Machines and containers came into the picture. Once we understand this, we will discuss What Virtual Machine is and how they overcome problems.

In the absence of Virtual Machines or cloud computing, hosting an application requires a physical server. As a business, the crucial factor to consider is the size and speed of the server. It is difficult to accurately predict the application’s demand from the outset, as the business may grow over time. To err on the side of caution, it is advisable to opt for a high-end physical server, which can be quite expensive.

Apart from the primary expense of purchasing the physical server, there are also recurring monthly operating expenses such as energy costs for power and cooling, hiring staff to maintain the server, and costs for operating system licenses. Typically, only a small portion of the server capacity (about 5% to 10%) is utilized, wasting a significant amount of company funds.

How do we host the application?

To get started, we need a physical server. We’ll then install an operating system, such as Windows or Linux, on top of the server. Finally, we’ll install our business application on top of the operating system. Once this is complete, our application will be ready for use, and users will be able to access it.

If you’re starting a new business and require a new application, it’s important to note that you’ll also need a new physical server and a license for the operating system it runs on. Once the operating system is installed, you can then install the new application. It’s crucial to keep in mind that in addition to the cost of the physical server, there will also be monthly recurring operating expenses.

You may be wondering why we can’t install the new application on our current physical server since the first one is only utilizing a small portion of its capacity. While it is possible in some cases, it is not always feasible.

Why can’t we host on the existing physical server?

There are multiple reasons why this could happen. One possibility is that the new application may have different dependencies than the initial application. Another possibility is that the new application requires a different version of the framework. Alternatively, the new application may require a distinct operating system altogether. It could also be the case that both applications need to access the same resources, leading to resource conflicts.

One solution would be to purchase a new physical server for each application to address the issue at hand. This approach results in direct correspondence between an application and a physical server. However, this means that a new physical server must be procured every time a new business application is needed. Furthermore, these applications typically utilize only a small portion (between 5% and 10%) of the server’s capacity. As a result, this method is not cost-effective for the company. This hosting model was prevalent until the introduction of virtualization.

What are Virtual Machines in Cloud Computing?

Virtual Machines (VMs) in cloud computing are a form of virtualization technology that allows you to create and run multiple instances of virtual computers on a single physical server or host system. Each virtual machine operates as an independent and isolated entity, running its own operating system (OS) and applications like a physical computer.

Nowadays, virtualization allows us to maximize the potential of physical servers. Kindly refer to the diagram below to help you grasp this concept more easily.

From the image above, it is clear that the host operating system is installed on the physical server. Essentially, the operating system is installed directly on the physical server. We’ve added Hypervisor software on top of the Operating System. This technology, from VMware, virtualizes the physical server’s hardware.

We use a Hypervisor to create virtual machines. With this technology, we can run multiple virtual machines on one physical server to meet the needs of our business. The first application is operating on VM1 while the second application is running on VM2, and so on. This approach is excellent because it allows us to maximize the server hardware’s usage.

Upon closer inspection of the diagram above, it can be observed that there is no longer a one-to-one correspondence between the application and the physical server. Instead, a new Virtual Machine is now required for each new application. As a result of virtualization, it is now possible to run multiple applications safely and securely on a single physical server.

Thanks to virtualization, each application now operates as if it is running on a dedicated physical server, complete with its own processor, memory, and drive space. However, these applications are actually running on a shared physical server, but each has its own dedicated virtual machine.

So, what exactly a Virtual Machine is?

Think of a virtual machine as a computer that exists within another computer. It’s possible to run several virtual machines on one physical server at once. You can install any operating system you prefer (e.g., Windows, Linux) on each virtual machine and install the necessary software and dependencies to meet the application requirements.

Popular virtualization platforms used in cloud computing include VMware, Microsoft Hyper-V, Xen, and KVM (Kernel-based Virtual Machine). Cloud providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) offer VM instances as a core service, allowing users to create and manage VMs in the cloud.

Virtual machines are a foundational cloud computing technology used for various purposes, such as running applications, testing environments, development, server consolidation, and more. They provide a way to maximize resource utilization, isolate workloads, and achieve flexibility in deploying and managing diverse computing environments.

Virtual Machines and Multiple Applications:

Imagine that we have three applications, namely App 1, App 2, and App 3, and we want to run them all on a single physical server, which we can call Server 1. However, we cannot run these applications directly on the server hardware. We need an operating system like Windows or Linux installed on the Physical Server to do so. This operating system is referred to as the Host Operating System, as it is installed at the server level. To enable the running of these applications, we install a software called Hypervisor on top of this Host Operating System. The Hypervisor is responsible for creating and managing virtual machines. So, to host the three applications, we create three virtual machines on top of the Hypervisor. We then host each of the applications within each virtual machine, as illustrated in the image below.

As we’ve previously discussed, a virtual machine emulates the hardware of a physical server, allowing each created virtual machine to receive a portion of the server’s hardware resources. We made three virtual machines in our case, so each one is allocated 33.33% of the memory, disk space, processor, and other hardware resources.

Advantages of Virtual Machines in Cloud Computing:

Virtual machines (VMs) offer several advantages in cloud computing, making them a versatile and widely used technology for deploying and managing applications. Here are some of the key advantages of using virtual machines in cloud computing:

1. Isolation and Security: VMs provide strong isolation between different instances. Each VM operates independently with its own dedicated resources, filesystem, and operating system, minimizing the risk of one application affecting others.
2. Legacy Application Support: VMs allow you to run legacy applications that require specific operating systems or software versions, enabling you to modernize without rewriting or modifying the application.
3. Operating System Flexibility: VMs support a wide range of operating systems, allowing you to run different OSes on the same physical hardware and accommodate diverse application needs.
4. Resource Allocation: VMs allow you to allocate specific amounts of CPU, memory, and storage to each instance, ensuring consistent and predictable performance for applications.
5. Hardware Abstraction: VMs abstract the underlying physical hardware, making it easier to move VM instances between different hosts or cloud environments without worrying about hardware compatibility.
6. Application Isolation: VMs are ideal for isolating different applications or workloads from one another. This is particularly useful for multi-tenant environments where multiple customers share the same infrastructure.
7. Snapshot and Cloning: VMs can be easily cloned, or snapshots are taken, providing a fast and efficient way to duplicate or backup instances for testing, development, and disaster recovery purposes.
8. Hardware Virtualization: VMs leverage hardware virtualization features provided by modern processors, enhancing performance and ensuring compatibility across different host systems.
9. Multi-Tenancy and Resource Sharing: VMs enable efficient resource sharing among multiple customers or users while maintaining strong isolation and security boundaries.
10. Compatibility and Interoperability: VMs can be migrated between different virtualization platforms and cloud providers with minimal effort, providing flexibility and avoiding vendor lock-in.
11. Application Development and Testing: VMs can be provisioned quickly for development, testing, and debugging purposes, providing consistent environments across the software development lifecycle.
12. Disaster Recovery: VM snapshots and images can be used for disaster recovery scenarios, enabling rapid restoration of applications and services in case of failures.
13. Support for Stateful Applications: VMs are well-suited for running stateful applications, such as databases, that require persistent storage and strong isolation.
14. Workload Isolation: VMs can isolate workloads from noisy neighbors, ensuring that resource-intensive or critical workloads do not impact others.
15. Security Segmentation: VMs can be used to implement security segmentation, separating sensitive workloads from less sensitive ones for improved security and compliance.

Virtual machines remain a fundamental building block in cloud computing environments, providing a flexible, secure, and reliable way to deploy and manage a wide range of applications and workloads.

Disadvantages of Virtual Machines in Cloud Computing

One benefit of using virtual machines is that we can run multiple applications on a single physical server, allowing us to effectively use the server’s resources, such as memory, disk space, and processor. However, it is necessary to create separate virtual machines for each application, which comes with a significant amount of overhead in terms of cost and maintainability. In the following section, we will discuss the drawbacks of virtual machines.

It’s crucial to note that Apps 1 to 3 cannot run directly on a virtual machine. The virtual machine’s purpose is to virtualize the server hardware resources, which means it’s only a portion of the underlying hardware. Therefore, we cannot run an application directly on the hardware. An operating system is necessary to run an application on the Virtual Machine.

For our example, we have three virtual machines, which means we need to install an operating system on each one. Typically, we can choose between Windows or Linux. The operating system we install on a virtual machine is referred to as the Guest Operating System. After installing the guest OS, we must install the application and any dependencies required. Installing Windows OS on one virtual machine and Linux OS on another is also possible. Refer to the diagram below for a clearer illustration.

Downsides of Virtual Machine:

While virtual machines (VMs) offer numerous advantages for cloud computing, they also come with certain disadvantages and challenges that organizations should consider. Here are some of the key disadvantages of using virtual machines in cloud computing:

1. Resource Overhead: VMs introduce a level of overhead due to the need for running a complete guest operating system for each instance. This overhead can lead to slightly reduced performance and higher resource consumption compared to containerized or bare-metal solutions.
2. Limited Scalability: VMs may not scale as efficiently as containers for applications with high demands for rapid scaling, as the overhead of managing multiple OS instances can become a limiting factor.
3. Resource Fragmentation: VMs with fixed CPU, memory, and storage allocations can lead to resource fragmentation. This can result in inefficient resource utilization if VMs are provisioned with more resources than they actually need.
4. Slower Startup Times: VMs typically have longer startup times compared to containers, as they involve booting up an entire guest OS. This can impact the agility and responsiveness of applications.
5. Less Granularity: VMs offer less granularity than containers in terms of resource allocation. It’s more challenging to allocate specific amounts of resources (CPU, memory) to individual processes within a VM.
6. Large Image Sizes: VM images tend to be larger than container images, which can impact storage and transfer costs in cloud environments.
7. Limited Portability: While VMs offer portability, they are generally less portable than containers. Moving VMs between different virtualization platforms or cloud providers might require additional configuration and effort.
8. Complex Management: Managing VMs, including patching, updates, and maintenance of guest OSes, can be more complex and time-consuming compared to containerized solutions.
9. Hypervisor Overhead: VMs require a hypervisor layer for virtualization, which introduces additional overhead and complexity compared to the lightweight isolation of containers.
10. Limited Microservices Benefits: VMs are more suitable for running monolithic applications rather than microservices, as the overhead of running a complete OS for each VM may negate some of the benefits of microservices architecture.
11. Vendor Lock-In: Some virtualization platforms and management tools might lock organizations into specific vendor ecosystems, limiting flexibility and interoperability.
12. Compatibility Challenges: Applications designed to run on specific OSes might encounter compatibility challenges when moved between different VMs with different guest OSes.

13. Licensing Costs: Some virtualization platforms may have associated licensing costs, which can add to the overall expenses of using VMs in a cloud environment.

14. Wasted of Server Resources: Installing three Operating Systems requires significant server hardware resources. This results in the wastage of vital server components like RAM, Disk Space, Memory, and Processor time, which are used to keep the Virtual Machines operational.

15. Admin Time to Keep OS up to Date: Every time the Operating System is updated or a system patch is available, it needs to be installed by the system administrator on all Virtual Machines that have the same Operating System. This process takes up a significant amount of administrative time for each installation.

16. Operating System License Cost: We also need to pay for these licenses.

17. Virtual Machine Bootup Consumes time: As we previously discussed, a virtual machine is essentially a computer within a computer, complete with its own operating system. To get the virtual machine up and running, its operating system must be booted, which can take a significant amount of time. In order to launch Application 1, we need to boot the operating system of Virtual Machine 1 and the host operating system running at the server level.

It’s important for organizations to carefully weigh these disadvantages against the benefits of using virtual machines and consider their specific workload requirements when deciding whether to use VMs or explore alternative technologies like containers or serverless computing.

What is Virtualization in Cloud Computing?

Virtualization in cloud computing refers to the technology and practice of creating virtual instances or representations of physical resources, such as computing hardware, storage devices, and network components. These virtual instances, known as virtual machines (VMs) or virtualized resources, simulate the behavior and characteristics of physical counterparts but operate independently and share the underlying physical resources of a host system.

Key concepts and components of virtualization in cloud computing include:

1. Hypervisor: The hypervisor, also known as a virtual machine monitor (VMM), is a software layer that manages and controls the creation, provisioning, and operation of virtual machines. It abstracts the underlying physical hardware and allocates resources to VMs.
2. Virtual Machines (VMs): VMs are isolated instances of virtualized hardware and software environments. Each VM includes its own guest operating system, applications, and configurations, making it independent of other VMs on the same host.
3. Resource Pooling: Virtualization allows for the pooling of physical resources, such as CPU, memory, and storage, which can then be dynamically allocated and shared among multiple VMs. This resource pooling enhances efficiency and utilization.
4. Isolation: Virtualization provides strong isolation between VMs, ensuring that activities in one VM do not affect others. Each VM operates as if it were running on a separate physical machine.
5. Abstraction: Virtualization abstracts the complexities of the underlying hardware, allowing applications to run in consistent environments regardless of the host’s physical characteristics.
6. Snapshot and Cloning: Virtualization platforms often offer features like snapshotting and cloning, allowing administrators to create copies of VMs or capture their state at a particular point in time.
7. Migration and Live Migration: VMs can be moved between physical hosts or data centers, a process known as migration. Live migration allows VMs to be moved without interruption to their operation.
8. Bare-Metal Hypervisors run directly on the physical hardware, providing efficient performance and resource utilization. Examples include VMware vSphere, Microsoft Hyper-V, and Xen.
9. Hosted Hypervisors: Hosted hypervisors run on top of a host operating system. While they introduce some overhead, they are easier to manage. Examples include VMware Workstation, Oracle VirtualBox, and Parallels Desktop.
10. Storage and Network Virtualization: In addition to server virtualization (VMs), cloud computing often involves virtualizing storage and network resources, allowing for dynamic allocation and management.
11. Cloud Services: Virtualization forms the foundation of cloud services, enabling providers to efficiently deliver and manage resources to users in a scalable and on-demand manner.

Virtualization is a foundational technology in cloud computing, enabling efficient resource utilization, isolation, scalability, and flexibility. It allows organizations to optimize their hardware investments, streamline management, and provide elastic computing environments that adapt to changing business needs.

Virtualization is the key technology for Cloud Computing. It involves partitioning a single physical server into multiple logical servers. Once divided, each logical server functions like a physical server, capable of running its own operating system and applications.

Virtualization is very handy for software developers and testers, as it allows developers to write code that runs in many different environments and, more importantly, to test that code. Virtualization is mainly used for three main purposes. 

1. Network Virtualization
2. Server Virtualization
3. Storage Virtualization

Network Virtualization in Cloud Computing:  

One way to optimize network resources is to divide the available bandwidth into separate channels. These channels operate independently from one another and can be assigned to specific servers or devices in real time. This allows for more efficient use of available resources.

Network virtualization in cloud computing refers to the abstraction and virtualization of network resources, such as switches, routers, firewalls, and load balancers, to create a logically isolated and programmable network environment. It allows multiple virtual networks, often referred to as virtual LANs (VLANs) or virtual networks, to run on a shared physical network infrastructure, enabling better resource utilization, isolation, and flexibility.

Key concepts and components of network virtualization in cloud computing include:

1. Virtual Networks: Virtual networks are logically segmented networks that run on top of a shared physical network infrastructure. Each virtual network operates as if it were a separate and isolated network, even though it shares the same physical resources.
2. Overlay Networks: Overlay networks use encapsulation techniques to create virtual network segments on top of the physical network. This allows for the creation of multiple isolated virtual networks using the same physical infrastructure.
3. Hypervisor Network Virtualization: Hypervisor-based network virtualization involves virtualizing network resources at the hypervisor level. Virtual switches within hypervisors manage network traffic between virtual machines and connect them to the physical network.
4. Software-Defined Networking (SDN): SDN is a network architecture that separates the control plane from the data plane, allowing for centralized control and programmability of network behavior. SDN can be used for network virtualization by defining and managing virtual networks through a central controller.
5. Network Overlays: Network overlays create virtual networks on top of existing physical networks. Technologies like VXLAN (Virtual Extensible LAN) and NVGRE (Network Virtualization using Generic Routing Encapsulation) are commonly used for creating overlay networks.
6. Network Segmentation: Network virtualization enables fine-grained network segmentation, allowing different virtual networks to be isolated from each other for security and performance reasons.
7. Multi-Tenancy: Network virtualization supports multi-tenancy, allowing different customers or user groups to have their own isolated virtual networks within a shared infrastructure.
8. Elasticity and Scalability: Network virtualization allows for the dynamic creation, modification, and removal of virtual networks, enabling cloud providers to respond quickly to changing demands.
9. Isolation and Security: Virtual networks provide isolation between different tenant environments, enhancing security and preventing unauthorized access to sensitive data.
10. Automation and Orchestration: Network virtualization can be orchestrated and managed programmatically, allowing for automated provisioning, configuration, and management of virtual networks.
11. Load Balancing and Traffic Routing: Network virtualization can include features like load balancing, traffic routing, and firewall services for enhanced application performance and security.
12. Hybrid Cloud Connectivity: Network virtualization can facilitate connectivity between on-premises data centers and cloud environments, enabling hybrid cloud scenarios.

Network virtualization plays a crucial role in modern cloud computing environments, enabling cloud providers and organizations to efficiently manage and allocate network resources, improve security, and deliver flexible and scalable network services to applications and users. It helps bridge the gap between the physical network infrastructure and the dynamic, on-demand nature of cloud computing.

Storage Virtualization in Cloud Computing:

Storage virtualization refers to the consolidation of physical storage from various network storage devices into a single storage system that can be managed from a central console. This technique is often employed in storage area networks (SANs).

Storage virtualization in cloud computing refers to the abstraction and virtualization of storage resources to create a unified and flexible storage infrastructure that is independent of the underlying physical hardware. It allows multiple storage devices, arrays, and technologies to be managed and presented as a single, cohesive storage pool, enhancing efficiency, scalability, and management in cloud environments.

Key concepts and components of storage virtualization in cloud computing include:

1. Virtual Storage Pool: Storage virtualization creates a virtual storage pool that aggregates physical storage resources from different devices and locations. This pool is managed and presented as a unified storage system.
2. Abstraction Layer: A storage virtualization layer abstracts the complexities of the underlying physical storage hardware. It provides a consistent interface for managing and provisioning storage resources.
3. Thin Provisioning: Storage virtualization allows for thin provisioning, where virtual storage volumes are allocated only as needed. This helps optimize storage utilization and reduces wastage.
4. Dynamic Provisioning: Virtualized storage can be dynamically allocated, resized, and provisioned to meet changing workload demands.
5. Data Migration: Storage virtualization enables seamless data migration and movement between different storage devices and tiers without disrupting applications.
6. Data Tiering: Storage virtualization supports data tiering, allowing data to be automatically moved between different storage types (e.g., SSD, HDD) based on usage patterns and performance requirements.
7. Snapshots and Replication: Virtualized storage often includes features like snapshots, cloning, and data replication for data protection, backup, and disaster recovery.
8. Aggregated Management: Storage virtualization provides centralized management and monitoring of the entire storage infrastructure, simplifying administrative tasks.
9. Vendor Neutrality: Storage virtualization enables the mixing and matching of storage devices from different vendors, avoiding vendor lock-in and maximizing hardware flexibility.
10. Elasticity and Scalability: Virtualized storage can scale horizontally by adding more physical storage devices to the virtual pool, accommodating growing storage needs.
11. Performance Optimization: Storage virtualization can optimize performance by dynamically allocating resources based on workload requirements and prioritizing critical applications.
12. Data Migration and Mobility: Virtualized storage supports workload and data mobility, allowing applications and data to move seamlessly between different storage devices and platforms.
13. Data Deduplication and Compression: Storage virtualization can include data deduplication and compression techniques to reduce storage space requirements.
14. Integration with Cloud Services: Storage virtualization can integrate with cloud storage services, enabling hybrid cloud scenarios and seamless movement of data between on-premises and cloud storage.

Storage virtualization enhances the efficiency, scalability, and management of storage resources in cloud computing environments. It allows cloud providers and organizations to optimize storage utilization, improve data protection and availability, and deliver more agile and cost-effective storage solutions to support various workloads and applications.

Server Virtualization in Cloud Computing:

Server virtualization involves concealing server resources such as processors, RAM, and operating systems from users. This technique aims to enhance resource sharing and ease the computational burden and complexity for users.

Server virtualization in cloud computing involves the creation of multiple virtual instances, known as virtual machines (VMs), on a single physical server. Each VM operates as an independent and isolated server with its own operating system, applications, and resources. Server virtualization is a fundamental technology that plays a crucial role in building and managing cloud computing environments.

Key concepts and components of server virtualization in cloud computing include:

1. Hypervisor: The hypervisor, also known as a virtual machine monitor (VMM), is a software layer that enables the creation, provisioning, and management of virtual machines. It abstracts and partitions the physical server’s resources to allocate them to VMs.
2. Virtual Machines (VMs): VMs are isolated instances of virtualized servers running on the same hardware. Each VM includes its own guest operating system, applications, and configurations.
3. Resource Pooling: Server virtualization allows the pooling of physical resources, such as CPU, memory, storage, and network bandwidth. These resources can be dynamically allocated and shared among multiple VMs.
4. Isolation: VMs are isolated from one another, ensuring that activities and processes in one VM do not impact others. Each VM operates as if it were running on a dedicated physical server.
5. Consolidation: Server virtualization enables server consolidation by running multiple VMs on a single physical server. This helps optimize resource utilization and reduce hardware costs.
6. Elasticity and Scalability: VMs can be rapidly provisioned, cloned, and scaled up or down to meet changing workload demands. This dynamic provisioning enhances flexibility and agility.
7. Live Migration: Some virtualization platforms support live migration, allowing VMs to be moved from one physical host to another without downtime or service interruption.
8. Backup and Disaster Recovery: VM snapshots and images can be used for data protection, backup, and disaster recovery purposes.
9. Testing and Development: VMs are commonly used for testing and development, providing consistent and isolated environments that can be easily duplicated and discarded.
10. Resource Allocation: Server virtualization allows fine-grained resource allocation, enabling administrators to allocate specific amounts of CPU, memory, and storage to each VM.
11. Legacy Application Support: Server virtualization allows legacy applications to run on modern hardware without modifying or rewriting the application code.
12. Multi-Tenancy: VMs can create isolated multi-tenant environments where different customers or user groups share the same physical infrastructure while remaining isolated from each other.
13. Hybrid Cloud Integration: Server virtualization can facilitate hybrid cloud scenarios by enabling seamless migration of VMs between on-premises data centers and cloud environments.

Server virtualization is a core technology that underpins cloud computing platforms’ efficiency, scalability, and flexibility. It enables cloud providers and organizations to optimize resource utilization, reduce hardware costs, and deliver scalable and responsive computing environments to support a variety of workloads and applications.

In the next article, I will discuss Containers in Cloud Computing and how containers overcome the problems of Virtual Machines in Cloud Computing. Here, in this article, I try to Explain Virtual Machines in Cloud Computing in detail, and I hope you enjoy this Virtual Machines in Cloud Computing article.