Virtual machines are foundational to cloud computing, enabling multiple operating systems to run on a single physical machine. They provide flexibility, resource efficiency, and isolation, making them crucial for various cloud architectures and applications.

Understanding VM creation, management, and networking is essential for deploying scalable cloud solutions. This knowledge helps optimize resource utilization, ensure security, and leverage cloud platforms effectively for diverse workloads and requirements.

Virtual machine fundamentals

• Virtual machines (VMs) are software-based emulations of physical computers that run on top of a host operating system and hardware
• VMs allow multiple operating systems to run concurrently on a single physical machine, providing isolation, flexibility, and resource efficiency
• Understanding the fundamentals of virtualization is essential for effectively leveraging VMs in cloud computing architectures

Hardware virtualization

• Enables running multiple operating systems on a single physical machine by abstracting the underlying hardware resources
• Virtualization software, called a hypervisor, manages the allocation of physical resources (CPU, memory, storage) to each VM
• Provides isolation between VMs, ensuring that one VM's activities do not affect the performance or stability of other VMs on the same host
• Allows for more efficient utilization of hardware resources by dynamically allocating resources based on the needs of each VM

Hypervisors for virtualization

• Hypervisors are the software layer responsible for managing and orchestrating virtual machines on a host system
• Two main types of hypervisors:
  • Type 1 (bare-metal): Runs directly on the host hardware (Hyper-V, VMware ESXi, Xen)
  • Type 2 (hosted): Runs as a software layer on top of the host operating system (VirtualBox, VMware Workstation)
• Hypervisors handle resource allocation, VM creation, and management of virtual hardware components for each VM
• Provide features like live migration, snapshot management, and virtual networking

Types of virtual machines

• System VMs: Emulate a complete hardware environment, allowing a full operating system to run within the VM (Windows, Linux)
• Process VMs: Execute individual applications or processes within a controlled environment (Java Virtual Machine)
• Paravirtualized VMs: Collaborate with the hypervisor to optimize performance by directly accessing hardware resources
• Hybrid VMs: Combine aspects of both system and process VMs to provide a balance between compatibility and performance

Virtual machine vs physical servers

• VMs offer greater flexibility, scalability, and resource efficiency compared to physical servers
• Multiple VMs can run on a single physical server, maximizing hardware utilization and reducing costs
• VMs can be easily created, cloned, and migrated between hosts, enabling rapid deployment and high availability
• Physical servers provide direct access to hardware resources and may be necessary for workloads with specific performance or compatibility requirements

Creating virtual machines

• Provisioning virtual machines involves defining their hardware specifications, operating system, and configuration
• Cloud platforms offer streamlined workflows and tools for creating and managing VMs at scale
• Understanding the key components and processes involved in VM creation is crucial for deploying applications and services in the cloud

Virtual machine images

• VM images are pre-configured templates that include an operating system, drivers, and optional software packages
• Images serve as the foundation for creating new VM instances quickly and consistently
• Cloud providers offer a wide range of pre-built images for popular operating systems and software stacks (Ubuntu, Windows Server, LAMP)
• Custom images can be created by capturing the state of an existing VM, including its operating system, configuration, and installed applications

Provisioning VMs in the cloud

• Cloud platforms provide web-based interfaces, command-line tools, and APIs for provisioning VMs
• Users can select the desired VM image, specify hardware resources (CPU, memory, storage), and configure networking and security settings
• Provisioning processes automate the creation and configuration of VMs, reducing manual effort and ensuring consistency
• Cloud providers offer features like autoscaling and load balancing to automatically adjust the number of VM instances based on demand

Configuring VM resources

• VMs can be configured with specific hardware resources to meet application requirements
• CPU: Number of virtual CPUs allocated to the VM, affecting processing power
• Memory: Amount of RAM assigned to the VM, impacting application performance and capacity
• Storage: Disk space allocated for the VM's operating system, applications, and data storage
• Network: Bandwidth and connectivity options for the VM, including virtual network interfaces and public IP addresses

Deploying custom VM images

• Custom VM images allow organizations to standardize their application environments and streamline deployment processes
• Creating custom images involves installing the desired operating system, drivers, and software packages on a VM and then capturing its state
• Custom images can be version-controlled and shared across teams to ensure consistency and reproducibility
• Cloud platforms provide tools for managing custom images, including import/export functionality and access control mechanisms

Virtual machine instances

• Virtual machine instances are the running instantiations of VM images in the cloud
• Instances encapsulate the compute, memory, and storage resources allocated to a specific VM
• Managing instances involves controlling their lifecycle, monitoring performance, and optimizing resource utilization

Compute instances in the cloud

• Cloud platforms offer a wide range of instance types optimized for different workload requirements (general-purpose, compute-optimized, memory-optimized, GPU-accelerated)
• Instances can be provisioned on-demand, allowing for rapid scaling and flexibility in resource allocation
• Compute instances are billed based on the resources consumed and the duration of their runtime
• Instances can be managed through cloud provider interfaces, APIs, or infrastructure-as-code tools (Terraform, CloudFormation)

Instance types and sizes

• Instance types define the hardware specifications and performance characteristics of a VM
• Sizes within an instance type determine the amount of CPU, memory, and storage resources allocated to the VM
• Selecting the appropriate instance type and size is crucial for optimizing application performance and cost-efficiency
• Cloud providers offer instance type families tailored for specific use cases (web servers, databases, machine learning)

Autoscaling groups of instances

• Autoscaling allows automatic adjustment of the number of VM instances based on predefined scaling policies
• Scaling policies can be based on metrics like CPU utilization, network traffic, or custom application metrics
• Autoscaling ensures that applications can handle variable workloads by automatically adding or removing instances to maintain performance and availability
• Autoscaling groups define the minimum, maximum, and desired number of instances to maintain

Spot instances vs reserved instances

• Spot instances are spare compute capacity offered at a discounted price by cloud providers
• Spot instances can be terminated by the provider with short notice if the spare capacity is needed elsewhere
• Reserved instances allow users to commit to a specific instance type and duration in exchange for significant discounts compared to on-demand pricing
• Reserved instances are suitable for predictable, steady-state workloads, while spot instances are ideal for flexible, interruption-tolerant workloads

Networking virtual machines

• Virtual networking enables communication between VMs, as well as connectivity to external networks and resources
• Configuring virtual networks involves defining IP address ranges, subnets, and network security rules
• Understanding virtual networking concepts is essential for designing scalable and secure cloud architectures

Virtual networking concepts

• Virtual networks (VNets) are logically isolated networks within a cloud environment
• VNets allow VMs to communicate with each other and with other cloud resources securely
• Subnets are subranges of IP addresses within a VNet, enabling logical segmentation of resources
• Network security groups (NSGs) act as virtual firewalls, controlling inbound and outbound traffic at the subnet or VM level

Private and public IP addresses

• Private IP addresses are used for communication within a virtual network and are not accessible from the public internet
• Public IP addresses are assigned to resources that require direct internet accessibility, such as web servers or VPN gateways
• Network address translation (NAT) enables outbound internet connectivity for VMs with private IP addresses
• Public IP addresses can be static (reserved) or dynamic (assigned on-demand)

Configuring virtual networks

• Cloud platforms provide tools and interfaces for creating and configuring virtual networks
• Virtual network configuration involves specifying IP address ranges, creating subnets, and defining network security rules
• VNets can be connected to on-premises networks using VPN gateways or dedicated interconnects
• Peering allows connecting multiple VNets within the same region or across regions for seamless communication

Load balancing VM instances

• Load balancers distribute incoming network traffic across multiple VM instances to improve performance, scalability, and availability
• Layer 4 load balancers operate at the transport layer (TCP/UDP) and distribute traffic based on IP address and port
• Layer 7 load balancers operate at the application layer (HTTP/HTTPS) and can route traffic based on URL, headers, or application-specific rules
• Load balancers integrate with autoscaling to automatically distribute traffic to newly added or removed instances

Storage for virtual machines

• Virtual machines require storage for their operating system, applications, and data
• Cloud platforms offer various storage options optimized for different performance, durability, and cost requirements
• Understanding storage fundamentals is crucial for designing resilient and scalable VM architectures

Virtual machine storage options

• Ephemeral storage: Temporary storage directly attached to the VM instance, lost when the instance is terminated (instance store)
• Persistent storage: Durable storage that persists independently of the VM instance lifecycle (block storage, file storage, object storage)
• Block storage: High-performance, low-latency storage suitable for databases and applications requiring frequent read/write operations (Amazon EBS, Azure Managed Disks)
• Object storage: Scalable, durable storage for unstructured data, accessible via HTTP/HTTPS APIs (Amazon S3, Azure Blob Storage)

Persistent disks and volumes

• Persistent disks are block storage devices that can be attached to VM instances
• Disks can be provisioned with different performance tiers (SSD, HDD) and capacities to meet application requirements
• Volumes are logical partitions of persistent disks that can be formatted with a file system and mounted to VM instances
• Persistent disks and volumes provide data durability and can be detached and reattached to different VM instances

Ephemeral vs durable storage

• Ephemeral storage is directly attached to the VM instance and has the same lifecycle as the instance
• Ephemeral storage is typically faster than persistent storage but is lost when the instance is terminated or fails
• Durable storage persists independently of the VM instance lifecycle and can be used for long-term data storage and recovery
• Durable storage options offer features like replication, snapshots, and backup capabilities to ensure data availability and durability

Snapshots and images of disks

• Snapshots are point-in-time copies of persistent disks that capture the disk's state and data
• Snapshots can be used for backup, recovery, and creating new disks with the same data
• Images are templates used to create new persistent disks with a specific configuration and data
• Custom images can be created from snapshots or existing disks to standardize disk provisioning and deployment

Managing virtual machines

• Effective management of virtual machines is essential for ensuring their availability, performance, and security
• VM management involves tasks such as starting, stopping, monitoring, updating, and backing up instances
• Cloud platforms provide tools and services to streamline VM management and automate common tasks

Starting and stopping VMs

• VMs can be started (provisioned) and stopped (deallocated) on-demand to control resource consumption and costs
• Starting a VM allocates the necessary compute, memory, and storage resources and boots the operating system
• Stopping a VM releases the compute and memory resources while preserving the attached storage and configuration
• Automated startup and shutdown schedules can be configured to optimize resource utilization and reduce costs during off-peak hours

Monitoring VM performance

• Monitoring VM performance is crucial for identifying bottlenecks, optimizing resource allocation, and ensuring application availability
• Cloud platforms offer native monitoring services that collect and visualize metrics such as CPU utilization, memory usage, disk I/O, and network traffic (Amazon CloudWatch, Azure Monitor)
• Custom metrics can be collected from applications running inside VMs using agents or APIs
• Alerts and notifications can be configured based on predefined thresholds to proactively detect and respond to performance issues

Updating and patching VMs

• Regular updates and patching of VM operating systems and installed software are essential for maintaining security and stability
• Cloud platforms provide tools for automating the update and patch management process (Amazon Systems Manager, Azure Update Management)
• Patch management involves identifying, downloading, and installing relevant security patches and software updates
• Update schedules can be customized to minimize disruption to application availability and align with maintenance windows

Backup and disaster recovery

• Backing up VM data and configurations is critical for protecting against data loss and ensuring business continuity
• Cloud platforms offer backup services that automate the process of creating and managing VM backups (Amazon Backup, Azure Backup)
• Backup policies define the frequency, retention period, and storage location for VM backups
• Disaster recovery strategies involve replicating VMs and data to secondary regions or data centers to enable rapid recovery in the event of a regional outage or disaster
• Disaster recovery plans should be regularly tested and updated to ensure their effectiveness and align with business requirements

Serverless vs virtual machines

• Serverless computing and virtual machines are two different approaches to deploying and running applications in the cloud
• Understanding the differences, trade-offs, and use cases for each approach is essential for designing efficient and cost-effective cloud architectures

Serverless computing paradigms

• Serverless computing abstracts away the underlying infrastructure management, allowing developers to focus on writing and deploying code
• Functions as a Service (FaaS): Execute individual functions in response to events or HTTP requests (AWS Lambda, Azure Functions)
• Serverless platforms automatically scale the execution environment based on the incoming workload and charge based on the actual consumption of resources
• Serverless architectures are well-suited for event-driven, highly scalable, and cost-sensitive workloads

Containers vs virtual machines

• Containers are lightweight, standalone executable packages that include an application and its dependencies
• Containers provide a consistent runtime environment across different platforms and enable fast deployment and scaling
• Virtual machines offer stronger isolation and compatibility by emulating a complete hardware environment
• Containers are more lightweight and efficient than VMs, as they share the host operating system kernel and resources
• Container orchestration platforms (Kubernetes, Docker Swarm) manage the deployment, scaling, and networking of containers across a cluster of VMs

Cost comparison of approaches

• Virtual machines are billed based on the provisioned resources (CPU, memory, storage) and the duration of their runtime, regardless of actual utilization
• Serverless platforms charge based on the actual execution time and resources consumed by the deployed functions
• Serverless can be more cost-effective for sporadic or bursty workloads, as there are no costs incurred during idle periods
• Virtual machines may be more cost-effective for steady-state, predictable workloads or when using reserved instances or spot instances

Use cases for VMs and serverless

• Virtual machines are suitable for:
  • Applications requiring full control over the operating system and runtime environment
  • Legacy applications that are not easily containerized or require specific hardware dependencies
  • Workloads with consistent resource requirements and long-running processes
• Serverless is suitable for:
  • Event-driven architectures and microservices
  • Rapid prototyping and iterative development
  • Workloads with unpredictable or highly variable traffic patterns
  • Applications with stateless processing and minimal runtime dependencies