Key Cloud and Virtualization Terms for Prelims

Cloud computing and virtualization are closely linked concepts that appear frequently in Prelims. Virtualization creates simulated computing environments, while cloud computing uses those virtualized resources to deliver services over the internet.

Fundamental Virtualization Concepts

Virtualization is the core enabling technology that abstracts physical hardware and allows multiple digital environments to run on a single computer or server.

• Hypervisor (Virtual Machine Monitor): Firmware or software that creates and runs virtual machines by isolating operating systems from physical hardware.
• Type-1 (Bare-Metal) Hypervisor: Runs directly on host hardware without an underlying host operating system.
• Type-2 (Hosted) Hypervisor: Runs inside a conventional host operating system like a standard application.
• Examples of Type-1: VMware ESXi, Microsoft Hyper-V, and KVM.
• Examples of Type-2: Oracle VM VirtualBox and VMware Workstation.
• Virtual Machine (VM): Virtualizes the entire physical hardware stack and runs a complete guest operating system with its own kernel.
• Containers: Virtualize at the operating system level, sharing the host operating system kernel while isolating user spaces.
• Key difference: Containers are lightweight, start in seconds, and require fewer system resources than virtual machines.

Containers, Docker and Kubernetes

• Docker: An open-source platform that packages applications and dependencies into standardized containers.
• Kubernetes: An open-source orchestration tool used to automate container deployment, scaling, and operational management.
• Why containers matter: They are faster to deploy and easier to scale than full virtual machines.
• Why Kubernetes matters: It helps manage large numbers of containers across systems.

Cloud Computing Service Models

Cloud computing is the on-demand delivery of computing services such as servers, storage, databases, networking, and software over the internet. It is usually delivered on a metered pay-per-use basis.

• Infrastructure as a Service (IaaS): Provides raw computing infrastructure such as physical or virtual servers, network bandwidth, and data storage.
• IaaS responsibility split: The provider manages physical hardware, while the client configures operating systems, runtimes, middleware, and applications.
• IaaS examples: Amazon Web Services EC2, Microsoft Azure Virtual Machines, and Google Compute Engine.
• Platform as a Service (PaaS): Provides a managed hardware and software environment for developers to build, run, and manage applications without maintaining backend infrastructure.
• PaaS examples: Google App Engine, AWS Elastic Beanstalk, and Heroku.
• Software as a Service (SaaS): Delivers fully managed, ready-to-use software applications over a web browser.
• SaaS responsibility split: The service provider handles hardware, hosting, updates, and maintenance.
• SaaS examples: Google Workspace, Microsoft 365, and Salesforce.
• Function as a Service (FaaS) or Serverless: Executes modular code snippets in response to specific triggers without requiring provisioned or managed server instances.
• FaaS examples: AWS Lambda, Google Cloud Functions, and Azure Functions.

Cloud Deployment Models

• Public Cloud: Infrastructure owned and operated by a third-party cloud service provider and shared among multiple tenants over the public internet.
• Private Cloud: Computing infrastructure dedicated exclusively to a single business entity, hosted on-premises or in an isolated third-party data center.
• Hybrid Cloud: Combines private and public cloud environments linked by proprietary or open technology to allow data and application movement between them.
• Community Cloud: Infrastructure shared by several organizations with shared concerns like regulatory compliance, security policies, or functional missions.
• Multi-Cloud: A strategy involving the simultaneous use of cloud services from multiple independent public cloud vendors to prevent vendor lock-in.
• Vendor lock-in: A dependency situation where a customer cannot easily transition away from a specific vendor due to proprietary formats or non-standard configurations.

Edge, Fog, Grid and Quantum Cloud Computing

• Edge Computing: Processes data near the physical source or user device rather than in a distant centralized data center.
• Benefit of edge computing: Minimizes bandwidth costs and decreases operational latency for time-critical systems.
• Fog Computing: Extends cloud computing by placing intermediate processing nodes between edge sensors and central data centers.
• Fog computing benefit: Enhances local compute efficiency, data filtering, and device coordination.
• Grid Computing: Connects geographically dispersed, heterogeneous computers to work concurrently on large computing jobs.
• Grid computing benefit: Pools vast computing capacity for large academic, scientific, or mathematical simulations.
• Quantum Cloud Computing: Delivers remote access to quantum processing units through standard cloud interfaces.
• Quantum cloud benefit: Allows researchers to run quantum algorithms on physical quantum hardware without local ownership.

India’s Sovereign and Public Cloud Initiatives

• GI Cloud (MeghRaj): The national cloud initiative initiated by the Ministry of Electronics and Information Technology (MeitY).
• Purpose of MeghRaj: It optimizes information and communication technology spending of government departments by providing standardized infrastructure, platform, and software environments.
• NIC role: The National Informatics Centre operates the National Cloud Data Centres under this framework.
• OpenForge Platform: The Government of India’s collaborative platform for open-source development of e-governance software applications.
• OpenForge purpose: It promotes reuse of public software code to minimize duplicate software development costs across Union and state ministries.
• Data Centre Policy: Designed by MeitY to designate data centres under the Essential Services Maintenance Act (ESMA).
• Data Centre Economic Zones: The policy creates such zones with uninterrupted power supply, optical fiber corridors, and green energy incentives.

Key Prelims Takeaways

• Virtualization vs cloud: Virtualization creates simulated environments; cloud computing delivers pooled virtualized resources over the internet.
• Type-1 hypervisor: Runs directly on hardware and does not need a host operating system.
• Containers: Share the host kernel, so they are smaller and faster to boot than virtual machines.
• Kubernetes: Used for container orchestration and is maintained by the Cloud Native Computing Foundation (CNCF).
• Serverless/FaaS: Charges users mainly for the exact execution time of code blocks.
• Edge computing: Reduces latency by processing data close to the source.
• MeghRaj: The Government of India’s GI Cloud initiative under MeitY.