Cloud Computing Applications - Summary

Web Services: Amazon

  • Amazon Web Service Components and Services
  • Working with the Elastic Compute Cloud (EC2)
    • Virtual server platform to create and run virtual machines.
    • Launch and run Amazon Machine Images (AMIs) with different OS.
    • Add or subtract virtual servers; cluster, replicate, and load balance servers.
  • Working with Amazon Storage Systems
  • Understanding Amazon Database Services

Web Services: Microsoft

  • Exploring Microsoft Cloud Services
  • Defining Windows Azure Platform
  • Using Windows Live

Web Services: Google

  • Exploring Google Applications
    • Cloud-Based User Applications (SaaS)
      • Productivity Tools: Google Docs, Sheets, Slides
      • Communication Tools: Gmail, Google Meet, Hangouts
      • Media & Social Tools: YouTube, Google Photos, Blogger
      • Mapping & Exploration: Google Maps, Google Earth
      • Analytics & Tracking: Google Analytics
      • Advertising Systems: AdWords, AdSense
    • Platform as a Service (PaaS): Google App Engine (GAE)
      • Allows developers to build, deploy, and scale web applications.
      • Programming Support: Java, Python, Node.js, Go, PHP.
      • Auto-scaling and Load Balancing, Built-in Services.
  • Surveying the Google Application Portfolio
    • Indexed Search
      • Web Crawling: Automated programs gather information from web pages.
      • Indexing: Content is analyzed and stored in Google’s search index.
      • PageRank Algorithm: Assesses the importance of a webpage based on inbound links and other factors.
      • Search Engine Results Page (SERP): Displays links and snippets based on query and PageRank.
    • The dark Web
      • Intentionally hidden and anonymized part of the Deep Web, requiring special software to access.
    • Aggregation and disintermediation
      • Aggregation: Collecting and displaying information from multiple sources in a unified format.
      • Disintermediation: Elimination of intermediaries between producers and consumers.
    • Productivity applications and services
    • Enterprise offerings
    • AdWords
      • Operates on a pay-per-click (PPC) model.
      • Advertisers bid on keywords relevant to their products or services.
    • Google Analytics
      • Helps track and analyze visitor behavior.
    • Google Translate
      • AI-driven statistical and neural machine translation.
  • Exploring the Google Toolkit
    • Google has a number of areas in which it offers development services
  • Working with Google App Engine
    • Google App Engine (GAE) is a Platform as a Service (PaaS) cloud-based Web hosting service on Google’s infrastructure

Case Studies: Cloud as Infrastructure for an Internet Data Center (IDC)

  • Introduction: Internet Data Center (IDC)
    • A physical facility housing computer systems and associated components.
  • Cloud Computing as an IDC Backbone
    • Provides a virtualized and programmable environment.
  • Architecture of a Cloud-Enabled IDC
    • Layers: Application, Platform, Infrastructure (IaaS), Virtualization, Physical Hardware, Data Center Facilities
  • Benefits of Cloud in IDC Environments
    • Cost Efficiency, Agility, Fault Tolerance, Energy Optimization, Global Accessibility, Dynamic Resource Allocation
  • Cloud Deployment Models for IDC
    • Private, Public, Hybrid, Community
  • Technologies Used in Cloud-Based IDCs
    • Virtualization, Cloud Platforms, Containerization, Orchestration Tools, Monitoring, Storage Solutions
  • Challenges in Managing Cloud-Based IDCs
    • Security and Compliance, Latency and Bandwidth, Resource Overhead, Interoperability, Vendor Lock-in
  • Future Trends
    • Serverless Computing, AI-Optimized IDCs, Edge-Cloud Synergy, Green Data Centers

Cloud Computing for Software Parks

  • Introduction to Cloud Computing
    • Cloud Computing: A model for enabling ubiquitous, on-demand access to shared computing resources.
    • NIST Definition: Cloud computing has 5 essential characteristics: on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service.
  • Role of Cloud Computing in Software Parks
    • Software parks are technology infrastructure zones that house multiple IT/ITES companies.
  • Cloud Infrastructure for Software Parks
    • Key Components: Virtualization Platforms, Data Centers, Containers & Orchestration.
  • Security, Compliance, and Governance
    • Security Strategies: Identity and Access Management (IAM), Encryption, Virtual firewalls and VPNs.
    • Cloud Compliance Standards: ISO 27001, SOC 2, GDPR/DPDP.
  • Cloud Business Models for Software Parks
    • CapEx vs. OpEx: Traditional IT uses Capital expenditure (CapEx), Cloud model uses operating expense (OpEx).
  • Advanced Use Cases in Software Parks
    • Smart Park Applications: Digital Twin, IoT, Edge computing.
  • Government and Industry Initiatives
    • India’s Cloud Push: MeghRaj (GI Cloud), STPI Cloud CoE.

Enterprise with Multiple Data Centers

  • An enterprise with multiple data centers operates more than one physical or virtual facility for hosting its IT infrastructure.
  • Why Enterprises Use Multiple Data Centers
    • High Availability, Disaster Recovery (DR), Latency Optimization, Load Distribution, Compliance & Data Sovereignty
  • Architecture of Multi-Data Center Enterprises
    • Components: Primary, Secondary/Backup, Edge/Regional, Cloud
  • Technologies Enabling Multi-DC Operations
    • Load Balancers, DNS-Based Traffic Routing, Data Replication Tools, SD-WAN, Virtualization & Containers, Hybrid Cloud Integrations
  • Deployment Strategies
    • Active-Active, Active-Passive, Geo-Redundancy
  • Challenges in Managing Multiple Data Centers
    • Data Consistency, Failover Management, Latency & Network Bottlenecks, Monitoring Complexity, Cost Overheads
  • Best Practices
    • Use Infrastructure-as-Code (IaC), Implement Data Tiering, Design with RTO/RPO targets, Monitor using unified platforms.