Cloud computing concepts:

  1. Introduction to Cloud Computing
  • Definition and characteristics of cloud computing
    • Evolution and history of cloud computing
    • Benefits and challenges of cloud computing
  • Cloud Service Models
  • Infrastructure as a Service (IaaS)
    • Platform as a Service (PaaS)
    • Software as a Service (SaaS)
    • Function as a Service (FaaS)/Serverless Computing
  • Cloud Deployment Models
  • Public cloud
    • Private cloud
    • Hybrid cloud
    • Community cloud
  • Cloud Infrastructure Components
  • Virtualization
    • Hypervisors
    • Containers (e.g., Docker, Kubernetes)
    • Orchestration and management tools (e.g., Terraform, Ansible)
  • Cloud Providers and Services
  • Major cloud service providers (e.g., AWS, Azure, Google Cloud Platform)
    • Overview of core services offered by cloud providers (compute, storage, networking, databases, etc.)
    • Specialty services (AI/ML, IoT, big data, serverless, etc.)
  • Cloud Security
  • Shared responsibility model
    • Identity and Access Management (IAM)
    • Encryption and data protection
    • Compliance and governance
  • Networking in the Cloud
  • Virtual Private Cloud (VPC)
    • Subnets, routing tables, and security groups
    • Load balancing and auto-scaling
    • Content Delivery Networks (CDNs)
  • Storage in the Cloud
  • Object storage vs. block storage
    • Amazon S3, Azure Blob Storage, Google Cloud Storage
    • File storage solutions (Amazon EFS, Azure Files)
    • Database services (RDS, DynamoDB, Cosmos DB, etc.)
  • Compute Services
  • Virtual machines (EC2, Azure Virtual Machines, Google Compute Engine)
    • Serverless computing (AWS Lambda, Azure Functions, Google Cloud Functions)
    • Container services (Amazon ECS, Azure Kubernetes Service, Google Kubernetes Engine)
  1. Monitoring, Logging, and Analytics
  • Cloud monitoring tools (CloudWatch, Azure Monitor, Google Cloud Monitoring)
    • Logging services (CloudTrail, Azure Log Analytics, Google Cloud Logging)
    • Data analytics and visualization services (Amazon Redshift, Azure HDInsight, Google BigQuery)
  1. Cost Management and Optimization
  • Pricing models (on-demand, reserved instances, spot instances, etc.)
    • Cost estimation and budgeting
    • Strategies for optimizing cloud costs
  1. Migration to the Cloud
  • Assessing workloads for cloud migration
    • Lift-and-shift vs. re-architecture approaches
    • Tools and best practices for cloud migration
  1. DevOps and Continuous Integration/Continuous Deployment (CI/CD)
  • DevOps principles and practices in the cloud
    • CI/CD pipelines using cloud-native tools (AWS CodePipeline, Azure DevOps, Google Cloud Build)
  1. Serverless Computing and Microservices
  • Architectural patterns for building serverless applications
    • Benefits and challenges of microservices architecture
    • Managing microservices in the cloud environment
  1. Emerging Trends and Technologies
  • Edge computing
    • Multi-cloud and hybrid-cloud strategies
    • Quantum computing and its implications for the cloud
  1. Case Studies and Real-World Applications
  • Examining real-world examples of successful cloud implementations
    • Best practices and lessons learned from cloud adoption journeys
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