Introduction to Cloud Services: AWS, Azure, and Google Cloud

Duration: Hours

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    Training Mode: Online

    Description

    Training Introduction:

    This course offers a comprehensive introduction to the three leading cloud service providers: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Participants will gain a fundamental understanding of the core services, features, and pricing models offered by each platform. The course will compare and contrast the strengths of these cloud platforms, enabling learners to make informed decisions on which cloud service to use for various business needs. By the end of the course, participants will have a clear understanding of the cloud service landscape and the foundational knowledge required to start working with AWS, Azure, and Google Cloud.

    Prerequisites:

    • Basic IT Knowledge: Participants should have a basic understanding of IT concepts, such as networking, databases, and virtualization.
    • Understanding of Cloud Computing Fundamentals: Familiarity with basic cloud computing concepts and models (such as IaaS, PaaS, and SaaS) is recommended.
    • Basic Understanding of the Internet: Knowledge of how the internet works, including concepts like web servers and client-server architecture.

    Table of Content:

    1. Introduction to Cloud Computing Services

    1.1 Overview of Cloud Computing
    1.2 Importance of Cloud Services in Modern IT
    1.3 Introduction to AWS, Azure, and Google Cloud
    1.4 Storage: S3, Elastic Block Store (EBS)
    1.5 Databases: RDS, DynamoDB
    1.6 Networking: VPC, Route 53

    2. Amazon Web Services (AWS)

    2.1 Core Services and Features
    2.2 Compute: EC2, Lambda
    2.3 Security and Compliance
    2.4 AWS Pricing Models and Cost Management
    2.5 Hands-On: Setting Up an AWS Account and Launching an EC2 Instance
    2.6 Storage: Blob Storage, Azure Files
    2.7 Databases: SQL Database, Cosmos DB
    2.8 Networking: Virtual Network, Load Balancer

    3. Microsoft Azure

    3.1 Core Services and Features
    3.2 Compute: Virtual Machines, Azure Functions
    3.3 Security and Compliance
    3.4 Azure Pricing Models and Cost Management
    3.5 Hands-On: Setting Up an Azure Account and Launching a Virtual Machine
    3.6 Storage: Cloud Storage, Persistent Disks
    3.7 Databases: Cloud SQL, BigQuery
    3.8 Networking: VPC, Cloud Load Balancing

    4. Google Cloud Platform (GCP)

    4.1 Core Services and Features
    4.2 Compute: Compute Engine, Cloud Functions
    4.3 Security and Compliance
    4.4 GCP Pricing Models and Cost Management
    4.5 Hands-On: Setting Up a GCP Account and Launching a Compute Engine Instance

    5. Comparing AWS, Azure, and Google Cloud

    5.1 Strengths and Weaknesses of Each Platform
    5.2 Service Comparison: Compute, Storage, Databases, Networking
    5.3 Pricing Comparison and Cost Optimization Strategies
    5.4 Case Studies of Multi-Cloud and Hybrid Cloud Deployments

    6. Managing Cloud Services

    6.1 Monitoring and Logging Services
    6.2 AWS CloudWatch, Azure Monitor, Google Cloud Monitoring
    6.3 Automation and Orchestration
    6.4 AWS CloudFormation, Azure Resource Manager, Google Cloud Deployment Manager
    6.5 Identity and Access Management (IAM) Across Platforms

    7. Security and Compliance in the Cloud

    7.1 Overview of Cloud Security Best Practices
    7.2 Identity and Access Management (IAM) in AWS, Azure, and Google Cloud
    7.3 Compliance Standards and Certifications
    7.4 Implementing Security Policies and Procedures

    8. Introduction to Cloud DevOps

    8.1 Overview of DevOps in the Cloud(Ref: DevOps and Working with Microsoft Azure Security Center)
    8.2 Tools and Services for CI/CD
    8.3 AWS CodePipeline, Azure DevOps, Google Cloud Build
    8.4 Infrastructure as Code (IaC) Concepts
    8.5 Terraform, AWS CloudFormation, Azure ARM Templates

    9. Case Studies and Real-World Applications

    9.1 Case Study 1: Migrating a Legacy Application to AWS
    9.2 Case Study 2: Implementing a Multi-Cloud Strategy
    9.3 Case Study 3: Using Google Cloud for Big Data and Machine Learning

    10. Hands-On Labs and Exercises

    10.1 Deploying a Simple Web Application on AWS, Azure, and Google Cloud
    10.2 Setting Up Cloud Storage Solutions Across Platforms
    10.3 Implementing Basic Security Measures in AWS, Azure, and GCP

    11. Future Trends in Cloud Services

    11.1 Emerging Technologies in Cloud Computing
    11.2 The Role of AI and Machine Learning in Cloud Services
    11.3 The Future of Multi-Cloud and Hybrid Cloud Environments

    12. Conclusion and Next Steps

    12.1 Recap of Key Concepts
    12.2 Exploring Advanced Cloud Services and Specializations
    12.3 Resources for Further Learning and Certification Paths

    Conclusion

    Understanding the offerings of AWS, Azure, and Google Cloud is crucial for developing a successful cloud strategy. Each platform has unique strengths that cater to different business needs, making it essential to evaluate them carefully. Equip yourself with the knowledge to leverage these cloud services effectively and drive innovation in your organization.

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