Chapter 6 Cloud Service Providers - Cloud Computing.pptx

Cloud Computing

1. Course: CSC1205 - Cloud Computing for Big Data Analytics Semester: January 2024 Lecturer: Ms Jayashiry Morgan

2. Recap: Concept of cloud management platforms Tools employed in cloud management Cloud management practices through real-world examples

3. Chapter 6: Cloud Service Providers

4. Learning Outcomes By the end of this session, students are able to: Understand the key features and differentiators of the three leading cloud providers: AWS, GCP, and Azure. Gain insights into their respective strengths and weaknesses to inform informed cloud provider selection. Explore real-world applications of these platforms across various industries.

5. Introduction – Cloud Ecosystem The ecosystem of cloud computing does not differ much from its meaning. The common components are hardware, software, and tag-along elements like cloud vendors, customers, partners, etc. Today with the help of cloud computing, businesses can reach out to cloud vendors and avail different products, run applications on their infrastructure, and store immense information. They have been able to answer their changing needs and cater to customers in a more refined manner.

6. Introduction – Cloud Ecosystem Devices with sensing system Connectivity Cloud Analytics End Users

7. Introduction – Cloud Provider Landscape There are THREE major cloud providers: Amazon Web Services (AWS): A cloud computing platform provided by Amazon. It is one of the largest and most widely adopted cloud service providers globally. Key Services: Compute: Offers a range of computing services, including Amazon EC2 (virtual servers) and AWS Lambda (serverless computing). Storage: Provides scalable and durable storage solutions such as Amazon S3 (object storage) and Amazon EBS (block storage).

8. Introduction – Cloud Provider Landscape Databases: Offers managed database services like Amazon RDS and Amazon DynamoDB. Networking: Includes services like Amazon VPC (Virtual Private Cloud) and AWS Direct Connect. AI/ML: Features services like Amazon SageMaker for machine learning. Development Tools: Provides services like AWS CodeDeploy and AWS CodePipeline for application development and deployment. Specialization: AWS is well-suited for a wide range of use cases, from hosting simple websites to running complex, high-performance computing (HPC) workloads. It is commonly chosen for its scalability, reliability, and extensive service catalog.

9. Introduction – Cloud Provider Landscape 2. Microsoft Azure: Azure is Microsoft's cloud computing platform, offering a wide range of services and tools for building, deploying, and managing applications through a global network of data centers. Key Services: Compute: Offers virtual machines (Azure VMs) and Azure Functions (serverless computing). Storage: Provides solutions like Azure Blob Storage and Azure Table Storage. Databases: Includes Azure SQL Database and Cosmos DB (a globally distributed database).

10. Introduction – Cloud Provider Landscape Networking: Features Azure Virtual Network and Azure ExpressRoute. AI/ML: Azure provides services like Azure Machine Learning and Azure Cognitive Services. Development Tools: Azure DevOps and Visual Studio are part of the comprehensive toolset. Specialization: Azure is often chosen by enterprises that rely heavily on Microsoft technologies. It's suitable for a variety of workloads, including application development, data storage and analysis, artificial intelligence (AI), and Internet of Things (IoT) solutions.

11. Introduction – Cloud Provider Landscape 3. Google Cloud Platform (GCP): GCP is Google's cloud computing offering, providing a suite of cloud services, storage, machine learning, and data analytics. Key Services: Compute: Includes Google Compute Engine (virtual machines) and Google Cloud Functions. Storage: Offers Google Cloud Storage and Cloud Filestore . Databases: Features Cloud SQL and Cloud Spanner (a globally distributed, horizontally scalable database).

12. Introduction – Cloud Provider Landscape Networking: Google Virtual Private Cloud and Cloud Load Balancing are part of the networking services. AI/ML: Google Cloud AI Platform and TensorFlow are prominent services. Development Tools: Google Cloud SDK and Cloud Source Repositories support development and deployment. Specialization: GCP is often selected for data-intensive applications, machine learning projects, and organizations heavily invested in containerized applications. It is also suitable for developers who appreciate a strong commitment to open-source technologies.

13. Introduction – Cloud Provider Landscape Several other cloud service providers: 1. IBM Cloud: IBM Cloud provides a range of cloud computing services, including IaaS, PaaS, and SaaS solutions. Key Services: Compute: IBM Virtual Servers and IBM Kubernetes Service for container orchestration. Storage: Object Storage and Block Storage services. Databases: Db2 on Cloud and IBM Cloud Databases. Networking: Virtual Private Cloud and Direct Link for secure connectivity.

14. Introduction – Cloud Provider Landscape AI/ML: Watson Studio and Watson Machine Learning. Development Tools: IBM Cloud Pak for Applications and IBM Cloud Continuous Delivery. Specialization: IBM Cloud is often chosen by enterprises with complex and mission-critical workloads. It is suitable for industries such as finance, healthcare, and government that have stringent regulatory and compliance requirements.

15. Introduction – Cloud Provider Landscape Several other cloud service providers: 2. Oracle Cloud: Oracle Cloud is the cloud computing arm of Oracle Corporation, a leading provider of database management systems and enterprise software. Key Services: Compute: Oracle Compute Service for virtual machines. Storage: Oracle Cloud Infrastructure Object Storage and Block Volumes. Databases: Oracle Database Cloud Service and Oracle Autonomous Database. Networking: Oracle Virtual Cloud Network and FastConnect .

16. Introduction – Cloud Provider Landscape AI/ML: Oracle AI Platform Cloud Service. Development Tools: Oracle Developer Cloud Service and Oracle Cloud Infrastructure Registry. Specializations: Oracle Cloud is recognized for its strong focus on enterprise solutions, especially in databases and applications. It offers a comprehensive suite of cloud services designed for mission-critical workloads and applications.

17. Introduction – Cloud Provider Landscape Several other cloud service providers: 3. Alibaba Cloud: Alibaba Cloud, also known as Aliyun , is the cloud computing arm of Alibaba Group, one of the largest e-commerce and technology companies in the world. Key Services: Compute: Elastic Compute Service (ECS) for scalable virtual servers. Storage: Object Storage Service (OSS) and Alibaba Cloud Disk. Databases: Alibaba Cloud ApsaraDB for databases. Networking: Virtual Private Cloud (VPC) and Global Accelerator.

18. Introduction – Cloud Provider Landscape AI/ML: Alibaba Cloud Machine Learning Platform for AI (PAI). Development Tools: Alibaba Cloud SDK and Alibaba Cloud Toolkit. Specializations: Alibaba Cloud is known for its strong presence in the Asia-Pacific region and offers a wide range of services, including unique offerings like ApsaraDB for PolarDB and MaxCompute for big data processing.

19. ACTIVITY 1: CLOUD PROVIDER DEEP DIVE

20. AMAZON WEB SERVICE (AWS) Strengths: Most extensive service offerings: Briefly list key categories like compute, storage, databases, and analytics. Emphasize the vastness of options. Scalability and flexibility: Briefly explain the ability to scale resources up or down quickly. Robust security and compliance: Briefly mention meeting stringent security requirements for diverse industries. Weaknesses: Complexity: Briefly mention the vastness of options could be overwhelming for beginners. Pricing: Briefly mention potentially higher costs compared to specific competitors. Real-World Example : Netflix utilizes AWS for its global content delivery network (CDN).

21. GOOGLE CLOUD PLATFORM (GCP) Strengths: Data analytics and machine learning: Briefly highlight their powerful tools and services for data processing and AI development. Competitive pricing: Briefly mention potentially lower costs than AWS for specific services. Developer-friendly: Briefly mention developer-friendly tools and open-source technologies. Weaknesses: Limited service offerings compared to AWS: Briefly mention the smaller selection compared to AWS. Smaller market share: Briefly mention potentially fewer available resources and expertise. Real-World Example : Spotify utilizes GCP for its data processing and analytics.

22. MICROSOFT AZURE Strengths: Integration with Microsoft products: Briefly mention seamless integration with existing Microsoft products like Office 365 and Active Directory. Security and compliance: Briefly mention the focus on enterprise-grade security and compliance features. Comprehensive suite of solutions: Briefly mention a wide range of services for various needs. Weaknesses: Vendor lock-in: Briefly mention potential challenges of switching providers due to integration with Microsoft products. Limited open-source support: Briefly mention the primary focus on Microsoft-specific technologies. Real-World Example : Xbox Live is powered by Microsoft Azure for online gaming.

23. KEY COMPARISONS:

24. ACTIVITY 2 – CHOOSING RIGHT CLOUD PROVIDER Facilitate a class discussion by posing questions like: What factors would be most important when choosing a cloud provider for a specific project? How can these strengths and weaknesses be weighed against each other in decision-making? Can you share any personal experiences or industry insights related to cloud provider selection?

25. ANSWER Factors to consider: Service offerings: Ensure the provider offers the specific services you require. Scalability: Choose a platform that can scale up or down as your needs evolve. Pricing: Compare pricing models and choose the one that aligns with your budget and usage patterns. Security: Evaluate the provider's security practices and compliance certifications. Vendor lock-in: Consider the potential challenges of switching providers in the future. Existing infrastructure: Consider potential synergies with existing infrastructure and tools.

26. ANSWER Recommendations: Startups and small businesses: GCP or Azure can offer good value propositions with their developer-friendly tools and competitive pricing. Large enterprises: AWS may be a suitable choice due to its extensive service offerings and enterprise-grade features. Organizations heavily invested in Microsoft solutions: Azure provides seamless integration and leverages existing expertise.

27. ACTIVITY 3 – CASE STUDY ANALYSIS The case study: Chapter 6_Activity 3_Case Study_QP.docx Method: Individual work and use Ms Word to prepare your answer

28. How to answer: For handling increased data storage needs and frequent app updates, all three CSPs offer scalable storage solutions such as Amazon S3 in AWS, Azure Blob Storage in Microsoft Azure, and Google Cloud Storage in GCP. These solutions allow FitLife to dynamically adjust storage capacity based on demand, ensuring they have sufficient resources during new product launches and marketing campaigns. For ensuring smooth and responsive mobile app performance, FitLife can leverage the global infrastructure of all three CSPs to distribute their app backend across different regions closer to their users. AWS offers AWS Global Accelerator, Azure provides Azure CDN (Content Delivery Network), and GCP offers Cloud CDN. These services help reduce latency and improve app responsiveness by delivering content from edge locations closer to users worldwide. To address high costs associated with managing on-site technology, FitLife can benefit from the cost-effective pricing models offered by each CSP. AWS offers pay-as-you-go pricing with no upfront costs, Azure provides options like Reserved Virtual Machine Instances for long-term commitments, and GCP offers sustained use discounts for continuous usage. FitLife can analyze their usage patterns and choose the pricing model that best aligns with their budget and scalability requirements.