Cloud Computing Architecture and Management

Cloud architecture, Layer
Anatomy of the Cloud
Network Connectivity in Cloud Computing
Applications on the Cloud
Managing the Cloud
Managing the Cloud Infrastructure Managing the Cloud application
Migrating Application to Cloud
Phases of Cloud Migration Approaches for Cloud Migration

1. CLOUD COMPUTING (4 Year – 1 Sem) Prepared By Dr. B.Rajalingam Associate Professor & HOD Department of Artificial Intelligence and Data Science (AI&DS) St. Martin’s Engineering College

2. Unit-1 : Computing Paradigms High-Performance Computing Parallel Computing Distributed Computing Cluster Computing Grid Computing Cloud Computing Bio computing Mobile Computing Quantum Computing Optical Computing Nano computing CC(Unit 3): Dr. B.Rajalingam 2

3. Unit-2: Cloud Computing Fundamentals Motivation for Cloud Computing The Need for Cloud Computing Defining Cloud Computing Definition of Cloud computing Cloud Computing Is a Service Cloud Computing Is a Platform Principles of Cloud computing Five Essential Characteristics Four Cloud Deployment Models CC(Unit 3): Dr. B.Rajalingam 3

4. Unit-3: Cloud Computing Architecture and Management Cloud architecture, Layer Anatomy of the Cloud Network Connectivity in Cloud Computing Applications on the Cloud Managing the Cloud Managing the Cloud Infrastructure Managing the Cloud application Migrating Application to Cloud Phases of Cloud Migration Approaches for Cloud Migration CC(Unit 3): Dr. B.Rajalingam 4

5. Unit-4: Cloud Service Models Infrastructure as a Service: Characteristics of IaaS Suitability of IaaS Pros and Cons of IaaS Summary of IaaS Providers Platform as a Service: Characteristics of PaaS Suitability of PaaS Pros and Cons of PaaS Summary of PaaS Providers Software as a Service: Characteristics of SaaS Suitability of SaaS Pros and Cons of SaaS Summary of SaaS Providers Other Cloud Service Models CC(Unit 3): Dr. B.Rajalingam 5

6. Unit-5: Cloud Service Providers EMC: EMC IT Captiva Cloud Toolkit Google: Cloud Platform Cloud Storage Google Cloud Connect Google Cloud Print Google App Engine Amazon Web Services: Amazon Elastic Compute Cloud Amazon Simple Storage Service Amazon Simple Queue Service Microsoft: Windows Azure Microsoft Assessment and Planning Toolkit SharePoint, IBM: Cloud Models IBM Smart Cloud SAP Labs: SAP HANA Cloud Platform, Virtualization Services Provided by SAP Sales force: Sales Cloud Service Cloud: Knowledge as a Service Rack space VMware, Manjra soft, Aneka Platform CC(Unit 3): Dr. B.Rajalingam 6

7. UNIT 3 Cloud Computing Architecture and Management CC(Unit 3): Dr. B.Rajalingam 7

8. Cloud Computing Architecture and Management Cloud architecture, Layer Anatomy of the Cloud Network Connectivity in Cloud Computing Applications on the Cloud Managing the Cloud Managing the Cloud Infrastructure Managing the Cloud application Migrating Application to Cloud Phases of Cloud Migration Approaches for Cloud Migration CC(Unit 3): Dr. B.Rajalingam 8

9. Cloud architecture and Layer CC(Unit 3): Dr. B.Rajalingam 9 Cloud architecture can be visualized as a multi-layered structure, where each layer provides specific services or capabilities. These layers work together to deliver cloud computing functionalities such as storage, networking, and application services. Here’s a breakdown of the Cloud Architecture Layers: 1. Physical Layer (Infrastructure Layer) 2. Virtualization Layer 3. Infrastructure Layer (IaaS – Infrastructure as a Service) 4. Platform Layer (PaaS – Platform as a Service) 5. Application Layer (SaaS – Software as a Service) 6. Service Management Layer 7. Security Layer 8. Orchestration and Management Layer

10. 1. Physical Layer (Infrastructure Layer) CC(Unit 3): Dr. B.Rajalingam 10 The physical layer consists of the physical components of cloud infrastructure, including data centers , servers, network devices, and storage systems. These are the foundational hardware resources required to deliver cloud services. Key Elements : Data centers housing servers and storage devices. Networking equipment (routers, switches, etc.). Power, cooling, and security systems for hardware.

11. 2. Virtualization Layer CC(Unit 3): Dr. B.Rajalingam 11 Virtualization abstracts the physical hardware, allowing for the creation of virtual machines (VMs) and virtualized resources such as storage and networking. This enables the efficient utilization of hardware and the flexibility of allocating resources dynamically. Key Elements : Hypervisors : Software that manages and creates virtual machines (e.g., VMware ESXi , KVM, Hyper-V). Containers : Lightweight virtualization solutions for isolating applications (e.g., Docker, Kubernetes). Virtual Networks : Network overlays providing communication between virtual instances. Virtualization makes cloud computing possible by enabling multi-tenancy and resource pooling.

12. 3. Infrastructure Layer (IaaS – Infrastructure as a Service) CC(Unit 3): Dr. B.Rajalingam 12 The infrastructure layer provides virtualized computing resources over the internet. Users can access processing power, storage, and networking resources without needing to manage the underlying physical hardware. Key Elements : Compute : Virtual machines (VMs) or instances (e.g., AWS EC2, Google Compute Engine). Storage : Virtual storage services (e.g., Amazon S3, Google Cloud Storage). Networking : Virtual networks, load balancers, and firewalls. Function : The infrastructure layer allows users to deploy and manage virtualized servers and storage, offering flexibility and scalability for businesses.

13. 4. Platform Layer (PaaS – Platform as a Service) CC(Unit 3): Dr. B.Rajalingam 13 The platform layer provides development and deployment environments that abstract the underlying infrastructure. Developers can focus on building and running applications without worrying about infrastructure management. Key Elements : Application Development : Tools and environments for building applications (e.g., Google App Engine, AWS Elastic Beanstalk, Azure App Services). Database Services : Managed databases (e.g., AWS RDS, Google Cloud SQL). Middleware : Services such as messaging, APIs, and integrations that connect various components. This layer simplifies the development process by managing infrastructure, offering development frameworks, and handling operating systems, middleware, and runtime environments.

14. 5. Application Layer (SaaS – Software as a Service) CC(Unit 3): Dr. B.Rajalingam 14 The application layer provides end-user applications delivered over the internet. These applications are fully managed by the service provider, and users can access them through a web browser or API. Key Elements : Business Applications : Software for various business functions (e.g., Salesforce, Microsoft Office 365, Google Workspace). Collaboration Tools : Online productivity and collaboration software (e.g., Slack, Zoom). Customer Relationship Management (CRM) : Services to manage customer interactions and sales (e.g., HubSpot, Zoho CRM). The application layer provides ready-to-use applications without requiring users to manage infrastructure or platforms.

15. 6. Service Management Layer CC(Unit 3): Dr. B.Rajalingam 15 This layer handles the management, monitoring, and optimization of cloud resources and services. It ensures that cloud services are running efficiently and securely. Key Elements : Monitoring Tools : Services that track performance, health, and usage of cloud resources (e.g., AWS CloudWatch, Azure Monitor). Automation Tools : Tools that automate deployment, scaling, and configuration (e.g., Terraform, Ansible). Security and Compliance Tools : Services that manage identity, access, and encryption (e.g., AWS IAM, Azure Security Center ). This layer is responsible for overseeing and managing the entire cloud infrastructure and services, ensuring performance, cost efficiency, and security compliance.

16. 7. Security Layer CC(Unit 3): Dr. B.Rajalingam 16 The security layer ensures that the cloud environment is protected against unauthorized access, data breaches, and other security threats. It spans all other layers to provide comprehensive protection. Key Elements : Identity and Access Management (IAM) : Control over who can access what in the cloud environment (e.g., AWS IAM, Azure Active Directory). Data Encryption : Encryption for data at rest and in transit (e.g., SSL/TLS, AES encryption). Firewalls and Security Groups : Configurations to restrict unauthorized access (e.g., AWS Security Groups, Azure Firewalls). The security layer ensures that cloud resources, applications, and data are secure, providing compliance with industry standards.

17. 8. Orchestration and Management Layer CC(Unit 3): Dr. B.Rajalingam 17 This layer manages the automated coordination, configuration, and scaling of cloud resources. It ensures that resources are dynamically allocated and deallocated based on demand. Key Elements : Orchestration Engines : Tools to automate the deployment and scaling of resources (e.g., Kubernetes, AWS CloudFormation). Auto-scaling : Automatically adjusting resources based on current loads (e.g., AWS Auto Scaling, Google Cloud Autoscaler ). Service Discovery : Dynamically identifying services and resources in the cloud environment (e.g., AWS Route 53, Consul). This layer enables the efficient allocation of resources and ensures that cloud services can scale up or down according to real-time needs.

18. Summary of Cloud Architecture Layers CC(Unit 3): Dr. B.Rajalingam 18 Physical Layer : Physical hardware like servers and networking. Virtualization Layer : Virtual machines and containers. Infrastructure Layer (IaaS) : Virtualized computing, storage, and networking. Platform Layer (PaaS) : Development and deployment platforms. Application Layer (SaaS) : End-user applications over the cloud. Service Management Layer : Tools for monitoring and managing resources. Security Layer : Protects cloud infrastructure and data. Orchestration and Management Layer : Automated resource management and scaling.

19. Anatomy of the Cloud CC(Unit 3): Dr. B.Rajalingam 19 The anatomy of the cloud refers to the essential components and structure of cloud computing. It encompasses the architecture, operational elements, and key technologies that form the backbone of cloud services. Here's a breakdown of the critical elements that make up the cloud: 1. Core Components of the Cloud a. Front-End (Client-Side) User Interfaces and Clients : This is what end-users interact with when accessing cloud services. It could be: Web browsers (e.g., Chrome, Firefox) for accessing applications. Mobile apps that interact with cloud services (e.g., Google Drive app). APIs (Application Programming Interfaces) that developers use to interface with cloud services programmatically. Devices : Desktops, laptops, tablets, smartphones, and other IoT devices that access cloud services via the internet.

20. b. Back-End (Cloud Infrastructure) CC(Unit 3): Dr. B.Rajalingam 20 Data Centers : Physical facilities with servers, storage systems, and networking devices. These are spread across different geographical regions for redundancy and performance optimization. Servers and Compute Resources : The physical or virtual machines (VMs) that provide processing power and computational capabilities for cloud applications. Storage : Massive, scalable storage systems that store data in the cloud. This includes object storage (e.g., Amazon S3), block storage (e.g., AWS EBS), and file storage services. Networking : Virtual and physical networking elements that connect the cloud infrastructure to the internet and within data centers , including routers, switches, firewalls, and load balancers.

21. 2. Cloud Service Models CC(Unit 3): Dr. B.Rajalingam 21 Cloud computing is typically offered in three main service models, each providing different levels of abstraction and control over the infrastructure: a. Infrastructure as a Service (IaaS) Provides virtualized computing resources over the internet, such as virtual machines, storage, and networks. Examples : Amazon EC2, Microsoft Azure VMs, Google Compute Engine. User Responsibility : Users manage applications, data, and sometimes the operating system, but not the underlying physical infrastructure. b. Platform as a Service (PaaS) Provides a platform allowing users to develop, run, and manage applications without the complexity of building and maintaining the underlying infrastructure. Examples : Google App Engine, Microsoft Azure App Service, Heroku. User Responsibility : Users focus on application development while the platform handles everything else (e.g., OS management, runtime). c. Software as a Service (SaaS) Offers fully developed applications over the internet, which are managed and maintained by the service provider. Examples : Salesforce, Google Workspace, Microsoft Office 365. User Responsibility : Users interact with the software but do not manage the underlying infrastructure or platform.

22. 3. Cloud Deployment Models CC(Unit 3): Dr. B.Rajalingam 22 There are different cloud deployment models based on who controls and manages the cloud infrastructure: a. Public Cloud Operated by third-party providers (e.g., AWS, Google Cloud, Microsoft Azure) and made available to the general public. Features : Shared infrastructure, scalable, cost-effective, but less control over security and compliance compared to private clouds. b. Private Cloud Cloud infrastructure is used exclusively by a single organization. It can be hosted on-premises or by a third-party provider. Features : Greater control over security, compliance, and customization, but typically more expensive than public cloud. c. Hybrid Cloud Combines both public and private clouds, allowing data and applications to be shared between them. Features : Flexibility to keep sensitive data in a private cloud while leveraging public cloud resources for less critical applications or peak workloads. d. Multi-Cloud Use of multiple cloud services from different providers to avoid vendor lock-in and provide redundancy. Features : Optimized for cost and performance, but can be complex to manage.

23. 4. Key Technologies and Concepts CC(Unit 3): Dr. B.Rajalingam 23 a. Virtualization Virtualization is the technology that allows for the creation of virtual machines (VMs) and containers by abstracting physical resources. Hypervisors : Software that enables virtualization (e.g., VMware, KVM, Hyper-V). Containers : Lightweight virtualization that packages applications with all their dependencies (e.g., Docker, Kubernetes). b. Microservices Architecture Microservices architecture breaks down applications into small, independent services that can be deployed and scaled separately. Benefits : Scalability, agility, and resilience. Examples : Services like Netflix or Amazon are built using microservices. c. Serverless Computing Serverless computing abstracts server management entirely, allowing developers to focus on building applications without provisioning or managing infrastructure. Examples : AWS Lambda, Google Cloud Functions, Azure Functions. Function : Resources are automatically allocated when needed and scaled dynamically based on workload. d. APIs (Application Programming Interfaces) APIs are used to integrate applications and services with the cloud. They enable communication between different software components and cloud services. Example : REST APIs, GraphQL . e. Automation and Orchestration Cloud environments use automation and orchestration tools to manage the deployment, scaling, and operation of resources. Tools : Kubernetes for container orchestration, Terraform for infrastructure-as-code, Ansible for automation. Ensures resources are efficiently provisioned and scaled based on demand, reducing manual intervention.

24. 5. Security and Compliance in the Cloud CC(Unit 3): Dr. B.Rajalingam 24 a. Identity and Access Management (IAM) IAM systems ensure that the right users have the appropriate access to cloud resources. Examples : AWS IAM, Azure Active Directory. b. Encryption Encrypting data at rest and in transit is crucial for cloud security. Examples : SSL/TLS for encryption in transit, AES for encryption at rest. c. Network Security Firewalls, VPNs, and virtual private clouds (VPCs) help secure the cloud environment. Examples : AWS Security Groups, Azure Network Security. d. Compliance and Auditing Cloud providers offer tools to help businesses comply with industry standards (e.g., GDPR, HIPAA) and provide auditing capabilities to track access and changes to data and resources.

25. 6. Cloud Management and Monitoring CC(Unit 3): Dr. B.Rajalingam 25 a. Cloud Management Platforms Cloud management platforms allow organizations to monitor, manage, and optimize their cloud environments. Examples : AWS CloudWatch, Azure Monitor, Google Cloud Operations Suite. b. Monitoring and Analytics Tools that monitor cloud performance, resource usage, and detect anomalies or potential security threats. Function : Helps ensure optimal performance, track costs, and improve security. c. Cost Management Cloud services can become expensive if not properly managed, so cost optimization tools are essential. Examples : AWS Cost Explorer, Azure Cost Management.

26. 7. Disaster Recovery and Backup CC(Unit 3): Dr. B.Rajalingam 26 Cloud platforms offer backup and disaster recovery solutions to ensure business continuity. Examples : AWS Backup, Google Cloud Storage, Azure Site Recovery. Data replication across regions, quick failover to secondary data centers in case of failure.

27. 8. Cloud Networking CC(Unit 3): Dr. B.Rajalingam 27 a. Virtual Networks Cloud services often use virtual networks (e.g., Virtual Private Cloud or VPC) to manage internal and external network traffic. b. Content Delivery Networks (CDN) CDNs distribute content to users from geographically dispersed data centers to improve load times and performance. Examples : Amazon CloudFront, Akamai.

28. Network Connectivity in Cloud Computing CC(Unit 3): Dr. B.Rajalingam 28 Network connectivity in cloud computing is essential for delivering cloud services, enabling data transfer, communication between resources, and interaction between users and the cloud environment. Cloud networking ensures the seamless operation of cloud services, including storage, compute, and applications, across different locations, devices, and platforms.

29. 1. Cloud Networking Basics CC(Unit 3): Dr. B.Rajalingam 29 Cloud networking refers to the combination of hardware and software resources used to enable cloud services and infrastructure. This includes virtualized networks, private and public networks, and hybrid models that connect users and applications to cloud resources. Key Components: Virtual Networks : Software-defined networks (SDNs) that connect cloud resources and enable isolated environments within the cloud. Networking Hardware : Routers, switches, firewalls, and load balancers that handle data transfer and manage traffic across the cloud. Internet Connectivity : Public cloud services rely on the internet for access, while private clouds may use dedicated lines.

30. 2. Virtual Private Cloud (VPC) CC(Unit 3): Dr. B.Rajalingam 30 A Virtual Private Cloud (VPC) is a private, isolated section of a cloud provider’s network. It allows users to configure and control virtualized networking components, including subnets, IP addresses, routing tables, and network gateways, providing a secure, customizable environment for cloud resources. Key Features: Subnets : Dividing a VPC into smaller, isolated networks. Route Tables : Directing traffic within and outside of the VPC. Internet Gateway : Allows resources within the VPC to connect to the internet. Virtual Private Gateway : Connects the VPC to on-premises data centers through VPN. Examples: AWS VPC : Amazon Web Services’ implementation of VPC, allowing users to create isolated networks for their resources. Google VPC : Google Cloud’s VPC solution provides a global, scalable network for secure cloud communication.

31. 3. Cloud Connectivity Models CC(Unit 3): Dr. B.Rajalingam 31 There are several ways to connect to the cloud, depending on the requirements for security, performance, and accessibility. a. Public Internet Connectivity Users and resources access the cloud through the public internet, which is the most common method for accessing public cloud services. Pros : Easy to set up, cost-effective. Cons : Less secure and prone to latency, especially in regions with poor internet infrastructure. b. Virtual Private Network (VPN) A VPN establishes a secure, encrypted connection between the user’s on-premises infrastructure and the cloud over the public internet. Pros : Increased security through encryption, easy to implement. Cons : Can experience performance issues due to shared internet infrastructure and potential latency. c. Direct Connectivity (Direct Connect, ExpressRoute) Cloud providers offer dedicated, high-bandwidth connections from on-premises infrastructure to the cloud. Examples include AWS Direct Connect, Azure ExpressRoute, and Google Cloud Interconnect. Pros : Lower latency, higher bandwidth, more secure. Cons : More expensive and complex to set up than internet-based connectivity. d. Peering Connections Peering allows different cloud networks (e.g., two VPCs or different cloud providers) to connect directly, bypassing the public internet. Types : VPC Peering : Direct connection between two VPCs. Inter-cloud Peering : Connects services between different cloud providers, enabling multi-cloud strategies. Pros : Secure and fast communication between clouds. Cons : Limited scalability for large multi-cloud deployments.

32. 4. Network Services in Cloud Computing CC(Unit 3): Dr. B.Rajalingam 32 Cloud providers offer several network services to enhance connectivity, performance, and security. Load Balancing Distributes incoming network traffic across multiple servers or instances, ensuring high availability and reliability of applications. Types : Layer 4 (Transport Layer) Load Balancing : Balances traffic at the network transport layer (TCP/UDP). Layer 7 (Application Layer) Load Balancing : Balances traffic based on content (e.g., HTTP requests). Examples : AWS Elastic Load Balancing (ELB), Azure Load Balancer, Google Cloud Load Balancing b. Content Delivery Networks (CDN) CDNs deliver content to users based on their geographic location by caching content at distributed edge servers, improving load times and reducing latency. Examples : Amazon CloudFront, Azure CDN, Google Cloud CDN c. DNS Services Domain Name System (DNS) services translate human-readable domain names (e.g., www.example.com ) into IP addresses. Cloud providers offer DNS management tools to route traffic efficiently. Examples : AWS Route 53, Azure DNS, Google Cloud DNS d. Firewall and Security Groups Virtual firewalls control inbound and outbound traffic to and from cloud instances. Security groups are used to define the traffic rules for specific instances. Examples : AWS Security Groups and Network Access Control Lists (ACLs), Azure Network Security Groups (NSGs), Google Cloud Firewall

33. e. Network Address Translation (NAT) CC(Unit 3): Dr. B.Rajalingam 33 Function : NAT allows instances in private subnets to connect to the internet without exposing their private IP addresses. It translates private IP addresses into a public IP for outgoing traffic. Examples : AWS NAT Gateway, Azure NAT Gateway 5. Cloud Networking Protocols Several protocols facilitate network connectivity in the cloud: IPsec (Internet Protocol Security) A protocol suite for securing IP communications through authentication and encryption. Use in Cloud : Frequently used in VPNs to secure traffic between on-premises networks and cloud environments. b. BGP (Border Gateway Protocol) BGP is used to exchange routing information between different networks. Use in Cloud : BGP is often used in direct connectivity setups (e.g., AWS Direct Connect) for routing between cloud and on-premises networks. c. HTTPS (Hypertext Transfer Protocol Secure) HTTPS is the secure version of HTTP, used to encrypt data between a user's browser and a cloud-based web application. Use in Cloud : HTTPS is essential for securing web applications and APIs hosted in the cloud. d. TCP/IP (Transmission Control Protocol/Internet Protocol) The fundamental communication protocol suite for the internet and cloud services. Use in Cloud : TCP/IP is used for almost all cloud communications, from connecting VMs to accessing cloud-based databases.

34. 6. Cloud Networking Challenges CC(Unit 3): Dr. B.Rajalingam 34 As cloud environments become more complex, there are several networking challenges to consider: a. Latency Issue : Delays in data transfer between users and cloud services, particularly in globally distributed cloud environments. Mitigation : Use of CDNs, edge computing, and dedicated connectivity like AWS Direct Connect. b. Security Issue : Protecting data in transit and securing network configurations is critical. Mitigation : Use of encryption (IPsec, SSL/TLS), VPNs, private connections, firewalls, and secure access policies (IAM). c. Network Performance and Availability Issue : Ensuring consistent and fast network performance is essential for real-time applications. Mitigation : Load balancing, autoscaling, and network redundancy. d. Multi-Cloud and Hybrid Cloud Networking Issue : Connecting different cloud environments and integrating on-premises and cloud infrastructures requires careful management of network configurations. Mitigation : Use of hybrid cloud services, peering, and cloud networking tools like VPNs and direct connectivity options.

35. 7. Emerging Trends in Cloud Networking CC(Unit 3): Dr. B.Rajalingam 35 a. 5G and Edge Computing Description : The combination of 5G and edge computing enhances cloud connectivity by bringing compute and storage closer to end-users, reducing latency. Impact : Enables real-time applications like IoT, autonomous vehicles, and augmented reality. b. SD-WAN (Software-Defined Wide Area Network) Description : SD-WAN simplifies the management of WAN connections and improves cloud connectivity by using software-defined technologies to control traffic. Impact : Provides optimized, secure, and cost-effective cloud connectivity. c. Cloud-Native Networking Description : Cloud-native applications (e.g., Kubernetes) rely on software-defined networking (SDN) to manage the dynamic, containerized environments. Impact : Ensures scalability and flexibility in cloud-native applications by abstracting complex networking tasks.

36. Applications on the Cloud CC(Unit 3): Dr. B.Rajalingam 36 Applications on the cloud are software programs that are hosted and run on cloud computing infrastructure rather than on local servers or personal devices. They take advantage of cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), Microsoft Azure, and others to provide scalable, flexible, and cost-effective services. 1. Types of Cloud Applications SaaS (Software as a Service): These are applications accessed over the internet, eliminating the need for local installation. Examples include Gmail, Salesforce, and Microsoft Office 365. PaaS (Platform as a Service): These provide platforms and environments to develop, run, and manage applications without the complexity of building and maintaining infrastructure. Examples include Google App Engine and AWS Elastic Beanstalk. IaaS (Infrastructure as a Service): Offers virtualized computing resources over the internet. Users can rent infrastructure components like servers, storage, and networking. Examples include AWS EC2, GCP Compute Engine.

37. 2. Benefits of Cloud Applications CC(Unit 3): Dr. B.Rajalingam 37 Scalability: Cloud applications can scale up or down based on demand, making them suitable for workloads that fluctuate. Cost Efficiency: Cloud providers offer a pay-as-you-go model, where businesses only pay for the resources they use, reducing capital expenditure. Global Reach and Accessibility: Users can access cloud applications from anywhere, promoting collaboration and flexibility in global teams. Security and Compliance: Major cloud providers offer robust security features and comply with regulations like GDPR, HIPAA, etc. Backup and Disaster Recovery: Cloud platforms provide easy solutions for data backup and recovery in case of disasters.

38. 3. Key Technologies for Cloud Applications CC(Unit 3): Dr. B.Rajalingam 38 Virtualization: Allows multiple virtual machines (VMs) to run on a single physical machine, maximizing resource utilization. Containers: Technologies like Docker and Kubernetes enable packaging applications and their dependencies into lightweight, portable containers. Microservices: Cloud applications often use a microservices architecture, breaking down applications into small, independent services that communicate via APIs. Serverless Computing: A model where the cloud provider automatically manages the infrastructure, allowing developers to focus purely on the code. AWS Lambda is a popular

39. CC(Unit 3): Dr. B.Rajalingam 39 4. Use Cases E-commerce Platforms: Applications like Shopify and Amazon that manage large amounts of data and transactions benefit from cloud scalability. Media Streaming Services: Services like Netflix, YouTube, and Spotify rely on cloud infrastructure to stream content to millions of users. Collaboration Tools: Cloud-based tools like Slack, Zoom, and Google Workspace allow real-time collaboration across distributed teams. 5. Cloud-Native Applications Cloud-native refers to applications specifically designed to run in cloud environments. They use cloud infrastructure and services optimally, typically incorporating technologies like containers, CI/CD pipelines, and DevOps practices.

40. Managing the Cloud CC(Unit 3): Dr. B.Rajalingam 40 Managing the cloud involves the efficient handling of cloud-based infrastructure, applications, and services to ensure optimal performance, cost efficiency, security, and scalability. Cloud management is a critical task for organizations adopting cloud computing to maintain control over their IT environment while taking full advantage of the cloud's capabilities. Here's an overview of key areas involved in cloud management:

41. 1. Cloud Management Platforms (CMP) CC(Unit 3): Dr. B.Rajalingam 41 Definition: CMPs are tools that provide a centralized interface to manage various cloud resources and services across different providers (e.g., AWS, Azure, GCP). They offer capabilities for provisioning, monitoring, automation, and optimization. Popular CMPs: CloudHealth by VMware Cisco CloudCenter Flexera RightScale Benefits: They provide unified control, help manage multi-cloud environments, optimize costs, and ensure compliance and security.

42. 2. Key Aspects of Cloud Management CC(Unit 3): Dr. B.Rajalingam 42 a. Provisioning and Orchestration Provisioning: Refers to setting up and allocating cloud resources like compute, storage, and networking based on requirements. This can be done manually or automated through scripts and orchestration tools. Orchestration: Involves automating workflows and coordinating tasks like starting, stopping, and scaling cloud services or applications across different environments. Tools: Terraform, Ansible, Kubernetes (for container orchestration). b. Monitoring and Performance Management Monitoring: Ensures that cloud resources and applications are performing optimally. This includes tracking resource utilization (CPU, memory, network), application response times, and identifying potential bottlenecks. Tools: Prometheus, Grafana, AWS CloudWatch, Azure Monitor. Key Metrics: CPU and memory usage, Network bandwidth and latency, Disk I/O operations, Service availability and downtime c. Cost Management and Optimization Cost Monitoring: Tracking cloud resource consumption to ensure that the usage aligns with budget constraints. Many organizations over-provision resources, leading to unnecessary costs. Cost Optimization Techniques: Rightsizing instances (e.g., adjusting underutilized instances), Using reserved or spot instances for cost savings, Automating instance shutdowns during off-hours, Eliminating unused resources (e.g., idle VMs, unattached storage volumes) Tools: AWS Cost Explorer, Azure Cost Management, Cloudability , and CloudCheckr .

43. CC(Unit 3): Dr. B.Rajalingam 43 d. Security and Compliance Identity and Access Management (IAM): Ensuring that only authorized users have access to specific cloud resources. Policies are enforced for role-based access control (RBAC), multi-factor authentication (MFA), and least privilege principles. Data Encryption: Encrypting data at rest and in transit to protect sensitive information. Compliance Management: Ensuring that the cloud infrastructure complies with industry standards such as GDPR, HIPAA, PCI DSS, etc. Security Tools: AWS IAM, Azure Active Directory, Prisma Cloud, AWS Shield, and Azure Security Center . e. Backup, Disaster Recovery, and High Availability Backup Management: Regularly creating and managing backups of critical data to avoid data loss. Disaster Recovery: Setting up processes to restore operations quickly in the event of a system failure, natural disaster, or security breach. This often involves geographically distributed cloud regions. High Availability (HA): Architecting cloud applications and infrastructure for minimal downtime and resilience by using techniques like load balancing, replication, and failover. Tools: AWS Backup, Azure Site Recovery, Google Cloud’s Disaster Recovery, Veeam.

44. CC(Unit 3): Dr. B.Rajalingam 44 f. Automation and DevOps Integration Automation: Managing cloud resources programmatically using Infrastructure as Code ( IaC ) tools like Terraform and CloudFormation. Automated processes reduce the chances of human error and increase consistency. DevOps: Integrating cloud management with continuous integration and continuous deployment (CI/CD) pipelines, allowing faster development and deployment cycles. DevOps Tools: Jenkins, GitLab CI, AWS CodePipeline , Azure DevOps. 3. Managing Multi-Cloud and Hybrid Cloud Environments Multi-Cloud: Managing applications and services spread across multiple cloud providers (e.g., using both AWS and Azure) to avoid vendor lock-in and leverage the best features of each platform. Hybrid Cloud: Managing a combination of on-premises infrastructure and public/private clouds, often requiring seamless integration and communication between environments. Challenges: Multi-cloud environments can be more complex to manage due to differing interfaces, APIs, and billing models. CMPs help streamline management across these platforms. 4. Cloud Governance Policies and Standards: Establishing a framework for how cloud resources are used and managed within the organization. Governance ensures consistency and enforces rules related to security, cost, and resource management. Tagging and Labeling : Cloud governance often involves tagging resources to track usage, cost, and ownership within an organization. Tags can help organize resources and align them with organizational goals.

45. CC(Unit 3): Dr. B.Rajalingam 45 5. Challenges in Cloud Management Resource Sprawl: Unmanaged cloud resources can lead to resource sprawl, increasing costs and complexity. Vendor Lock-In: Organizations relying heavily on one provider may find it difficult to switch due to differences in platforms and APIs. Security Risks: Cloud environments are inherently more open, making them vulnerable to misconfigurations and data breaches. 6. Best Practices for Effective Cloud Management Set up proper monitoring and alerting systems to detect performance issues early. Automate as much as possible to reduce manual intervention and errors. Regularly audit and optimize resource usage to avoid cost overruns. Enforce strict security policies through IAM and encryption. Use tagging to manage resources efficiently across the organization.

46. Managing the Cloud Infrastructure CC(Unit 3): Dr. B.Rajalingam 46 Cloud infrastructure refers to the foundational services and resources that run on cloud platforms, such as compute, storage, networking, and security configurations. Managing cloud infrastructure ensures that these resources are available, secure, scalable, and optimized for performance. Key Responsibilities: Provisioning Resources: Setting up virtual machines, containers, databases, storage, and networking based on business requirements. Example: Provisioning EC2 instances (AWS) or VMs (Azure, GCP). Scaling Infrastructure: Dynamically increasing or decreasing resources based on demand (horizontal or vertical scaling). Example: Auto-scaling groups in AWS automatically launch or terminate instances based on traffic patterns. Network Management: Configuring virtual private clouds (VPCs), subnets, gateways, load balancers, and firewalls. Ensuring network traffic routing and isolation for security and efficiency. Example: Setting up VPCs and VPNs for hybrid cloud connectivity.

47. CC(Unit 3): Dr. B.Rajalingam 47 Storage and Backup: Managing various types of cloud storage (e.g., block storage, object storage, file storage). Automating backup policies to ensure data is always recoverable. Example: S3 buckets (AWS), Azure Blob Storage, and automated backup strategies. Security and Access Control: Implementing Identity and Access Management (IAM) to control who can access which resources. Encrypting data at rest and in transit. Example: Using AWS IAM for role-based access and MFA (Multi-Factor Authentication) enforcement. Cost Management: Monitoring infrastructure usage and optimizing costs through rightsizing and other techniques. Example: Terminating idle instances or optimizing storage tiers for cost savings.

48. Key Tools for Managing Cloud Infrastructure: CC(Unit 3): Dr. B.Rajalingam 48 Infrastructure as Code ( IaC ): Automating infrastructure setup and changes through code. Tools: Terraform, AWS CloudFormation, Azure Resource Manager (ARM) Templates. Monitoring and Performance Management: Cloud-native services like AWS CloudWatch, Google Stackdriver , and Azure Monitor. Third-party tools like Datadog and Prometheus/Grafana for more advanced monitoring. Automation Tools: Automating routine tasks like backups, patching, and scaling. Tools: Ansible, Chef, Puppet. Challenges in Managing Cloud Infrastructure: Resource Sprawl: Unused or idle resources may lead to unnecessary costs. Complexity in Multi-Cloud: Managing resources across multiple providers can be complex. Security Misconfigurations: Mismanaged configurations can lead to vulnerabilities (e.g., open S3 buckets).

49. Managing Cloud Applications CC(Unit 3): Dr. B.Rajalingam 49 Cloud applications are the software and services that run on top of the cloud infrastructure. Managing cloud applications involves deploying, scaling, monitoring, and securing software that users interact with, whether it's a web service, mobile app backend, or enterprise application. Key Responsibilities: Deployment of Applications: Automating the deployment process through Continuous Integration/Continuous Deployment (CI/CD) pipelines. Example: Using Jenkins or GitLab CI to automate deployment into cloud environments like AWS Lambda or Google Cloud Functions. Scaling Applications: Ensuring that the application can handle varying levels of traffic by dynamically adjusting resources. Example: Using Kubernetes to manage and scale containerized applications or Elastic Beanstalk to auto-scale web apps. Monitoring and Logging: Tracking application performance, user activity, and error rates. Example: Using services like AWS CloudWatch, Azure Application Insights, or Datadog to monitor app performance. Security and Authentication: Ensuring that cloud applications are secure, from user authentication (e.g., OAuth, SSO) to API security (e.g., rate limiting, token-based authentication). Example: Implementing OAuth 2.0 for secure API access or using AWS Cognito for user authentication. Application Performance Optimization: Analyzing and improving response times, reducing latency, and optimizing database queries or caching mechanisms. Example: Implementing caching via AWS CloudFront or Redis to reduce load times. Fault Tolerance and High Availability: Designing applications to be resilient and handle failures without downtime. Example: Implementing auto-failover databases (AWS RDS Multi-AZ) or distributed message queues (AWS SQS, Azure Service Bus).

50. CC(Unit 3): Dr. B.Rajalingam 50 Key Tools for Managing Cloud Applications: CI/CD Pipelines: Tools: Jenkins, GitLab CI, CircleCI , AWS CodePipeline . Containerization and Orchestration: Packaging and running applications in lightweight containers that can be easily scaled and deployed across multiple environments. Tools: Docker, Kubernetes, AWS ECS, Azure Kubernetes Service (AKS), GCP Kubernetes Engine (GKE). Serverless Architecture: Running application code without managing infrastructure. Tools: AWS Lambda, Google Cloud Functions, Azure Functions. Monitoring and Logging: Application-specific monitoring tools to track performance and troubleshoot issues. Tools: New Relic, Datadog APM, Sentry, ELK Stack (Elasticsearch, Logstash, Kibana). Challenges in Managing Cloud Applications: Handling Traffic Spikes: Unexpected traffic spikes can overwhelm applications if not properly scaled. Maintaining High Availability: Applications must be resilient to failure, requiring replication, load balancing, and failover strategies. Security at the Application Layer: Application vulnerabilities (e.g., SQL injection, XSS) need to be managed with robust security measures.

51. Migrating Application to Cloud CC(Unit 3): Dr. B.Rajalingam 51 Migrating an application to the cloud involves moving existing on-premises applications and data to a cloud-based infrastructure. This process can significantly improve scalability, performance, and cost-efficiency, but it requires careful planning and execution to ensure a smooth transition. There are several strategies for cloud migration, each suited to different types of applications and business needs. Steps for Migrating an Application to the Cloud: 1. Assess the Current Environment Inventory and Analysis: Identify the applications, databases, and data that need to be migrated. Assess the dependencies between applications, data storage, and infrastructure. Evaluate the performance, security, and compliance requirements. Cloud Readiness Assessment: Analyze whether your current applications are cloud-ready or need modifications. Tools: AWS Migration Evaluator, Azure Migrate, Google Cloud Migrate for Compute Engine. Choosing the Right Cloud Model: Public Cloud: AWS, Azure, GCP—resources are shared across users. Private Cloud: Dedicated environment—higher control and security. Hybrid Cloud: A combination of on-premises and cloud environments.

52. CC(Unit 3): Dr. B.Rajalingam 52 2. Choose a Cloud Migration Strategy a. Rehosting (Lift and Shift) Definition: Moving the application as-is from on-premises to the cloud with minimal or no modification. When to Use: Suitable for applications that work well on existing infrastructure and don’t need cloud-native features. Advantages: Fastest and least complex; low initial cost. Challenges: May not leverage the full benefits of the cloud (e.g., auto-scaling, serverless). b. Replatforming (Lift, Tinker, and Shift) Definition: Making a few optimizations to the application during migration to leverage basic cloud features, like using managed databases or cloud storage. When to Use: When minor changes can improve performance without significant re-architecture. Advantages: Less effort than refactoring; leverages cloud-managed services. Challenges: Some level of reconfiguration is required. c. Refactoring (Re-architecting) Definition: Completely re-engineering the application to take full advantage of cloud-native features like serverless, microservices, and containers. When to Use: Ideal for applications that need high scalability, agility, and efficiency in the cloud. Advantages: Maximum benefit from cloud technologies (auto-scaling, pay-per-use). Challenges: Most complex and costly; requires deep expertise in cloud development. d. Repurchasing (Move to SaaS) Definition: Replacing the existing application with a cloud-based SaaS (Software-as-a-Service) alternative. When to Use: When the cost of maintaining or upgrading the current application is too high. Advantages: Simplified management and operations; lower maintenance. Challenges: Data migration can be complex; vendor lock-in risks. e. Retiring Definition: Decommissioning applications that are no longer useful or have been replaced by modern alternatives. When to Use: When certain legacy applications are no longer needed after migration. Advantages: Reduces costs and resource usage. Challenges: Ensuring critical data is backed up and accessible before retiring.

53. CC(Unit 3): Dr. B.Rajalingam 53 3. Design the Cloud Architecture Decide on Cloud Provider(s): AWS, Azure, and GCP each offer unique services and pricing models, so choose based on your application needs. Architect for Scalability and High Availability: Use auto-scaling groups, load balancers, and cloud-native services. Ensure that databases are configured with replication and failover mechanisms. Cloud-Native Features: Consider using managed databases (AWS RDS, Azure SQL), serverless functions (AWS Lambda, Azure Functions), and container orchestration (Kubernetes).

54. CC(Unit 3): Dr. B.Rajalingam 54 4. Plan Data Migration Data Transfer Strategy: For large datasets, consider offline data transfer methods like AWS Snowball or Google Transfer Appliance. For ongoing data, use database replication and synchronization tools. Tools: AWS Database Migration Service (DMS), Azure Data Migration Service, Google Cloud Transfer Service. Data Integrity and Security: Ensure data is encrypted both in transit and at rest. Validate that data has been successfully migrated before decommissioning on-prem infrastructure. Database Migration: Assess whether to move to a managed database service or keep existing database engines in virtual machines. Example: Migrating on-premises MySQL to Amazon RDS or Azure SQL Database.

55. CC(Unit 3): Dr. B.Rajalingam 55 5. Prepare for Application Migration a. Application Dependency Mapping: Map out dependencies between services, databases, and external systems to avoid downtime. Ensure cloud infrastructure supports the necessary networking configurations (e.g., VPCs, subnets, firewalls). b. Test in Staging Environment: Set up a staging environment in the cloud to test the migration process. Run load tests and monitor application performance to identify any issues before live migration. c. Security and Compliance: Implement identity and access management (IAM) for secure access to cloud resources. Ensure compliance with industry regulations (e.g., GDPR, HIPAA) is maintained during and after migration.

56. CC(Unit 3): Dr. B.Rajalingam 56 6. Execute the Migration a. Migration Process: Follow a phased approach to minimize downtime, starting with low-priority applications. Use automated tools where possible to ensure consistency and reduce manual errors. b. Cutover Strategy: Big Bang: Move everything at once, typically during scheduled downtime. Advantage: Fast, but risky. Phased Migration: Migrate applications and data incrementally. Advantage: Less risk and downtime, but takes longer. c. Rollback Plan: Always have a rollback plan in case migration fails. Ensure backups are available to restore on-prem systems if necessary.

57. CC(Unit 3): Dr. B.Rajalingam 57 7. Post-Migration Optimization Performance Tuning: Monitor cloud applications to ensure they are performing as expected. Use cloud-native monitoring tools (e.g., AWS CloudWatch, Azure Monitor, GCP Stackdriver ) to analyze performance metrics. Cost Optimization: Review the cloud usage and identify areas for cost reduction, such as eliminating idle resources, right-sizing instances, and using reserved instances. Tools: AWS Cost Explorer, Azure Cost Management, GCP Billing Reports. Security Audits: Perform security audits and implement additional controls if needed (e.g., encryption, network firewalls, IAM policies). Cloud-Native Enhancements: Over time, refactor parts of the application to use cloud-native services like serverless functions, managed databases, and containerized microservices to improve agility and cost efficiency.

58. CC(Unit 3): Dr. B.Rajalingam 58 8. Monitoring and Management Ongoing Monitoring: Set up continuous monitoring of both infrastructure and applications. Tools: Prometheus + Grafana, Datadog, New Relic. Disaster Recovery Plan: Ensure disaster recovery strategies are implemented with proper backups and multi-region failover setups. Training and Documentation: Train your teams on managing cloud environments. Keep documentation updated on architecture, dependencies, and processes in the cloud. Challenges and Considerations in Cloud Migration: Downtime Risk: Poor planning may result in extended downtime during migration. Data Security and Compliance: Ensuring the security of sensitive data during migration is crucial. Application Dependencies: Legacy applications might have complex dependencies that are difficult to replicate in the cloud. Cost Overruns: Without proper monitoring and optimization, cloud costs can exceed expectations.

59. Phases of Cloud Migration Approaches for Cloud Migration CC(Unit 3): Dr. B.Rajalingam 59 Cloud migration is a complex process that typically follows specific phases and utilizes different approaches based on the application's architecture, business needs, and the desired outcomes from migrating to the cloud. Understanding these phases and approaches is critical to ensure a smooth migration that leverages the benefits of cloud computing effectively. Phases of Cloud Migration 1. Planning and Assessment Goal: Evaluate the current environment and define the migration strategy. Activities: Perform a cloud readiness assessment. Identify the applications, services, and data to be migrated. Map dependencies between systems (e.g., databases, APIs, networking). Evaluate business needs (e.g., scalability, cost savings, performance). Choose the target cloud environment (e.g., AWS, Azure, Google Cloud). Output: Migration plan, cost estimation, and detailed timeline. 2. Designing the Cloud Architecture Goal: Define how the migrated applications and infrastructure will operate in the cloud. Activities: Design cloud architecture for scalability, performance, and security. Decide on networking configurations, storage types, and compute services. Define auto-scaling, load balancing, disaster recovery, and backup strategies. Plan how the cloud infrastructure will interact with existing on-premises systems (for hybrid environments). Output: Cloud architecture blueprint and infrastructure requirements.

60. CC(Unit 3): Dr. B.Rajalingam 60 3. Choosing the Cloud Migration Strategy Goal: Select the best migration approach for each application or service. Activities: Choose among cloud migration strategies (Lift and Shift, Refactor, etc., detailed in the next section). Plan specific actions based on the chosen strategy for each application. Output: Migration strategy mapped to each application. 4. Migration Preparation Goal: Set up the cloud environment and prepare the application for migration. Activities: Set up the necessary cloud infrastructure (virtual machines, networks, storage, security policies). Prepare the application for migration (e.g., reconfiguring for cloud, decoupling dependencies). Establish a testing/staging environment in the cloud. Establish data migration pipelines and choose the appropriate tools for data transfer. Output: Cloud environment ready for migration, staging environment, and data migration plan.

61. CC(Unit 3): Dr. B.Rajalingam 61 5. Application and Data Migration Goal: Migrate applications and data to the cloud environment. Activities: Migrate data, ensuring data integrity and minimal downtime. Use automation tools to deploy applications to the cloud. Test the application to ensure functionality, performance, and security. Gradually move users or services to the cloud, ensuring proper cutover strategy (Big Bang or phased). Output: Application and data live in the cloud, successfully migrated with minimal impact. 6. Testing and Optimization Goal: Ensure that applications are working correctly in the new environment and optimize them for the cloud. Activities: Test for application performance, security, and user experience. Monitor resource utilization, cost, and adjust auto-scaling configurations as needed. Conduct security assessments and penetration testing. Implement performance optimization techniques such as caching, load balancing, and database tuning. Output: Application running smoothly in the cloud with optimized performance. 7. Ongoing Management and Monitoring Goal: Monitor cloud resources, optimize costs, and manage security continuously. Activities: Use cloud-native monitoring tools (AWS CloudWatch, Azure Monitor, etc.) to track performance and usage. Implement cost management tools to prevent resource sprawl and manage cloud expenses. Set up security audits, backup policies, disaster recovery strategies, and routine maintenance. Output: Stable cloud operations with continuous monitoring and improvements.

62. CC(Unit 3): Dr. B.Rajalingam 62 Approaches for Cloud Migration (The "6 R’s") The "6 R’s" provide a framework for deciding how to migrate different applications to the cloud. These approaches vary in complexity and potential benefits depending on the requirements of each application. 1. Rehosting (Lift and Shift) Definition: Moving an application as-is from on-premises to the cloud with minimal changes. Use Case: For applications that don’t need cloud-native capabilities but benefit from moving off legacy infrastructure. Benefits: Fastest migration method. Least risk and effort. No need to rewrite or refactor code. Drawbacks: May not fully leverage the cloud’s scalability and flexibility. Higher ongoing operational costs since cloud-native features (e.g., auto-scaling) are not utilized. 2. Replatforming (Lift, Tinker, and Shift) Definition: Making minimal changes to optimize the application for the cloud without rewriting its core architecture. Use Case: For applications that need some optimization to improve performance (e.g., moving to managed databases or using cloud-native storage). Benefits: Leverages cloud-managed services for reduced operational burden. Retains most of the original application code, minimizing development effort. Drawbacks: Slightly more complex than rehosting. May still not fully leverage cloud-native capabilities.

63. CC(Unit 3): Dr. B.Rajalingam 63 3. Repurchasing (Move to SaaS) Definition: Replacing the existing application with a SaaS (Software as a Service) alternative. Use Case: For applications where migrating to a cloud-native, subscription-based service is more efficient (e.g., replacing an on-prem CRM with Salesforce). Benefits: No need for maintenance or infrastructure management. Immediate access to cloud-native features and scalability. Drawbacks: Potential data migration challenges. Vendor lock-in and reduced control over customization. 4. Refactoring (Re-architecting) Definition: Rewriting and restructuring the application to take full advantage of cloud-native features like microservices, serverless, and containers. Use Case: Ideal for complex, high-performance applications that need to scale dynamically or adopt agile development practices. Benefits: Full leverage of cloud scalability, agility, and cost-efficiency. Modernized application architecture that’s easier to maintain and update. Drawbacks: Most time-consuming and expensive. Requires significant development resources and expertise.

64. CC(Unit 3): Dr. B.Rajalingam 64 5. Retire Definition: Decommissioning or archiving applications that are no longer necessary or have been replaced by modern alternatives. Use Case: When certain legacy applications are redundant, no longer useful, or too expensive to migrate. Benefits: Eliminates unnecessary costs and reduces complexity. Drawbacks: May require archiving or long-term storage of historical data before retiring the system. 6. Retain (Hybrid Strategy) Definition: Keeping some applications on-premises, particularly if they are not ready for the cloud, or require low latency, specific compliance, or performance that cloud services cannot meet. Use Case: When organizations prefer to maintain control of certain mission-critical applications or data. Benefits: Maintains control over sensitive data and applications. Avoids cloud migration risks for legacy or compliance-heavy systems. Drawbacks: Requires ongoing management of on-prem infrastructure. Can complicate hybrid environments, adding complexity and overhead.

65. Thank You CC(Unit 3): Dr. B.Rajalingam 65