Unit 05 - Cloud Architecture and Design Patterns.pdf

SE 4455 Cloud Computing Unit 5: Cloud Architecture and Design Patterns Fadi AlMahamid, Ph.D. Contents 01 Introduction to Cloud Architecture 02 Cloud Design Patterns 03 High Availability, Scalability, and Load Balancing 04 Sustainable Cloud Design 05 Efficient Resource Utilization 01 Introduction to...

SE 4455 Cloud Computing Unit 5: Cloud Architecture and Design Patterns Fadi AlMahamid, Ph.D. Contents 01 Introduction to Cloud Architecture 02 Cloud Design Patterns 03 High Availability, Scalability, and Load Balancing 04 Sustainable Cloud Design 05 Efficient Resource Utilization 01 Introduction to Cloud Architecture Cloud Architecture ➔ Architectural Design: Architecture generally involves the deliberate organization of interrelated components to construct a complex structure. It's about creating a coherent system where all parts function together effectively. ➔ Software Architectural Design: In software engineering, architectural design refers to drafting a blueprint of a software system's structure. This plan outlines how software components, interfaces, and data flows interact within the system to meet specific requirements. Purpose: Ensures the system's scalability, reliability, and performance while meeting the predefined requirements and constraints. ➔ Cloud Architecture: The conceptual model that encompasses the components and subcomponents necessary for cloud computing. These components typically involve a front-end platform, back-end platforms, a cloudbased delivery, and a network designed to deliver computing services over the Internet. ➔ Key Components of Cloud Architecture: Front End (Client Side) Back End (Cloud Service Provider Side) Cloud-Based Delivery Models (IaaS, PaaS, SaaS) Network (Internet, Intranet) Benefits of Cloud Architecture ➔Flexibility and Scalability: Easily scales resources to meet demand. ➔Cost Efficiency: Reduces or eliminates capital expenditure on hardware and facilities. ➔High Availability and Disaster Recovery: Ensures services are always on, and data is safe, regardless of local failures or disasters. 02 Core Cloud Design Patterns Client-Server Architecture Description: A model where client applications request services from servers, which respond with the requested information or action. This fundamental architecture underpins many web and network applications. Workstation Benefits: Simplifies network management and centralizes data storage and processing. Laptop Considerations: Requires robust server management, which can lead to bottlenecks if not properly scaled. Mobile Server Distributed Architecture Description: Distributes software components across multiple networked computers to improve scalability and fault tolerance. DB Server Benefits: Enhances application performance, reliability, and availability. Considerations: App Server Complexity in managing distributed systems and potential consistency issues. File Server Banking System Service-Oriented Architecture (SOA) Description: An architectural pattern where functionality is organized into reusable services, accessible over a network, allowing for integration across different systems and platforms. Benefits: Enhances flexibility and agility, promotes reuse, and eases integration. Map Service Payment Service Login Service Enterprise Service Bus Service Registry Considerations: Can become complex to manage and requires strict governance. Web Portal Microservices Architecture Description: Structures an application as a collection of loosely coupled services, each implementing a specific business function and communicating via welldefined APIs. Benefits: Facilitates continuous delivery, scalability, and resilience. API Gateway Mobile REST API Passenger Web UI REST API Passenger Management Trip Management REST API REST API Considerations: Complexity in managing multiple services and data consistency challenges. Deriver Web UI Driver Management Payments Publish-Subscribe (Pub-Sub) Architecture Description: A messaging paradigm where subscribers receive messages published to a topic asynchronously, decoupling producers from consumers. Publisher 1 Publisher 2 Benefits: Enhances message scalability and flexibility and simplifies system integration. Message Broker Topic 1 Topic 2 Topic 3 Subscriber B Subscriber C Considerations: Managing large numbers of topics and subscriptions can be challenging. Broker Architecture vs PubSub Subscriber A Multi-layered (Tiered) Architecture Description: Organizes software into layers, each with specific responsibilities such as presentation, application logic, and data management, to promote separation of concerns. Benefits: Improves maintainability and allows for independent layer scaling. Considerations: Can introduce complexity and performance overhead. Presentation Layer Business Logic Layer Persistence Layer Data Layer Event-Driven Architecture Description: Components generate events that trigger other parts of the application to act, facilitating highly responsive and scalable systems. Consumer Event Channel Enables real-time responses and simplifies scalability. Requires robust event management and tracking. Consumer Events Benefits: Considerations: Consumer Events Producer Producer Producer Asynchronous Messaging Architecture Description: Uses message queues to enable components to communicate without requiring a synchronous response, improving system resilience and flexibility. Benefits: Decouples application components and enhances scalability and fault tolerance. Considerations: Complexity in message tracking and handling failures. Producer Consumer Queue Pipe-Filter Architecture Description: Structures data processing applications as a sequence of processing components (filters) connected by channels (pipes) through which data flows. Each filter performs a specific processing task, with the output of one filter serving as the input to the next. Benefits: Simplifies system design by decomposing it into reusable filters, facilitates parallel processing and enhances maintainability and scalability. Source Pipeline 1 Filter Pipeline 2 Filter Considerations: Managing data flow between filters can be complex, and the slowest filter in the pipeline may impact performance. Destination Serverless Architecture Description: An architectural approach that allows developers to build and deploy applications and services without managing underlying infrastructure. The cloud provider dynamically manages the allocation of resources, automatically scaling to match demand. Benefits: Reduces operational overhead, improves cost efficiency through pay-per-use pricing models, and automatically scales. Considerations: Potential for vendor lock-in, challenges in performance tuning for cold starts, and limitations in runtime environments. 03 High Availability, Scalability, and Load Balancing Cloud Elasticity ➔ Elasticity refers to the ability of a system to automatically adjust and allocate computational resources based on the current demand, ensuring optimal performance, reliability, and efficiency without manual intervention ➔ In cloud computing, ensuring that applications are reliable, can handle increasing loads, and distribute traffic effectively are key goals. ➔ Elasticity encapsulates the essence of dynamically managing workloads to achieve: High Availability (HA) minimizes downtime and maintains business continuity. Scalability allows systems to accommodate growth without performance degradation. Load Balancing efficiently distributes incoming network traffic across multiple servers to ensure no single server becomes overwhelmed. Together, these principles enhance user experience and system resilience. High Availability (HA) ➔ High Availability is the ability of a system to remain operational and accessible, even in the event of component failures or maintenance operations. ➔ HA is achieved through: Redundancy refers to the duplication of critical components or functions of a system with the intention of increasing reliability of the system fault tolerance: The ability of a system to continue operating without interruption when one or more of its components fail failover: the process by which a system automatically transfers control to a duplicate system, component, or network upon the failure or abnormal termination of the currently active operation. No Single Point of Failure: The system design ensures that no one failure will lead to the complete breakdown of a system. ➔ HA systems are measured by their uptime, aiming for 'five nines' (99.999%) availability. Redundancy Cluster Fault-Tolerance Failover Cluster Cluster Replica Server 1 Server 2 Server 1 Server 2 Load Balancer Server 3 Server 1 Active Server 2 Passive Scalability is the capability of a system to handle a growing amount of work or its potential to accommodate growth. There are two types: Vertical Scalability (Scaling Up): Enhancing the capacity of an existing server or resource, such as adding more CPUs or memory. Horizontal Scalability (Scaling Out): Adding more instances of resources, such as deploying additional servers to handle increased load. Effective scalability strategies involve understanding workload patterns and anticipating growth to ensure resources are utilized efficiently. Vertical Scaling Increase in processing power Principles of Scalability Horizontal Scaling Increase the number of machines Load Balancing Strategies Load Balancing is a technique used to distribute incoming network traffic across multiple servers to ensure no single server bears too much load. This not only optimizes resource use but also improves responsiveness and availability. Load balancers can operate at various layers of the OSI model and utilize different algorithms, such as roundrobin, least connections, and IP hash, depending on the application’s specific requirements. Cluster Server 1 Server 2 Load Balancer 04 Sustainable Cloud Design Understanding Sustainable Cloud Design ➔ Sustainable cloud design refers to the practice of architecting, deploying, and managing cloud computing resources in a way that minimizes their environmental impact. ➔This involves efficient use of computing resources, reducing energy consumption, and leveraging renewable energy sources. ➔Key components include energy-efficient hardware, optimized workload distribution, and the use of green data centers. Challenges in Cloud Sustainability ➔Data Center Energy Consumption: Cloud services rely on data centers, which are energyintensive facilities. ➔Resource Over-provisioning: Overestimating the need for computing resources leads to waste and unnecessary emissions. ➔Lack of Visibility: Difficulty in measuring and managing the environmental impact of cloud resources. ➔Dependency on Non-renewable Energy: Many data centers still depend on non-renewable energy sources. Green Data Centers ➔Employ energy-efficient technologies and designs. ➔Utilize renewable energy sources like solar and wind. ➔Implement advanced cooling systems and server utilization strategies. ➔Aim to reduce carbon footprint and operational energy use. Key Considerations for Sustainable Cloud Solutions ➔ Efficiency by Design: Optimize software and hardware to use the least energy for a given task. ➔ Right-Sizing: Match the size of your computing resources to the workload, avoiding over-provisioning. ➔ Renewable Energy Usage: Choose cloud providers and data centers powered by renewable energy sources. ➔ Lifecycle Management: Implement strategies for the entire lifecycle of cloud services, from deployment to decommissioning, focusing on reducing waste. ➔ Carbon Footprinting: Understand and track your cloud infrastructure's carbon footprint to identify improvement areas. Tools for Sustainable Cloud Computing ➔ Cloud Service Providers’ Sustainability Tools: Use tools like AWS’s Carbon Footprint Tool and Google Cloud's Carbon Footprint dashboard for tracking and managing emissions. ➔ Energy Efficiency Best Practices: Implement guidelines from The Green Grid, Energy Star, and other organizations focused on IT energy efficiency. ➔ Serverless Architectures: Leverage serverless computing to automatically scale usage up or down, ensuring efficient use of resources. ➔ Managed Services: Utilize managed services (e.g., AWS Fargate, Google Kubernetes Engine) that optimize resource allocation and reduce idle capacity. ➔ Renewable Energy Credits and Carbon Offsetting: Engage in renewable energy credits and carbon offset programs to mitigate unavoidable emissions. Steps for Building Sustainable Cloud Solution Step 1: Assess and Plan for Sustainability Step 2: Design for Efficiency Step 3: Optimize Resource Utilization Step 4: Use Sustainable Resources and Services Step 5: Implement Energy-Efficient Operations Step 6: Monitor, Analyze, and Report Step 7: Engage in Renewable Energy and Carbon Offsetting Step 8: Educate and Advocate Step 1: Assess and Plan for Sustainability Define Sustainability Goals: Before starting, define what sustainability means for your project. Goals might include minimizing energy consumption, reducing carbon footprint, or maximizing the use of renewable energy. Assessment: Evaluate the current state of your infrastructure and applications in terms of efficiency and sustainability. This includes assessing energy use, resource utilization, and dependency on non-renewable energy sources. Step 2: Design for Efficiency Efficient Architecture: Design your architecture to be as efficient as possible. This includes using microservices architectures, serverless computing, and designing for scalability to ensure that resources are used optimally. Right-Sizing: Carefully select the type and size of resources (e.g., compute instances, storage solutions) to match your workload requirements closely, avoiding over-provisioning. Step 3: Optimize Resource Utilization Dynamic Scaling: Implement auto-scaling to adjust the resources automatically based on demand. This ensures that you are not wasting resources during low traffic and can handle high loads efficiently. Load Balancing: Use load balancing to distribute workloads evenly across resources, improving efficiency and reducing the need for excess capacity. Step 4: Use Sustainable Resources and Services Select Green Data Centers: Choose cloud providers and data centers that use renewable energy sources and are committed to sustainability. Managed Services: Use managed services and serverless computing options where possible. These services are typically optimized for high efficiency and lower energy use because the provider can aggregate customer workloads. Step 5: Implement Energy-Efficient Operations Continuous Monitoring: Use tools to continuously monitor your resources' performance and efficiency. Look for ways to reduce energy use and improve efficiency. Update and Maintenance: Regularly update applications and infrastructure to leverage more efficient technologies and practices. This includes optimizing software to run more efficiently on the hardware. Step 6: Monitor, Analyze, and Report Sustainability Metrics: Collect and analyze data on energy consumption, carbon footprint, and other relevant sustainability metrics. Continuous Improvement: Use the insights gained from monitoring and analysis to make iterative improvements to your cloud solutions, reducing environmental impact over time. Step 7: Engage in Renewable Energy and Carbon Offsetting Renewable Energy Credits: Purchase renewable energy credits (RECs) to offset your energy use with renewable sources. Carbon Offsetting: Invest in carbon offset projects to compensate for the emissions that cannot be eliminated through your sustainability efforts. Step 8: Educate and Advocate Stakeholder Engagement: Educate stakeholders about the importance of sustainability in cloud computing and the steps your project takes to address it. Share Best Practices: Contribute to the broader community by sharing your experiences, challenges, and solutions in building sustainable cloud solutions. 05 Efficient Resource Utilization Introduction to Efficient Resource Utilization ➔ Efficient Resource Utilization in cloud computing aims to optimize the use of computing resources to deliver maximum performance at minimum cost. It involves strategies to ensure that resources like computing, storage, and networking are used as effectively as possible, reducing waste and improving cost-efficiency. ➔ Key benefits include reduced operational costs, enhanced performance, and minimized environmental impact. ➔ Resource Utilization refers to how computing resources are used to perform meaningful work. High utilization means resources are being used effectively, while low utilization indicates potential waste. ➔ Challenges include over-provisioning, underutilization, and resource contention, leading to inefficiencies and increased costs. Strategies for Maximizing Utilization ➔Right-Sizing: Adjusting the size of computing resources based on workload requirements to avoid over-provisioning. ➔Auto-Scaling: Automatically adjusting the number of resources in response to varying loads, ensuring optimal performance without manual intervention. ➔Load Balancing: Distributing workloads evenly across resources to prevent any single resource from being overwhelmed, improving overall system efficiency. Best Practices for Efficient Resource Utilization ➔Adopt a multi-faceted approach combining rightsizing, auto-scaling, and load balancing for computing resources. ➔Implement cost-effective storage strategies like data tiering and thin provisioning. ➔Optimize network usage with CDNs and bandwidth management. ➔Leverage monitoring tools for continuous optimization. ➔Embrace green computing principles to enhance sustainability.