دیوپس ابری: ساخت برنامه‌های مقیاس‌پذیر و قابل‌اعتماد

This book delivers cloud-based applications that are both scalable and reliable, aligning with the evolving needs of the present user base. This innovative approach blends the agility of cloud computing with the efficiency of contemporary DevOps methodologies. The book starts by providing valuable insights into the ever-evolving software landscape of Cloud-native DevOps. It delves into strategies for crafting scalable and dependable applications and illustrates the art of leveraging open-source tools to enhance collaboration. It navigates through the integral role of microservices in contemporary software development and imparts the know-how to integrate them with DevOps practices. The book simplifies container technology, with a focus on Docker and Kubernetes. It further elucidates the process of streamlining software delivery through Continuous Integration and Continuous Deployment (CI/CD). As you progress, you will explore open-source tools, including Argo, Kubeflow Pipelines, and AWS Step Functions. The concluding section covers real-world case studies and best practices for implementing Cloud-native DevOps. The book reviews the core concepts covered throughout and provides an exciting glimpse into the future of Cloud-native DevOps. Upon completing this book, you will be well-versed in the principles and practices of Cloud-native DevOps, understand real-world applications, and recognize the critical importance of security in cloud computing. What You Will Learn Create cloud-based applications that can scale with the changing needs of today’s user base Combine the flexibility of cloud computing with the efficiency of modern DevOps methodologies Understand the core concepts and principles of Cloud-native DevOps Understand microservices, containers, and continuous integration and continuous deployment (CI/CD) Table of Contents About the Author About the Technical Reviewer Chapter 1: Unveiling the Cloud- Native Paradigm Pre-cloud Era Evolution of Cloud Native Shift from Mainframe Computing to a Cloud-Native Approach Advantages of Cloud-Native Computing over Mainframe Disadvantages of Cloud-Native Computing over Mainframe The Twelve-Factor App Introduction and Understanding of Cloud Native What Is CNCF? Core Pillars of Cloud Native Containerization Continuous Integration and Delivery Serverless Computing Advantages of Serverless Cloud Computing Popular Serverless Computing Platforms Disadvantages of Serverless Cloud Computing Cloud Concept Key Features of a Public Cloud Downside of Public Cloud Key Features of a Private Cloud Downside of Private Cloud Key Features of Hybrid Cloud Downside of Hybrid Cloud Differences Between IaaS, PaaS, and SaaS Infrastructure-as-a-Service (IaaS) Advantages of IaaS Disadvantages of IaaS Platform-as-a-Service (PaaS) Advantages of PaaS Disadvantages of PaaS Software-as-a-Service (SaaS) Advantages of SaaS Disadvantages of SaaS Cloud Native Maturity Model (CNMM) Layers of Cloud-Native Landscape Provisioning Layer Runtime Layer Orchestration and Management Layer Application Definition and Development Layer Summary Chapter 2: Cloud-Native DevOps Architectural Overview Introduction to DevOps in Cloud-Native Environment What Is DevOps? Principles of DevOps 7C’s of DevOps Life Cycle Continuous Development Continuous Integration Continuous Testing Continuous Deployment Benefits of Infrastructure Automation Continuous Feedback Continuous Monitoring Continuous Operations Kubernetes Scalability What Is Kubernetes? Fundamental Architecture of Kubernetes Cluster Master Node Worker Node Hardened Installation of Kubernetes Perform the Following Steps on Master Node Perform the Following Steps on the Worker Node Kube-bench for Security of Kubernetes Cluster Steps to Set Kube-bench on Your Nodes Scaling of Kubernetes Recommended Practices for Kubernetes Scaling Manual Scaling What Is Autoscaling? Kubernetes Autoscaling Horizontal Pod Autoscaling (HPA) Description of Each Attribute Described in the Preceding YAML File Vertical Pod Autoscaling (VPA) Comparison of Monolithic and Public Managed Kubernetes Cluster Summary Chapter 3: Security in Cloud-Native Applications with a Shift-Left Approach Introduction to Shift-Left Security in Cloud Native Shift-Left Secure Right Risk from Third-Party Components Embracing Technologies to Shift Left 1. Static Application System Testing (SAST) 2. Dynamic Application Security Testing (DAST) 3. Interactive Application Security Testing (IAST) 4. Software Composition Analysis (SCA) 5. Runtime Application Self-protection (RASP) 6. IaC Scanning 7. Infrastructure Scanning 8. Compliance Check Security Testing with Shift-Left Approach Benefits of Shift-Left Strategy Infrastructure as Code (IaC) and Security Role of IaC in Cloud Native Security Strategy Using IaC for Organizations Tools for IaC Security IaC with Terraform Terraform Working Terraform Architecture IaC Tools Value Proposition of IaC Tools Best Practices for IaC Securing API in Early Stages Common API Risk Factors What Is API Security Testing? Securing API Using Pynt Working of Pynt Pynt Setup Pynt Security Testing Summary Chapter 4: CI/CD Pipeline in Cloud-Native DevOps Overview of CI/CD C1/CD Principles Principles of Continuous Integration Principles of Continuous Delivery CI/CD Pipeline Stages Source Stage Build Stage Test Stage Deploy Stage CI/CD Best Practices in Cloud Native Benefits of CI/CD in Cloud-Native DevOps Integration of Version Control Version Control Overview CI/CD Build Tool Implementation Cloud-Agnostic in CI/CD Pipeline CI/CD Pipeline Using Jenkins Security in CI/CD Threats in CI/CD Automated Tools for Securing CI/CD Pipeline Static Application Security Testing (SAST) Dynamic Application Security Testing (DAST) Interactive Application Security Testing (IAST) Securing a CI/CD Pipeline: Recommended Approaches Summary Chapter 5: Open-Source Tools for Cloud-Native DevOps Overview of Open-Source Tools in Cloud Native Argo Streamlining Workflows Getting Started with Argo Concepts of Argo CD Application Target State Argo Controller Sync Live State Refresh Implementation of Argo Workflows Using Custom Kubernetes Resources Implementation of CI/CD Through Argo Workflows Integration of Argo CD and Kubernetes Kubeflow Pipelines Kubeflow Overview Problem Identification Source, Prepare, and Analyze Data Kubeflow Principles Kubeflow Pipelines Kubeflow in Cloud Native Applications Future Trends in Cloud-Native DevOps Tools DataOps AIOps (Artificial Intelligence for IT Operations) Hyperautomation Adoption of Cloud-Native Technologies Infrastructure as Code (IaC) Management Artificial Intelligence (AI) Evolution Security and Compliance Collaboration Between DevOps Teams Fresh Dimension in Quantum Computing Adapting to Change Artificial Intelligence for IT Operations (AIOps) ChatOps GitOps No Operations (NoOps) Summary Chapter 6: Scalability and Autoscaling Strategies Scaling Principles in Cloud-Native Applications Utilizing Automation in Cloud-Native Architecture Several Key Areas Within Cloud-Native ­Architecture Are Ripe for Automation Infrastructure Provisioning and Management Monitoring and Remediation Continuous Integration/Continuous Delivery (CI/CD) Dynamic Scaling Multi-cloud Strategies Reactive and Preemptive Scaling Reactive Scaling Preemptive Scaling Cloud Native for Edge Computing Autoscaling Implementation in AWS Benefits of Autoscaling Steps to Create Autoscaling Future Trends in Scalability and Autoscaling Machine Learning-Driven Autoscaling Serverless Architectures and Event-Driven Scaling Edge Computing and Distributed Scaling Hybrid and Multi-cloud Scalability Cost-Efficient Autoscaling Strategies Summary Chapter 7: Collaborative Development in the Cloud Native Enabling Collaboration Between Developers and Operations DevOps Culture Agile and Scrum Methodology in Cloud Native Benefits of Agile Methodology Roles in Scrum Artifacts in Scrum Optimizing Cloud-Based Data Flow Data Pipeline Architecture Factors Prioritize Compliance in the Initial Stage Best Practices in Data Pipeline Architecture Consider Future Growth When Planning for Performance and Scalability ETL Processes and Supply Chain Management Transition from on-prem to ETL Securing Cloud-Integrated Logistics Operations Capabilities of Cloud Computing in Supply Chain Management Summary Chapter 8: IAM Security in Cloud- Native Environment IAM Fundamentals in Cloud-Native Environments Foundational Elements of Cloud-Native IAM Infrastructure Fundamental Pillars of IAM IAM Components Least Privileges Principles Implementation of Least Privileges IAM Best Practices for Service Accounts and API Access Key Components of User Management in Cloud-Native Applications Implementation of User Management in Cloud Native Secure Handling of API Keys Least Privilege for Service Accounts Difficulties Associated with Service Accounts Best Practices for Managing Service Accounts IAM Governance and Policy Management in Cloud Native Governance Risk Management Compliance IAM Standards Building Concrete IAM Summary Chapter 9: Threat Analysis for Cloud-Native Deployments Understanding Cloud-Native Security Challenges Type of Threats in Cloud Native Challenges in Cloud-Native Security 3R’s of Cloud-Native Security Security Controls in Cloud Native Threat Vectors in Microservices Architectures Threat Modeling with STRIDE Security Testing and Validation Red Teaming in Cloud Native Implementation Steps Best Practices in Cloud-Native Security Conduct Due Diligence Audit and Improve Configurations Security Controls and Countermeasures Key Management in Cloud Native Summary Chapter 10: Future Trends in Cloud Native Serverless Computing and Function as a Service (FaaS) Benefits of Serverless Computing Function as a Service (FaaS) Benefits of FaaS Best Practices for FaaS Key Challenges in Serverless Computing AI and Machine Learning Integration Intersection in Cloud Native Challenges and Considerations Implementing AI in Cloud Native Challenges in Security and Compliance Complexity in Deployment and Model Training Obstacles in Data Integration Scalability Management Best Practices of Integrating AI/ML in Cloud Native Evolution of Containerization Technologies Beyond Docker and Kubernetes The Rise of No-Code/Low-Code Platforms in DevOps Workflows Benefits of No Code and Low Code Use of No Code and Low Code Summary Index This book delivers cloud-based applications that are both scalable and reliable, aligning with the evolving needs of the present user base. This innovative approach blends the agility of cloud computing with the efficiency of contemporary DevOps methodologies.The book starts by providing valuable insights into the ever-evolving software landscape of Cloud-native DevOps. It delves into strategies for crafting scalable and dependable applications and illustrates the art of leveraging open-source tools to enhance collaboration. It navigates through the integral role of microservices in contemporary software development and imparts the know-how to integrate them with DevOps practices. The book simplifies container technology, with a focus on Docker and Kubernetes. It further elucidates the process of streamlining software delivery through Continuous Integration and Continuous Deployment (CI/CD). As you progress, you will explore open-source tools, including Argo, Kubeflow Pipelines, and AWS Step Functions. The concluding section covers real-world case studies and best practices for implementing Cloud-native DevOps. The book reviews the core concepts covered throughout and provides an exciting glimpse into the future of Cloud-native DevOps.Upon completing this book, you will be well-versed in the principles and practices of Cloud-native DevOps, understand real-world applications, and recognize the critical importance of security in cloud computing.What You Will LearnCreate cloud-based applications that can scale with the changing needs of today's user baseCombine the flexibility of cloud computing with the efficiency of modern DevOps methodologiesUnderstand the core concepts and principles of Cloud-native DevOpsUnderstand microservices, containers, and continuous integration and continuous deployment (CI/CD)Who This Book Is ForDevOps engineers, cloud architects, software developers, system administrators, IT managers, team leads, and business decision makers