Cloud-Native DevOps: Building Scalable and Reliable Applications

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)   Who This Book Is For DevOps engineers, cloud architects, software developers, system administrators, IT managers, team leads, and business decision makers