Book Image

Multi-Cloud Handbook for Developers

By : Subash Natarajan, Jeveen Jacob
Book Image

Multi-Cloud Handbook for Developers

By: Subash Natarajan, Jeveen Jacob

Overview of this book

Unleash the power of cloud computing with Multi-Cloud Handbook for Developers, your guide to mastering the nuances of cloud-native and multi-cloud, covering practical strategies for design, development, and management. Explore the essential concepts, challenges, and methodologies critical for navigating the complex landscape of modern cloud computing. Using core architectural and design principles (such as microservices and 12-factor architecture) and advanced strategies (such as distributed application design patterns, domain-driven design (DDD), and API-first strategies), you’ll learn how to build portable and efficient apps across various cloud platforms. You’ll understand how to leverage Infrastructure as Code (IaC), continuous integration and deployment (CI/CD), GitOps, and DevOps practices, along with containerization and orchestration techniques using Docker and Kubernetes. You’ll also get to grips with data, security, compliance, and cloud cost management strategies in multi-cloud environments. With real-world case studies, best practices, and insights into future trends, this book will equip you with the skills to develop, manage, troubleshoot, and innovate cloud-native applications across diverse cloud platforms, positioning you at the forefront of the cloud computing revolution.
Table of Contents (17 chapters)
1
Part 1:Introduction to Multi-Cloud and Cloud-Native
4
Part 2: Designing and Developing Cloud-Native Applications for Multi-Cloud
7
Part 3: Managing and Operating Cloud-Native Apps in Multi-Cloud
11
Part 4: Best Practices, Case Studies, and Future Trends for Multi-Cloud and Cloud-Native

Practical examples: building effective cloud-native applications

Now that we know what points to consider while building a cloud-native application, let’s consider a few examples to understand them:

  • Internet of Things (IoT) sensor data analytics platform: Imagine you’re developing an IoT platform that collects data from thousands of sensors deployed in various locations. This platform needs to efficiently gather, process, and analyze sensor data in real time to provide insights and trigger actions. In this scenario, a combination of programming languages and frameworks can be utilized:
    • Java for scalability: Java is known for its robustness and scalability. It could be used for building the backend services of the IoT platform, especially when dealing with a large number of sensor data inputs. The use of Java’s multithreading capabilities can help handle concurrent data streams effectively.
    • Apache Kafka for data streaming: Apache Kafka, often used with Java...