Explainable Machine Learning in Medicine

Cloud native development gives you the power to rapidly build, secure, and scale software. But you still need to navigate many potential pitfalls along the way. Through practical examples, this book demonstrates how to use Google Cloud as a laboratory to enable rapid innovation, a factory to automate toil, a resilient, scalable, and secure citadel for running applications, and an observatory to observe them. Author Daniel Vaughan shows you how to take applications from prototype to production by combining Google Cloud services, a cloud native programming model, and best practices. By following an example project from start to finish, developers, architects, and engineering managers working with the Google Cloud Platform will learn how to build and run cloud native applications on Google Cloud with confidence. Understand cloud native development concepts from microservices and containerization to architecture best practices and cost optimization Learn Google Cloud services that specifically support this development style: compute, persistence, messaging, DevOps, security and networking, and observability Confidently build cloud native applications on Google Cloud Learn how to address nonfunctional requirements such as security, observability, and testing Successfully make the transition from initial proofs of concept and prototypes to production systems