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Learn how to leverage Kubernetes for early adoption of emerging technologies. Kubernetes has become the most popular and, often considered, the most robust container orchestration system available today. With a vast number of features and capabilities that extend far beyond the simple execution of containerized applications, Kubernetes is the future of enterprise platform development. This book focuses on the Internet of Things, Blockchain, and Machine Learning as the industries currently leveraging the capabilities of Kubernetes. Advanced Platform Development with Kubernetes takes you through the process of building software platforms with these in-demand capabilities. You'll progress through the development of data processing pipelines, event queues and indexing large volumes of raw data and metrics. Each concept is demonstrated through examples using Apache Kafka for real-time event data, Ethereum for Blockchain capabilities, Elasticsearch for data indexing, Logstash to route and transform data, Prometheus and Loki to aggregate metrics and Grafana for metrics visualization. The book uses Golang to demonstrate interactions with the Kubernetes API, support Python and an assortment of languages implemented in Serverless Functions, and then ties these concepts together with a data science layer for machine learning with Kubeflow. The examples and exercises throughout teach Kubernetes through the lens of platform development and express the power and flexibility of Kubernetes in clear and pragmatic examples. Discover why Kubernetes is an excellent choice for any individual or organization looking to embark on developing a successful software platform. What You'll Learn Configure Kubernetes to support common platform requirements, including resource management and security Develop a development toolchain for continuous integration and deployment Use data pipelines with Logstash, Kafka and Elasticsearch Apply a Serverless platform with OpenFaaS and Kubeless Leverage Blockchain capabilities with Ethereum and Hyperledger Implement a data science platform with Kubeflow Extend Kubernetes with Custom Resource Definitions and command line utilities Who This Book Is For System architects, full-stack developers, programmers, and DevOps engineers with some experience with building and using containers. This book also targets readers who have started with Kubernetes and need to progress from a basic understanding of the technology and "Hello World" example to more productive, career building implementations.