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Full Description
Leverage Kubernetes for the rapid adoption of emerging technologies. Kubernetes is the future of enterprise platform development and has become the most popular, and often considered the most robust, container orchestration system available today. This book focuses on platforming technologies that power the Internet of Things, Blockchain, Machine Learning, and the many layers of data and application management supporting them.
Advanced Platform Development with Kubernetes takes you through the process of building platforms with these in-demand capabilities. You'll progress through the development of Serverless, CICD integration, data processing pipelines, event queues, distributed query engines, modern data warehouses, data lakes, distributed object storage, indexing and analytics, data routing and transformation, query engines, and data science/machine learning environments. You'll also see how to implement and tie together numerous essential and trending technologies including: Kafka, NiFi, Airflow, Hive, Keycloak, Cassandra, MySQL, Zookeeper, Mosquitto, Elasticsearch, Logstash, Kibana, Presto, Mino, OpenFaaS, and Ethereum.
The book uses Golang and Python to demonstrate the development integration of custom container and Serverless functions, including interaction with the Kubernetes API. The exercises throughout teach Kubernetes through the lens of platform development, expressing the power and flexibility of Kubernetes with clear and pragmatic examples. Discover why Kubernetes is an excellent choice for any individual or organization looking to embark on developing a successful data and application platform.
What You'll Learn
Configure and install Kubernetes and k3s on vendor-neutral platforms, including generic virtual machines and bare metal
Implement an integrated development toolchain for continuous integration and deployment
Use data pipelines with MQTT, NiFi,Logstash, Kafka and Elasticsearch
Install a serverless platform with OpenFaaS
Explore blockchain network capabilities with Ethereum
Support a multi-tenant data science platform and web IDE with JupyterHub, MLflow and Seldon Core
Build a hybrid cluster, securely bridging on-premise and cloud-based Kubernetes nodes
Who This Book Is For
System and software architects, full-stack developers, programmers, and DevOps engineers with some experience 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 projects.
Contents
Chapter 1: Software Platform and the API.- Chapter 2: DevOps Infrastructure.- Chapter 3: Development Environment.- Chapter 4: In Platform CI/CD.- Chapter 5: Pipeline.- Chapter 6: Indexing and Analytics.- Chapter 7: Data Lakes.- Chapter 8: Data Warehouses.- Chapter 9: Routing and Transformation.- Chapter 10: Platforming Blockchain.- Chapter 11: Platforming AIML.
