Books by Jeff Carpenter

Is Kubernetes ready for stateful workloads? This open source system has become the primary platform for deploying and managing cloud native applications. But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging. If you want to avoid the inefficiencies and duplicative costs of having separate infrastructure for applications and data, this practical guide can help.Using Kubernetes as your platform, you'll learn open source technologies that are designed and built for the cloud. Authors Jeff Carpenter and Patrick McFadin provide case studies to help you explore new use cases and avoid the pitfalls others have faced. Youll get an insider's view of what's coming from innovators who are creating next-generation architectures and infrastructure.With this book, you will:Learn how to use basic Kubernetes resources to compose data infrastructureAutomate the deployment and operations of data infrastructure on Kubernetes using tools like Helm and operatorsEvaluate and select data infrastructure technologies for use in your applicationsIntegrate data infrastructure technologies into your overall stackExplore emerging technologies that will enhance your Kubernetes-based applications in the future

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This revised third edition--updated for Cassandra 4.0 and new developments in the Cassandra ecosystem, including deployments in Kubernetes with K8ssandra--provides technical details and practical examples to help you put this database to work in a production environment.Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. Developers, DBAs, and application architects looking to solve a database scaling issue or future-proof an application will learn how to harness Cassandra's speed and flexibility.Understand Cassandra's distributed and decentralized structureUse the Cassandra Query Language (CQL) and cqlsh (the CQL shell)Create a working data model and compare it with an equivalent relational modelDesign and develop applications using client driversExplore cluster topology and learn how nodes exchange dataMaintain a high level of performance in your clusterDeploy Cassandra onsite, in the cloud, or with Docker and KubernetesIntegrate Cassandra with Spark, Kafka, Elasticsearch, Solr, and Lucene