The white paper "Knative Cookbook (By O’Reilly): Building Effective Serverless Applications with Kubernetes and OpenShift – Download Now" is no longer available on Infoq.com; However we invite you to explore the related content below.
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Architecting for Reactive Microservices - an O'Reilly book pack. Download now.
In these concise O'Reilly reports, Jonas Bonér, co-author of the Reactive Manifesto & creator of the Akka project, provides architects and technology leaders with an overview of the principles and strategies they should consider when designing systems of microservices for cloud native applications.
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O'Reilly: Architecting for Scale (Two Free Chapter Excerpts) - Download Now
Learn techniques for building systems that can handle huge quantities of traffic, data, and demand—without affecting the quality your customers expect. Architects, managers, directors in engineering and operations organizations will learn how to build applications at scale that run more smoothly.
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Knative Cookbook (By O’Reilly): Building Effective Serverless Applications with Kubernetes and OpenShift – Download Now
Learn now Knative - the first serverless platform natively designed for Kubernetes - can help you solve common issues building serverless applications such as integrating applications and building container images from source. Explore more than 60 practical recipes.
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Forrester Thought Leadership Paper: Building Value Streams with Feature Management Platforms
Read this paper to learn how testing in production is critical to successful software development, why complexity, silos, and poor cross-team collaboration slow development, and how Feature Management platforms are seen as the key to breaking barriers.
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5 Reasons You Want an Out-of-the-Box Identity Service
With a secure identity service, developers are freed up to spend more time on core functionality and less time on security. Plus, it’s easier to launch applications that are secure out of the box. Customers can have seamless experiences, they engage more, and your project realizes greater ROI.
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Serving Machine Learning Models: A Guide to Architecture, Stream Processing Engines, and Frameworks
This practical report introduces architecture for serving models in real time as part of input stream processing. This approach would also enable data science teams to update models without restarting existing applications.
