Generative Ai With Kubernetes

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Generative Ai With Kubernetes

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Author : Jonathan Baier
language : en
Publisher: BPB Publications
Release Date : 2025-02-28

Generative Ai With Kubernetes written by Jonathan Baier and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-28 with Computers categories.

DESCRIPTION Over the past few years, we have seen leaps and strides in ML and most recently generative AI. Companies and software teams are rushing to enhance, rebuild, and create new software offerings with this new intelligence. As they innovate and create delightful new experiences for their customers new challenges arise. Understanding how these applications work and how to use state-of-the-art infrastructure tools like Kubernetes will help organizations and professionals succeed with this new technology. The book covers essential technical implementations from ML fundamentals through advanced deployment strategies, focusing on practical patterns. Core topics include Kubernetes-native GPU scheduling and resource management, MLOps pipeline architectures using Kubeflow/MLflow, and advanced model serving patterns. It details data management architectures, vector databases, and RAG systems, alongside monitoring solutions with Prometheus/Grafana. Finally, we will look at some advanced concerns for production in the realm of security and data reliability. After reading this book, you will be equipped with a broad knowledge of the end-to-end generative AI pipeline and how Kubernetes can be leveraged to run your generative AI workloads at scale in the real-world. KEY FEATURES ● Learn how Kubernetes can help you run your generative AI workloads. ● Using hands-on examples, you will work with real-world foundational models and a variety of tools and capabilities in the K8s ecosystem. ● A broad survey of both generative AI and Kubernetes in one book. WHAT YOU WILL LEARN ● How to evaluate and compare models for new applications and use cases. ● How Kubernetes can add reliability and scale to your AI applications. ● What does an AI delivery pipeline contain and how to start one. ● How AI models encode words and work with natural language. ● How prompting and refinement techniques can improve results. ● How to use your own data to augment AI responses. WHO THIS BOOK IS FOR This book is for teams building new applications or new functionality with generative AI, but want to better understand the infrastructure needed to bring their AI applications to production. This book is also for shared services, infrastructure, or cybersecurity teams who provide platforms and infrastructure for application, or product development. TABLE OF CONTENTS 1. Introduction to Generative Artificial Intelligence 2. Kubernetes for Generative AI 3. Introduction to Foundational Models on Kubernetes 4. Working with Foundational Models 5. Process and Pipelines 6. Process and Pipelines on Kubernetes 7. Managing Data for Generative AI 8. Refining and Improving Results 9. Observability and Monitoring 10. Securing ML/GenAI Pipelines on K8s

Kubernetes For Generative Ai Solutions

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Author : Ashok Srirama
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-06-06

Kubernetes For Generative Ai Solutions written by Ashok Srirama and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.

Master the complete Generative AI project lifecycle on Kubernetes (K8s) from design and optimization to deployment using best practices, cost-effective strategies, and real-world examples. Key Features Build and deploy your first Generative AI workload on Kubernetes with confidence Learn to optimize costly resources such as GPUs using fractional allocation, Spot Instances, and automation Gain hands-on insights into observability, infrastructure automation, and scaling Generative AI workloads Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGenerative AI (GenAI) is revolutionizing industries, from chatbots to recommendation engines to content creation, but deploying these systems at scale poses significant challenges in infrastructure, scalability, security, and cost management. This book is your practical guide to designing, optimizing, and deploying GenAI workloads with Kubernetes (K8s) the leading container orchestration platform trusted by AI pioneers. Whether you're working with large language models, transformer systems, or other GenAI applications, this book helps you confidently take projects from concept to production. You’ll get to grips with foundational concepts in machine learning and GenAI, understanding how to align projects with business goals and KPIs. From there, you'll set up Kubernetes clusters in the cloud, deploy your first workload, and build a solid infrastructure. But your learning doesn't stop at deployment. The chapters highlight essential strategies for scaling GenAI workloads in production, covering model optimization, workflow automation, scaling, GPU efficiency, observability, security, and resilience. By the end of this book, you’ll be fully equipped to confidently design and deploy scalable, secure, resilient, and cost-effective GenAI solutions on Kubernetes.What you will learn Explore GenAI deployment stack, agents, RAG, and model fine-tuning Implement HPA, VPA, and Karpenter for efficient autoscaling Optimize GPU usage with fractional allocation, MIG, and MPS setups Reduce cloud costs and monitor spending with Kubecost tools Secure GenAI workloads with RBAC, encryption, and service meshes Monitor system health and performance using Prometheus and Grafana Ensure high availability and disaster recovery for GenAI systems Automate GenAI pipelines for continuous integration and delivery Who this book is for This book is for solutions architects, product managers, engineering leads, DevOps teams, GenAI developers, and AI engineers. It's also suitable for students and academics learning about GenAI, Kubernetes, and cloud-native technologies. A basic understanding of cloud computing and AI concepts is needed, but no prior knowledge of Kubernetes is required.

Keras To Kubernetes

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Author : Dattaraj Rao
language : en
Publisher: John Wiley & Sons
Release Date : 2019-05-07

Keras To Kubernetes written by Dattaraj Rao and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-07 with Computers categories.

Build a Keras model to scale and deploy on a Kubernetes cluster We have seen an exponential growth in the use of Artificial Intelligence (AI) over last few years. AI is becoming the new electricity and is touching every industry from retail to manufacturing to healthcare to entertainment. Within AI, were seeing a particular growth in Machine Learning (ML) and Deep Learning (DL) applications. ML is all about learning relationships from labeled (Supervised) or unlabeled data (Unsupervised). DL has many layers of learning and can extract patterns from unstructured data like images, video, audio, etc. em style="box-sizing: border-box;"Keras to Kubernetes: The Journey of a Machine Learning Model to Production takes you through real-world examples of building DL models in Keras for recognizing product logos in images and extracting sentiment from text. You will then take that trained model and package it as a web application container before learning how to deploy this model at scale on a Kubernetes cluster. You will understand the different practical steps involved in real-world ML implementations which go beyond the algorithms. Find hands-on learning examples Learn to uses Keras and Kubernetes to deploy Machine Learning models Discover new ways to collect and manage your image and text data with Machine Learning Reuse examples as-is to deploy your models Understand the ML model development lifecycle and deployment to production If youre ready to learn about one of the most popular DL frameworks and build production applications with it, youve come to the right place!

Big Data On Kubernetes

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Author : Neylson Crepalde
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-19

Big Data On Kubernetes written by Neylson Crepalde and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-19 with Computers categories.

Gain hands-on experience in building efficient and scalable big data architecture on Kubernetes, utilizing leading technologies such as Spark, Airflow, Kafka, and Trino Key Features Leverage Kubernetes in a cloud environment to integrate seamlessly with a variety of tools Explore best practices for optimizing the performance of big data pipelines Build end-to-end data pipelines and discover real-world use cases using popular tools like Spark, Airflow, and Kafka Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn today's data-driven world, organizations across different sectors need scalable and efficient solutions for processing large volumes of data. Kubernetes offers an open-source and cost-effective platform for deploying and managing big data tools and workloads, ensuring optimal resource utilization and minimizing operational overhead. If you want to master the art of building and deploying big data solutions using Kubernetes, then this book is for you. Written by an experienced data specialist, Big Data on Kubernetes takes you through the entire process of developing scalable and resilient data pipelines, with a focus on practical implementation. Starting with the basics, you’ll progress toward learning how to install Docker and run your first containerized applications. You’ll then explore Kubernetes architecture and understand its core components. This knowledge will pave the way for exploring a variety of essential tools for big data processing such as Apache Spark and Apache Airflow. You’ll also learn how to install and configure these tools on Kubernetes clusters. Throughout the book, you’ll gain hands-on experience building a complete big data stack on Kubernetes. By the end of this Kubernetes book, you’ll be equipped with the skills and knowledge you need to tackle real-world big data challenges with confidence.What you will learn Install and use Docker to run containers and build concise images Gain a deep understanding of Kubernetes architecture and its components Deploy and manage Kubernetes clusters on different cloud platforms Implement and manage data pipelines using Apache Spark and Apache Airflow Deploy and configure Apache Kafka for real-time data ingestion and processing Build and orchestrate a complete big data pipeline using open-source tools Deploy Generative AI applications on a Kubernetes-based architecture Who this book is for If you’re a data engineer, BI analyst, data team leader, data architect, or tech manager with a basic understanding of big data technologies, then this big data book is for you. Familiarity with the basics of Python programming, SQL queries, and YAML is required to understand the topics discussed in this book.

Generative Ai Security

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Author : Ken Huang
language : en
Publisher: Springer Nature
Release Date : 2024-04-05

Generative Ai Security written by Ken Huang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-05 with Business & Economics categories.

This book explores the revolutionary intersection of Generative AI (GenAI) and cybersecurity. It presents a comprehensive guide that intertwines theories and practices, aiming to equip cybersecurity professionals, CISOs, AI researchers, developers, architects and college students with an understanding of GenAI’s profound impacts on cybersecurity. The scope of the book ranges from the foundations of GenAI, including underlying principles, advanced architectures, and cutting-edge research, to specific aspects of GenAI security such as data security, model security, application-level security, and the emerging fields of LLMOps and DevSecOps. It explores AI regulations around the globe, ethical considerations, the threat landscape, and privacy preservation. Further, it assesses the transformative potential of GenAI in reshaping the cybersecurity landscape, the ethical implications of using advanced models, and the innovative strategies required to secure GenAI applications. Lastly, the book presents an in-depth analysis of the security challenges and potential solutions specific to GenAI, and a forward-looking view of how it can redefine cybersecurity practices. By addressing these topics, it provides answers to questions on how to secure GenAI applications, as well as vital support with understanding and navigating the complex and ever-evolving regulatory environments, and how to build a resilient GenAI security program. The book offers actionable insights and hands-on resources for anyone engaged in the rapidly evolving world of GenAI and cybersecurity.

The Future Of Cloud Integrating Ai Ml And Generative Ai For Scalable Solutions

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Author : Chandrakanth Rao Madhavaram
language : en
Publisher: JEC PUBLICATION
Release Date :

The Future Of Cloud Integrating Ai Ml And Generative Ai For Scalable Solutions written by Chandrakanth Rao Madhavaram and has been published by JEC PUBLICATION this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

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Generative Ai With Python And Tensorflow 2

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Author : Joseph Babcock
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-04-30

Generative Ai With Python And Tensorflow 2 written by Joseph Babcock and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-30 with Computers categories.

This edition is heavily outdated and we have a new edition with PyTorch examples published! Key Features Code examples are in TensorFlow 2, which make it easy for PyTorch users to follow along Look inside the most famous deep generative models, from GPT to MuseGAN Learn to build and adapt your own models in TensorFlow 2.x Explore exciting, cutting-edge use cases for deep generative AI Book DescriptionMachines are excelling at creative human skills such as painting, writing, and composing music. Could you be more creative than generative AI? In this book, you’ll explore the evolution of generative models, from restricted Boltzmann machines and deep belief networks to VAEs and GANs. You’ll learn how to implement models yourself in TensorFlow and get to grips with the latest research on deep neural networks. There’s been an explosion in potential use cases for generative models. You’ll look at Open AI’s news generator, deepfakes, and training deep learning agents to navigate a simulated environment. Recreate the code that’s under the hood and uncover surprising links between text, image, and music generation.What you will learn Export the code from GitHub into Google Colab to see how everything works for yourself Compose music using LSTM models, simple GANs, and MuseGAN Create deepfakes using facial landmarks, autoencoders, and pix2pix GAN Learn how attention and transformers have changed NLP Build several text generation pipelines based on LSTMs, BERT, and GPT-2 Implement paired and unpaired style transfer with networks like StyleGAN Discover emerging applications of generative AI like folding proteins and creating videos from images Who this book is for This is a book for Python programmers who are keen to create and have some fun using generative models. To make the most out of this book, you should have a basic familiarity with math and statistics for machine learning.

Cloud Native Devops With Kubernetes

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Author : John Arundel
language : en
Publisher: O'Reilly Media
Release Date : 2019-03-08

Cloud Native Devops With Kubernetes written by John Arundel and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-08 with Computers categories.

Kubernetes is the operating system of the cloud native world, providing a reliable and scalable platform for running containerized workloads. In this friendly, pragmatic book, cloud experts John Arundel and Justin Domingus show you what Kubernetes can do—and what you can do with it. You’ll learn all about the Kubernetes ecosystem, and use battle-tested solutions to everyday problems. You’ll build, step by step, an example cloud native application and its supporting infrastructure, along with a development environment and continuous deployment pipeline that you can use for your own applications. Understand containers and Kubernetes from first principles; no experience necessary Run your own clusters or choose a managed Kubernetes service from Amazon, Google, and others Use Kubernetes to manage resource usage and the container lifecycle Optimize clusters for cost, performance, resilience, capacity, and scalability Learn the best tools for developing, testing, and deploying your applications Apply the latest industry practices for security, observability, and monitoring Adopt DevOps principles to help make your development teams lean, fast, and effective

Core Kubernetes

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Author : Jay Vyas
language : en
Publisher: Simon and Schuster
Release Date : 2022-07-26

Core Kubernetes written by Jay Vyas and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-26 with Computers categories.

Take a deep dive into Kubernetes inner components and discover what really powers a Kubernetes cluster. This in-depth guide shines a light on Kubernetes' murky internals, to help you better plan cloud native architectures and ensure the reliability of your systems. In Core Kubernetes you will learn about: Kubernetes base components Kubernetes networking Storage and the Container Storage Interface External load balancing and ingress Kubernetes security Different ways of creating a Kubernetes cluster Configuring Kubernetes to use a GPU To build and operate reliable Kubernetes-based systems, you need to understand what’s going on below the surface. Core Kubernetes is an in-depth guide to Kubernetes’ internal workings written by Kubernetes contributors Chris Love and Jay Vyas. It’s packed with experience-driven insights and advanced techniques you won’t find anywhere else. You’ll understand the unique security concerns of container-based applications, minimize costly unused capacity, and get pro tips for maximizing performance. Diagrams, labs, and hands-on examples ensure that the complex ideas are easy to understand and practical to apply. About the technology Real-world Kubernetes deployments are messy. Even small configuration errors or design problems can bring your system to its knees. In the real world, it pays to know how each component works so you can quickly troubleshoot, reset, and get on to the next challenge. This one-of-a-kind book includes the details, hard-won advice, and pro tips to keep your Kubernetes apps up and running. About the book This book is a tour of Kubernetes under the hood, from managing iptables to setting up dynamically scaled clusters that respond to changes in load. Every page will give you new insights on setting up and managing Kubernetes and dealing with inevitable curveballs. Core Kubernetes is a comprehensive reference guide to maintaining Kubernetes deployments in production. What's inside Kubernetes base components Storage and the Container Storage Interface Kubernetes security Different ways of creating a Kubernetes cluster Details about the control plane, networking, and other core components About the reader For intermediate Kubernetes developers and administrators. About the author Jay Vyas and Chris Love are seasoned Kubernetes developers. Table of Contents 1 Why Kubernetes exists 2 Why the Pod? 3 Let’s build a Pod 4 Using cgroups for processes in our Pods 5 CNIS and providing the Pod with a network 6 Troubleshooting large-scale network errors 7 Pod storage and the CSI 8 Storage implementation and modeling 9 Running Pods: How the kubelet works 10 DNS in Kubernetes 11 The core of the control plane 12 etcd and the control plane 13 Container and Pod security 14 Nodes and Kubernetes security 15 Installing applications

Artificial Intelligence Applications And Innovations Aiai 2025 Ifip Wg 12 5 International Workshops

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Author : Antonios Papaleonidas
language : en
Publisher: Springer Nature
Release Date : 2025-06-25

Artificial Intelligence Applications And Innovations Aiai 2025 Ifip Wg 12 5 International Workshops written by Antonios Papaleonidas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-25 with Computers categories.

This 2-volume set constitutes the refereed proceedings of International Workshops, held as parallel events of the 21st IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2025, held in Limassol, Cyprus, during June 26–29, 2025. The 44 full papers and 6 short papers presented in these proceedings were carefully reviewed and selected from 117 submissions. The AIAI 2025 conference hosts several workshops that support innovative research on various specific and hot scientific domains every year. These satellite events offer a deep insight into both rapid advances and timely creative applications of AI.