A practical guide to building a modern, GenAI-powered data platform with a Lakehouse foundation, covering MDM, data mesh, AI enablement, streaming pipelines, observability, and cloud-driven architectures for trusted analytics.

Key Features

• Discover characteristics of future-ready platforms - data mesh, automation, & observability
• Design trustworthy data products with contracts, federated governance, and decentralized ownership
• Understand how GenAI accelerates Lakehouse development and enables self-service analytics

Book Description

What you will learn

• Future-ready platforms: data mesh, automation, observability
• Design trusted data products with contracts and governance
• Build Lakehouses with medallion architecture: bronze, silver, gold
• Apply Unity Catalog for governance and endorsed datasets
• Implement MDM using linkages, survivorship, and entity resolution
• Develop real-time and streaming pipelines at scale
• Enable governed self-service analytics for business users
• Use GenAI to generate code with Claude and Databricks Genie

Who this book is for

This book is crafted for aspiring data and AI/ML architects, engineers and analysts starting their data engineering journey and seeking a practical, hands-on guide to building scalable, cloud-driven data platforms. It’s ideal for professionals familiar with PySpark who want to design modern Lakehouse architectures using Delta Lake, while learning MDM, data mesh, AI enablement, streaming pipelines, automation, and data observability. A working knowledge of Python, Spark, and SQL is expected.

Description
Traditional monolithic architectures struggle to scale with multi-team development, frequent deployments, and diverse tech stacks. This book serves as a comprehensive, hands-on roadmap for frontend developers and architects to break down these monoliths into modular, independently deployable, and technology-agnostic components.

Structured around a complete multi-framework e-commerce app built incrementally throughout the book, this project-backed book combines practical coding with cutting-edge tooling. You will start by building a React 18 host shell, then master dynamic runtime module integration using Webpack 5 Module Federation, Vite, and ultra-fast Bun local builds. The chapters walk you through managing distributed workspaces via Nx and Turborepo monorepos, seamlessly embedding Vue, Angular 15, and Svelte 4 modules, and eliminating style bleeding with isolated Tailwind CSS design systems. Finally, you will implement interface contract testing and orchestrate automated, independent cloud deployments using Docker, Kubernetes, and GitHub Actions pipelines to AWS, Azure, and GCP.

By the end of this book, you will transcend single-framework limitations and possess the high-level competency required to confidently engineer, scale, and govern production-ready microfrontend architectures in real-world enterprise environments.

Description
As large language models continue to transform how we build intelligent systems, the ability to integrate proprietary data through vector search and RAG has become essential for creating accurate, contextually-aware applications that go beyond the limitations of pre-trained models

This comprehensive guide takes you from foundational concepts to production-ready implementations of vector databases and RAG systems. Starting with vector semantics and embeddings, you will learn to generate vector representations using neural networks, BERT, and OpenAI models. The book covers popular vector databases including Weaviate and Milvus, teaching you how to implement efficient search algorithms like k-nearest neighbors and hierarchical navigable small worlds. You will build complete RAG pipelines, explore advanced techniques like GraphRAG, and master evaluation frameworks using LlamaIndex. Each chapter includes hands-on Python examples with practical code implementations that demonstrate real-world applications.

By the end of this book, you will have mastered the skills needed to design, build, and evaluate production-grade vector search systems and RAG applications. You will be equipped to enhance LLM applications with private data, implement semantic search at scale, troubleshoot retrieval issues, and solve real-world information retrieval challenges using cutting-edge AI techniques with confidence.

Description
The field of artificial intelligence is undergoing a paradigm shift, moving beyond instruction-based generative AI to intent-driven agentic AI. This new frontier is defined by autonomous systems that can independently reason, plan, and act to achieve complex goals, serving as a strategic imperative that promises to redefine operational efficiency for the modern enterprise.

This book provides a hands-on playbook for architects and technology leaders to move from prototypes to robust, enterprise-grade agentic applications. It guides you through the lifecycle of building autonomous systems, mastering durable patterns like Coordinator-Worker-Delegator (CWD), building for interoperability using the open-standard Agent Communication Protocol (ACP), and mitigating security threats with a formal Agentic Risk Framework.

By the end of this book, you will be equipped with the expert knowledge required to architect, build, deploy, and govern sophisticated, scalable, and value-driven agentic AI systems that deliver tangible results in real-world enterprise environments.

Description
Apache Airflow cemented its position as the de facto workflow automation and data orchestration tool; hence, mastering Airflow has become critical for ensuring data reliability and operational efficiency. As Airflow enters the version 3.0 era, shifting towards a decentralized, service-oriented architecture with a native focus on data assets, staying ahead of its design patterns is important for modern data teams.

This book provides a comprehensive journey through the modern patterns of data orchestration. Readers will start with the origins and architecture of Airflow, followed by installation and configuration, core and special features, logging and monitoring, and popular managed versions. Each chapter delivers practical and hands-on insights that will help readers to practice side-by-side.

By the end of this book, readers will possess the practical competencies required to design, develop, test, and deploy production-grade pipelines. Readers will also gain invaluable skills in the latest asset-centric development, micro-orchestration, and modern CI/CD practices, turning them into highly capable engineers ready to tackle complex, enterprise-scale data infrastructure challenges.

Description
Most software engineers can build features. Far fewer can design the entire platform behind them, end-to-end, in production. Cloud architecture has become the defining skill of a senior engineer, yet most resources teach it in fragments, leaving you to assemble the full picture on your own.

Drawing on decades of enterprise architecture experience, the authors provide a complete, end-to-end blueprint. You begin with the foundations: core pillars (availability, performance, security, observability, cost, and sustainability), design patterns, methods, technology selection, and adaptive architecture, taught through one running case study, Aethera Airlines. Then you design nine real-world systems from the ground up: UPI payments, a trading platform, OTT streaming, a collaborative document editor, an agentic LLM-powered recommendation engine, plus chat, social media, ride-sharing, and a URL shortener. Throughout, you apply domain-driven design, API-first thinking, capacity planning, and multi-cloud cost trade-offs, with hands-on exercises and design challenges for each of the nine systems.

By the end, you will think and build like a cloud architect: engineering fault-tolerant, secure, and observable platforms on any major cloud, and ready for senior system design interviews at top tech companies.

Description
Domain-Driven Design (DDD) is a software development philosophy centered on aligning complex codebases with the core business domain. By establishing a Ubiquitous Language shared between developers and domain experts, it bridges the gap between technical implementation and business strategy.

This book serves as a practical, accessible guide to mastering the art of translating business needs into clean, adaptable code. It explores the historical context and foundational principles of DDD, emphasizing the collaborative communication required to build a shared understanding of the domain. The text delves deeply into both Strategic and Tactical Design, using real-world case studies and concrete examples to illustrate how to model complex business processes. Additionally, it addresses practical challenges, such as managing organizational complexities, handling legacy systems, and integrating DDD with Agile or Lean methodologies.

By the end of this book, you will understand how to define domains, map system relationships, and utilize Tactical Design patterns to implement robust business rules in code. You will know how to iteratively refine software models through refactoring to ensure they remain aligned with evolving business goals. Ultimately, you will be equipped with the mindset and practical skills needed to overcome real-world architectural complexities, leverage modern software methodologies, and cultivate the collaborative art of building highly valuable software solutions.

Description
Kubernetes has become the leading platform for deploying and managing containerized applications in modern enterprise environments. As organizations continue adopting cloud-native architectures, securing Kubernetes infrastructure and workloads has become a critical requirement. The Certified Kubernetes Security Specialist (CKS) certification validates the practical skills required to secure Kubernetes environments and implement security best practices.

This book is a practical study guide designed to help readers prepare for the CKS exam through hands-on learning and real-world scenarios. It covers cluster hardening, RBAC, service accounts, pod security, supply chain security, runtime security, network policies, logging, monitoring, and policy enforcement. The book includes practical labs, troubleshooting exercises, sample questions, exam-focused scenarios, preparation strategies, and full-length practice papers designed to mirror real certification challenges.

By the end of this book, readers will gain the confidence to secure Kubernetes environments and handle real-world security challenges. DevOps engineers, platform engineers, cloud architects, and security engineers will develop practical skills needed to succeed in the CKS certification and beyond.

Description
This book argues that AI is not simply software running on infrastructure; it is reshaping the infrastructure itself. As compute scales from megawatts to gigawatts, data centers evolve into AI factories, where energy, data, and silicon are fused into systems that continuously produce intelligence.

The book presents AI factories as the industrial backbone of the intelligence age, built on the foundational pillars of compute, network, power, sustainability, security, and governance. It moves from the foundations of AI factories, exascale computing, compute sovereignty, and efficient compute systems into multi-layered architectures, secure training systems, AI networking, power systems, autonomous grid systems, advanced cooling technologies, circular data centres, net-zero operations, modular construction, and water-neutral operations. Each chapter builds toward understanding how AI infrastructure is designed, operated, and governed as a living system.

By the end of this book, readers will gain a deeper understanding of the technical, operational, and strategic principles required to design and manage AI data centres. The book prepares leaders, architects, and innovators to navigate the future of intelligent infrastructure, where AI factories become essential systems for building, operating, and governing intelligence at scale, and where intelligence is manufactured, energy is cognition, and infrastructure itself begins to think.

Description
AI is powering modern industries across different domains, from recommendations to forecasting, making it a must-have skill. As global AI adoption accelerates, it has become necessary for professionals to understand deeply how to utilize machine learning to build more reliable solutions

The book systematically covers foundational to advanced data science concepts through structured programming implementations. It begins with machine learning fundamentals and exploratory data analysis using NumPy and Pandas, then covers the math behind supervised algorithms like linear regression and unsupervised clustering techniques like K-means. You will master ensemble learning architectures like XGBoost, time series forecasting with FBProphet, automated hyperparameter optimization using the Optuna framework, and imbalanced data corrections via SMOTE. The book concludes with a specialized bonus chapter that breaks down the math behind multi-head self-attention mechanisms and fine-tuning strategies within large language model transformer architectures using the Hugging Face ecosystem.

By the end of this book, readers will be able to move confidently from raw data to working models. They will possess practical skills in data preparation, model building, evaluation, and optimization, giving them the confidence to solve complex, data-driven software engineering problems in real-world scenarios.

Description
Artificial intelligence is reshaping how we live, work, learn, and solve complex problems. For students entering a technology-driven world, understanding the fundamentals of AI is an increasingly valuable skill. This comprehensive guide introduces machine learning, data science, computer vision, and natural language processing in a clear and engaging way for Class X students.

Designed to build both conceptual knowledge and practical skills, the book provides a structured journey through the AI landscape. It covers topics ranging from decision trees to neural networks and introduces the key stages of AI project development, including problem scoping, data acquisition, data exploration, modelling, and evaluation. It also develops important career-readiness skills and introduces responsible AI, ethical practices, and green computing.

By the end of this book, readers will understand fundamental AI concepts and gain confidence in using Python and modern AI tools. Students will be equipped to move from passive users of technology to active creators who can explore ideas and develop their own AI projects. Whether you are a student, educator, or technology enthusiast, this book provides an accessible foundation for learning and creating in an AI-enabled world.

Description
Cloud adoption continues to accelerate as organizations migrate workloads to platforms like AWS, Azure, and Google Cloud. However, as cloud adoption grows, managing and optimizing cloud costs has become increasingly complex and critical for businesses striving to maintain efficiency and financial control.

This book provides a practical, end-to-end guide to cloud cost management, taking you from foundational concepts to advanced optimization and governance. The book presents a comprehensive framework for managing cloud costs built on three pillars: observability, optimization, and governance. You will learn how to gain visibility into cloud usage and cost drivers, apply optimization strategies such as rightsizing, elasticity, modernization, and commitment-based savings to reduce waste, and establish governance through policies, allocation models, and cost-aware practices. The book also covers pricing fundamentals and real-world scenarios.

By the end of this book, you will be equipped to control cloud spending, implement sustainable cost strategies, and align technology decisions with business goals. Whether you are a cloud engineer, architect, or IT decision-maker, you will gain practical skills to manage cloud costs with confidence.

Description
Data contracts are becoming important as organizations move to cloud platforms, data products, and decentralized data ownership. They create clear agreements between data producers and consumers, helping teams reduce broken pipelines, unclear ownership, and trust issues in daily data work. Data Contracts in Action shows how data contracts help establish clear agreements between data producers and consumers, improving trust, reducing operational issues, and creating scalable foundations for modern data ecosystems.

This book takes the reader from the basics of data governance and data quality to the practical use of data contracts in modern data platforms. It explains why governance matters, how data debt grows, and how contracts can define schemas, metadata, validation rules, ownership, and expectations. The readers will learn how to design contract-driven architectures, use standards such as JSON Schema, Avro, Protobuf, YAML, and OpenAPI, apply CI/CD and version control, monitor contract violations, and handle schema evolution.

This book takes the reader from the basics of data governance and data quality to the practical use of data contracts in modern data platforms. It explains why governance matters, how data debt grows, and how contracts can define schemas, metadata, validation rules, ownership, and expectations. The readers will learn how to design contract-driven architectures, use standards such as JSON Schema, Avro, Protobuf, YAML, and OpenAPI, apply CI/CD and version control, monitor contract violations, and handle schema evolution.

Description
Artificial intelligence has evolved beyond chatbots and static decision trees. Enterprise agents today need to be able to see images, understand spoken language, remember context over sessions, and reason through multi-step tasks without human intervention. LangChain has emerged as the leading open-source framework for combining these capabilities into production-ready systems.

This book is a hands-on guide to building multi-modal, context-aware AI agents. Readers start by designing reusable LangChain workflows and selecting the right language models, then move into building multimodal pipelines that handle text, images, and audio together. From there, the book covers vision-enabled agents powered by GPT-4o and CLIP, voice assistants built with Whisper and Azure Speech, and agents with persistent memory that maintain context across sessions. Later chapters tackle emotion-aware interactions, retrieval-augmented generation with hybrid search, and knowledge graph fusion for advanced multi-hop reasoning. The book also explores autonomous agents that execute real-world tasks and provides a practical guide to multi-agent planning, collaboration, and evaluation.

By the end of this book, readers will be equipped to design and deploy production-grade AI agents that handle real-world complexity, agents that see, hear, remember, reason, and act with intelligence and precision.

Description
Developing a mobile application is a key component in digital strategies to reach consumers. Developing it requires vision and expertise. Reusing the available knowledge is a key catalyst for progress. In AI-accelerated software development, this book gives the reader the psychological intelligence to anchor and become the captain of the ship powered by LLM.

Beginning with essential core dimensions from team prep and cross-cutting functions to technology selection, accelerators, and quality strategy, this book bridges the gap between high-level strategy and everyday coding. Build an understanding of the languages powering today’s top frameworks with practical explorations of Swift, Kotlin, and Dart. Through guided, step-by-step code walkthroughs of real-world one-page applications, you will gain immediate, practical mastery of Flutter, Kotlin Multiplatform (KMP), and cutting-edge Super App architectures.

By the end of this book, the readers will be equipped to play the key role as a strategist in a mobile development engagement and will have domain expertise. The reader will be equipped to consult, lead, and architect mobile application development.

Description
Driven by the rise of public hacks and exploits, securing Linux server infrastructures requires robust defense mechanisms. To mitigate modern cyber threats, implementing modern tools like Lynis, ClamAV, and OpenVAS is critical to continuously auditing networks. Fortifying setups using UFW, nftables, and PSAD firewalls, alongside SSH hardening, reduces the attack surface. Additionally, analyzing complex malware through ELF analysis and YARA signatures ensures the integrity of enterprise, cloud, and personal environments.

This book bridges theory and real-world execution by providing a methodical roadmap for proactive defense. It delivers step-by-step instructions, diagrams, and examples of attack types to secure data and applications. IT professionals will learn to deploy resilient internal services, manage incident resolution using rsnapshot or Timeshift backups, and execute a thorough network security assessment.br>
By the end of this book, you will master practical hardening steps to turn vulnerabilities into impenetrable strength. You will possess realistic strategies to create bulletproof systems and enhance site resilience against external threats. Ultimately, you will be fully equipped to protect infrastructure and make your Linux environments completely unbreakable.

Description
Cyberattacks continue to evolve in sophistication, frequency, and business impact. Organizations face ransomware attacks, cloud breaches, insider threats, supply chain compromises, AI-driven attacks, and advanced persistent threats that can disrupt operations and damage reputations. Effective incident response is no longer optional; it is a critical business capability.

This book provides a practical approach to cybersecurity incident response, covering threat landscapes, incident handling methodologies, forensic readiness, response playbooks, threat intelligence integration, cloud security incidents, post-incident recovery, and the use of artificial intelligence in modern threat detection and response. Readers will learn how to prepare organizations for cyber incidents, detect threats efficiently, contain and eradicate attacks, preserve forensic evidence, and continuously improve security operations. Real-world examples, industry frameworks, and operational best practices are incorporated throughout the book.

By the end of this book, readers will be equipped to design, implement, and mature incident response programs capable of handling modern cybersecurity challenges while improving organizational resilience and recovery capabilities.

Description
Modern software systems do not fail in simple ways anymore. They run across clouds, regions, containers, functions, and sometimes edge devices, all interacting at speeds humans cannot easily reason about. Traditional monitoring still has value, but on its own, it often falls short of explaining why something broke or what actually matters in the moment. As architectures grow more distributed and AI-driven, observability has shifted from basic signal collection to interpretation, context, and decision support.

The book takes you on a step-by-step engineering journey, starting with core observability architectural principles and data-driven monitoring strategies. You will master OpenTelemetry, handling context propagation and advanced tracing techniques across complex microservices and Kubernetes monitoring environments. From there, you will learn to optimize an open-source intelligent monitoring toolchain featuring Prometheus, OpenSearch, Grafana, and Jaeger. We will also learn how generative AI is being applied in real environments to interpret incidents, reduce noise, and support operational judgment, including where it helps and where caution is still needed.

By the end of this book, the readers will be fully equipped to deploy a secure, scalable, and intelligent observability platform in any corporate environment.

Learn quantum chemistry and computing with updated Qiskit workflows, noise-aware simulations, and quantum machine learning techniques using Python, with hands-on learning, turning complex concepts into practical skills.

Key Features

• Explore new chapters on quantum machine learning and advanced algorithms
• Apply noise-aware quantum chemistry with error mitigation techniques
• Work with updated Qiskit workflows and modern Python examples

Book Description

What you will learn

• Understand quantum mechanics and molecular systems
• Build quantum circuits using Qiskit and Python
• Implement VQE for molecular energy estimation
• Apply error mitigation in noisy quantum systems
• Use optimizers for stable hybrid quantum workflows
• Develop quantum machine learning models for molecules
• Explore advanced algorithms beyond VQE

Who this book is for

Professionals interested in chemistry and computer science at the early stages of learning or interested in a career of quantum computational chemistry and quantum computing, including advanced high school and college students. Helpful to have high school level chemistry, mathematics (algebra), and programming. An introductory level of understanding Python is sufficient to read the code presented to illustrate quantum chemistry and computing.

Description
Technology is crucial in today’s world, especially for project management. Modern software solutions help teams better coordinate, communicate more clearly, and make smarter decisions. As businesses embrace digital transformation, utilizing advanced technologies becomes essential for staying ahead and meeting the evolving needs of all stakeholders. Embracing technology not only simplifies tasks but also fosters collaboration and innovation among team members.

This book serves as a comprehensive guide for anyone looking to enhance their project management skills. It combines theoretical knowledge with practical application, offering a wealth of more than 1700 practice questions and insights to prepare for certification exams and real-world challenges. Each chapter focuses on essential aspects of project management, providing key takeaways and learnings.

By the end of this book, readers will emerge as confident and competent project managers, equipped with a robust understanding of key methodologies, risk management strategies, and effective stakeholder engagement techniques. They will have sharpened their leadership skills, enhanced their decision-making abilities, and gained practical insights that will empower them to navigate complex projects successfully and drive their teams toward achieving exceptional results.

Description
Quantum computing is rapidly evolving from a theoretical concept into a practical technology, influencing areas such as cybersecurity, optimization, artificial intelligence, and scientific research. As industries explore their potential, there is a growing demand for engineers, developers, and researchers who can understand and apply quantum computing using accessible tools such as Python.

This book is written from a combined perspective of teaching, research, and industry experience, ensuring both conceptual clarity and practical relevance. It introduces core concepts such as qubits, quantum states, gates, and circuits, and then progresses to algorithms such as Grover’s and Shor’s. It also explains quantum hardware, noise, and real-world limitations. You will gain hands-on experience using Qiskit, Cirq, and AWS Braket, along with exposure to advanced topics such as variational algorithms, quantum cryptography, and quantum machine learning, supported by simulation exercises and mini projects.

By the end of this book, readers will be able to design and implement quantum programs, work with modern quantum platforms, and apply quantum concepts to real-world problems with confidence.

Description
Data is everywhere, but data by itself has little value unless we can learn from it. Let us Learn Machine Learning takes you on a step-by-step journey from raw data to intelligent predictions. Beginning with data preparation and exploration, the book explains how to build, evaluate, and improve machine learning models using techniques such as Linear Regression, Logistic Regression, SVM, KNN, Naive Bayes, Decision Trees, Bagging, Boosting, and more. Along the way, you will learn how to engineer features, select the right models, reduce dimensionality, and deal with real-world challenges such as overfitting and imbalanced datasets.

Written in a simple, practical style, this book focuses on developing intuition as much as technical skill, making machine learning accessible to students, developers, and professionals alike.

Each chapter contains:
? Lucid explanation of the concept.
? Well thought-out, fully working programming examples.
? End-of-chapter exercises to practice the skills learned in the chapter.

Description
Data Structures and Algorithms is an important subject in any university curriculum for the computer science stream. It provides a great tool in the hands of software engineers and plays a significant role in software design and development. It is also becoming a must-have skill for many competitions and job interviews in the software industry.

This book covers the topics useful for students and also for software developers working in the industry. The concepts are explained in a step-wise manner and illustrated with numerous figures, text, examples, and immediate code samples, which help in better understanding of data structures and algorithms with their implementation. There are exercises at the end of the chapters which help students to explore more and build a better foundation of the subject. The book has more than 500 illustrations, code samples, and problems. Solutions for exercises are also available with programs. Students can use it for self-learning, and developers can use this for providing efficient solutions for their day-to-day development problems.

After completion of this book, students will have a good understanding of Data Structures and Algorithms concepts and implementation. Software engineers will be able to provide better solutions with appropriate data structures and efficient algorithms.

What you will learn
? Fundamentals of data structures and algorithms.
? Algorithms analysis.
? Variety of data structures and algorithms useful for software design and development.
? How to efficiently use different data structures and algorithms.
? When and where to use appropriate data structures and algorithms.
? Data structures and algorithms concepts with implementation.
? Approach to solve problems using the right data structures and algorithms.

Who this book is for
Students who want to self-study data structures and algorithms for their university curriculum subject and to enter the software industry. It is also useful for software engineers who want to learn it to solve day-to-day problems with better software design and write efficient code.

Table of Contents
1. Introduction 2. Arrays 3. Linked Lists 4. Stacks and Queues 5. Recursion 6. Trees 7. Graphs 8. Sorting 9. Searching and Hashing 10. Storage Management

Description
Test-driven development (TDD) is a development approach that flips traditional coding on its head by writing tests before writing the actual code. This powerful methodology helps developers write cleaner, more maintainable, and bug-resistant software. In the world of Python, TDD is not just a best practice; it is a game-changer. This book is your hands-on guide to mastering TDD the Pythonic way.

This book begins with the fundamentals of TDD, such as what it is, why it matters, and how to set up your development environment for test-first coding. Each chapter introduces you to core concepts like unit testing, test automation with unittest and pytest, mocking, refactoring, and continuous integration. You will build real Python applications through a TDD lens, progressing from simple functions to fully tested modules and components. A few chapters will explore TDD for APIs, working with databases, and using test doubles effectively, and each chapter ends with a practical mini-project to reinforce learning.

By the end of this book, you will not only be comfortable with writing tests first but also confident in designing cleaner architecture and delivering production-ready Python code faster. This book will also empower you to build smarter and ship with confidence.

Description
While traditional search engine optimization (SEO) was once the definitive tool for brand visibility, the rise of answer engines and generative models has introduced a notorious shift in consumer behavior. This book provides insights for navigating these changes, ensuring your content remains searchable and relevant in an era where traditional search results are being replaced by direct, AI-generated answers.

The AI Search Playbook provides a comprehensive overview of the emerging strategies necessary to survive this transition. You will learn to master answer engine optimization (AEO) to secure your place in direct AI responses and generative engine optimization (GEO) to influence the outputs of large language models. Key takeaways include techniques for structuring product data for AI consumption, understanding the mechanics of agent-based search, and transitioning your brand’s digital footprint from outdated SEO practices to these sophisticated new discovery frameworks.

By the end of this book, readers will be fully equipped to lead their product data through the AI revolution with confidence and technical competence. You will possess the specialized knowledge required to ensure your products and ideas are not just indexed, but actively found and recommended by the AI agents of tomorrow.

Description
Modern applications demand architectures that can scale, evolve, and adapt to changing business requirements. Designing successful microservices requires more than breaking an application into smaller services; it requires understanding deployment and operational practices. This book presents a practical, domain-driven approach to understanding how modern microservices architecture is designed and operated.

The book begins by establishing the fundamentals of microservices, comparing monolith and microservices architectures while introducing loose coupling, strong cohesion, and data decomposition. It then demonstrates how business growth drives the transition to Event Storming and architectural patterns to define service boundaries before applying these principles across the Product Catalog, search, customer, cart, and checkout domains through data architectures, services, and deployment infrastructure with Micro Frontends, API Gateway, CQRS, EDA, service discovery, service mesh, circuit breaker, containerization, and container orchestration, further exploring the integration of AI, ML, and data pipelines support, recommendations, fraud detection, and pricing intelligence.

By the end of this book, the readers will be equipped with the expertise to move beyond theoretical concepts, providing the practical toolkit and design patterns necessary to architect, scale, and manage sophisticated microservices ecosystems in any enterprise environment.

Description
AI is rapidly permeating every facet of our lives, fine-tuning the quality of our existence and shaping a better future. Organizations are improving their business performance by leveraging AI in their digital transformation initiatives. At the heart of this fervent global wave are the data scientists, the data engineers, the AI architects and developers, who are infusing AI into applications to solve real-world problems.

This book begins with an understanding of AI, subsequently showing how to apply AI to solve real-world challenges. Each chapter provides several illustrations, code examples, and hands-on exercises to augment further understanding of the technical concepts, preparing the readers to implement right from the very first chapter. The readers also learn how to make their AI-based solutions robust and enterprise-ready. Though the concepts are explained with Java and AI tools in Azure, this could be well applied using other programming languages and other similar cloud environments.

This book will help Java developers and architects quickly ramp up on AI and use the necessary tools to build AI-enabled applications. AI technology stakeholders, administrators, and enthusiasts will learn and understand the concepts and how these are being applied in the real-world.

Description
Kubernetes has become the backbone of modern cloud-native applications, but it is also a high-value target for attackers. As organizations rapidly adopt containers, service meshes, and automation, securing Kubernetes clusters has become an active security battle.

This book takes a hands-on, end-to-end approach to Kubernetes security. It begins by exploring real-world attack surfaces, guiding readers through container enumeration, RBAC abuse, and cluster takeover techniques. The focus then shifts to defense, covering Kubernetes audit log analysis, runtime detection, monitoring with Prometheus, and incident response. From an offensive perspective, you will learn to scan exposed services, deliver reverse shell payloads, and enumerate internal cluster metadata. Switching to defensive operations, you will conduct threat hunting using API audit logs, correlate runtime telemetry to reconstruct incident kill chains, and run automated tools. Each chapter is built around practical demonstrations that mirror how attacks and detections occur in real environments.

By the end of this book, readers will gain real-world proficiency in both offensive cluster exploitation and defensive forensic analysis in Kubernetes environments. They will be able to identify and exploit common weaknesses, detect malicious behavior, and design Kubernetes clusters.

Description
Modern frontend development is no longer limited to building screens; it now defines how enterprises deliver scalable, secure, performant, and consistent digital experiences. As applications grow across teams, channels, frameworks, and business domains, frontend architecture has become a critical capability for modern software delivery.

This book provides a practical guide to designing and managing enterprise-grade frontend systems. It covers frontend foundations, architecture principles, project organization, monorepos, microfrontends, development workflows, tooling, performance optimization, security, authentication, UI interaction patterns, design systems, accessibility, internationalization, modernization, and real-world case studies. Through examples across Angular, React, and Vue, along with the World Global Bank case study, the book connects architectural theory with practical implementation.

By the end of this book, readers will be able to think beyond individual frameworks and design frontend platforms that are modular, maintainable, secure, and ready for enterprise scale. It will help developers, architects, and technical leaders make better decisions while building modern web applications.

Description
Data Product Thinking is transforming modern enterprise strategy by turning raw datasets into reliable, self-service assets that drive real business value. It bridges technical data management and strategic business execution, giving you a clear blueprint for building, governing, and scaling high-impact data products.

This book provides a complete roadmap across four core phases. You will start by mastering data governance, business impact, and product characteristics across transactional, analytical, document, and third-party environments. Next, it covers key quality properties—existence, accuracy, completeness, timeliness, trustworthiness, and usability—while managing the lifecycle from creation to decommissioning. You will examine consumption formats for structured data, semi-structured documents, media, and AI models, alongside privilege management, backward compatibility, data culture, data economics, and agile adoption across governance, domains, and individual products. Finally, you will unlock data products for AI models, generative AI, quantum computing, low-code platforms, and autonomous networks.

By the end of this book, you will have the skills to design, govern, and deploy scalable data products, empowering you to lead enterprise data transformation.

Diagnose and fix Unity 6 performance problems with a measurement-driven workflow. Use the Profiler, Frame Debugger, batching, lighting, LOD, and occlusion culling to validate smoother and more efficient gameplay.

Key Features

• Measurement-first guidance connects baselines, profiling evidence, changes, and verified gains
• Tool-focused context explains why the Profiler and Frame Debugger reveal real bottlenecks now
• Complete Unity challenges show how rendering, lighting, LOD, and culling improve gameplay well

Book Description

What you will learn

• Identify common Unity performance pitfalls
• Profile bottlenecks with Unity tools
• Reduce draw calls through static batching
• Optimize real-time and baked lighting
• Apply LOD and occlusion culling
• Measure gains against a performance baseline

Who this book is for

Unity developers who can build scenes and want to diagnose performance issues with practical, measurable techniques. The material is valuable for game programmers, technical artists, and indie developers using the Profiler, Frame Debugger, static batching, lighting, LOD, occlusion culling, and baseline comparisons.

Work more effectively with Claude Code through 101 practical techniques for setup, planning, automation, and verification. Strengthen project guidance, tool use, safety checks, and delivery habits.

Key Features

• Practical coverage of setup, memory, skills, hooks, MCP, subagents, and safe daily workflows
• Clear rationale for boundaries, verification, citations, and deterministic safety controls
• Focused guidance across 101 compact tips for stronger Claude Code work from start to finish

Book Description

What you will learn

• Configure Claude Code for dependable daily use
• Structure CLAUDE.md files for precise project guidance
• Create reusable slash commands and multi-phase skills
• Apply plan mode and specifications before implementation
• Build hooks, MCP tools, and subagents with guardrails
• Verify outputs, sources, sessions, and delivery quality

Who this book is for

Developers, technical leads, AI-assisted coding practitioners, and teams already using or evaluating Claude Code. Basic command-line and software development familiarity will help readers apply the configuration, automation, testing, and workflow guidance.

Build production-grade Large Language Model systems for finance. Learn how to design, fine-tune, evaluate, govern, and deploy LLMs, Retrieval-Augmented Generation (RAG), and AI agents for trading, banking, risk management, compliance, and financial research using rigorous mathematics, practical code, and real-world case studies.

Key Features

• Build production-ready financial LLM systems with RAG, fine-tuning, AI agents, and MCP
• Apply LLMs to trading, investment research, banking, risk, fraud, compliance, and documents
• Explore reasoning models, multimodal AI, time-series LLMs, and autonomous financial agents
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

What you will learn

• Understand LLM foundations for financial applications
• Build financial LLM systems from ingestion to deployment
• Fine-tune models with LoRA, QLoRA, RLHF, and DPO
• Create RAG pipelines for financial documents and knowledge
• Design autonomous agents and multi-agent finance workflows
• Integrate LLMs securely with MCP and enterprise systems
• Apply LLMs to trading, banking, risk, fraud, KYC, and AML
• Evaluate and govern auditable financial AI with rigorous metrics

Who this book is for

This book is written for data scientists, quantitative analysts, portfolio managers, traders, fintech developers, AI engineers, software architects, banking professionals, compliance specialists, regulators, researchers, and graduate students who want to apply Large Language Models to finance. Readers should have a fundamental understanding of Python programming, machine learning, and financial markets. The book is equally suitable for practitioners building production AI systems and researchers interested in the mathematical foundations of financial LLMs.

On t’a dit que la programmation, c’était pour les autres. Ceux qui ont commencé tôt, qui adorent les maths et qui pensent en binaire.

Ce livre te démontre le contraire. Sa méthode progressive et accessible permet de débuter sans jargon inutile, avec assez d’humour pour survivre aux premiers bugs et comprendre qu’une erreur bien comprise vaut mieux qu’un code qui fonctionne par hasard.

À l’aide d’exemples très concrets, dès les premières pages, tu apprendras à avancer à ton rythme, à clarifier ta logique, à comprendre que le code se lit, se discute et s’améliore avec les autres, et à utiliser l’IA comme copilote sans lui abandonner le volant. À l’heure où les machines génèrent du code à la chaîne, savoir le lire, le corriger et le diriger devient une compétence rare et très recherchée.

Que tu sois au début de ton parcours, en pleine reconversion ou déjà plongé dans le numérique, ce livre t’apprendra à coder et à penser autrement.

Discover hacks to quickly get started with Procreate with the help of this color guide and learn how to use it on an iPad to create exquisite illustrations and animations

Key Features

• Follow step-by-step instructions and tips to learn Procreate and get the most out of it
• Work through hands-on tutorials with real artwork that will boost your confidence to explore Procreate further
• Highly recommended for iPad users who want to be able to paint on the go
• Free with your book: DRM-free PDF version + access to Packt’s next-gen Reader*

Book Description

What you will learn

• Set up Procreate canvases for different illustration projects
• Use brushes, textures, gestures, and shortcuts with confidence
• Customize brushes and create new effects in Brush Studio
• Use assisted drawing tools to improve accuracy and speed
• Create animations and multi-page artwork using Procreate's assist tools
• Paint directly on 3D models using Procreate's 3D tools
• Develop polished digital illustrations from start to finish

Who this book is for

This book is ideal for beginners who want to start creating professional illustrations in Procreate but are unsure where to begin. It is also suited to experienced illustrators who work with other tools and want to expand their creative repertoire with Procreate.

"This book makes a compelling case that experimentation is not a process layered on top of architecture, but a property the architecture itself must support."- Scott Hanselman, VP, Member of Technical Staff, Microsoft and GitHub

Key Features

• Apply Scale by Subtraction to improve reliability while controlling cost and complexity
• Evolve ShopFlow from MVP to a global platform through realistic architectural trade-offs
• Implement Zero Trust, database sharding, FinOps, and AI-native self-healing
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

What you will learn

• Apply Scale by Subtraction to reduce system complexity
• Distinguish temporary traffic spikes from sustained growth
• Use tipping-point metrics to guide service decoupling
• Shard databases while preserving data integrity
• Secure distributed systems with Zero Trust and mTLS
• Balance delivery velocity, availability, and FinOps
• Design AI-native infrastructure with autonomous agents

Who this book is for

Software architects, engineering directors, CTOs, and senior or staff engineers who need to scale systems, teams, and operational practices without introducing unnecessary complexity. A fundamental understanding of cloud computing and basic familiarity with AI applications are recommended; no specific language, vendor, or technology stack is required.

Take a practical approach to quantum technology, equipping leaders with frameworks, strategies, and tools to act early and stay ahead of disruption

Key Features

• Develop actionable quantum strategies aligned to business outcomes
• Build and scale quantum teams, partnerships, and investment plans
• Implement quantum-safe security and hybrid quantum-AI systems
• Design governance that aligns executive, technical, and security stakeholders
• Migrate to post-quantum cryptography without disrupting operations

Book Description

What you will learn

• Establish governance structures that align quantum initiatives across your organization
• Assess and upgrade infrastructure for quantum-AI hybrid integration
• Execute a phased migration to post-quantum cryptographic standards
• Evaluate quantum threats specific to your industry and risk profile
• Understand the full quantum ecosystem from sensing to distributed networking
• Design university and government partnerships that accelerate quantum talent pipelines
• Lead organizational change through the quantum transition with confidence

Who this book is for

This book is written for executives, board members, investors, startup founders, academic leaders, and policymakers who recognize that quantum technology demands strategic attention today. No background in quantum physics or advanced computing is required. Whether you are a CEO building a business case for quantum investment, a CISO planning a post-quantum security migration, a CTO?evaluating infrastructure readiness, or a policymaker shaping national quantum strategy, this book meets you are the level of leadership decision-making and equips you to move forward with clarity and confidence.

Learn practical Copilot Cowork workflows to delegate work, automate tasks, and work smarter across Microsoft 365

Key Features

• Use practical workflows for inboxes, meetings, research, reporting, project handoffs, and more
• Create repeatable workflows, team-specific skills, and extended capabilities that fit the way your organization works

Book Description

What you will learn

• Turn everyday tasks into Cowork workflows
• Delegate multi-step work instead of writing one-off prompts
• Move seamlessly from notes to documents, decks, emails, and more
• Automate recurring work with scheduled prompts and team-specific skills
• Extend Copilot Cowork across your team's tools and processes

Who this book is for

This book is for Microsoft 365 users, knowledge workers, team leads, managers, and business professionals who want to move beyond basic Copilot prompts and use Copilot Cowork to handle complete, repeatable workflows. No programming experience is required, but readers should have a working familiarity with Microsoft 365 and access to Microsoft Copilot features relevant to their organization.

1 book. 18 experts. 4 continents. A fast track to understanding ESG in the Age of AI

Key Features

• 18 global experts bring ESG and AI insights together in one book
• Turn ESG and AI into an advantage with smarter data and decisions
• Navigate regulation, investment, governance, and cyber risk

Book Description

What you will learn

• Build actionable ESG strategies enhanced by AI
• Navigate ESG frameworks and evolving compliance
• Establish governance for ESG and responsible AI
• Apply AI to finance, risk and investor trust
• Drive sustainable innovation with accountability
• Apply ESG and AI to food, health and cities
• Integrate cybersecurity into ESG strategy
• Lead effectively through institutional complexity

Who this book is for

Executives, board members, investors, policymakers and technology leaders seeking a fast, authoritative overview of ESG and AI. Ideal for busy decision-makers who want insights from 18 experts across four continents without navigating each field separately. Relevant across corporate, public, nonprofit, and academic sectors. No deep technical expertise is required: only a working understanding of ESG and an interest in AI.

A practical, illustrated guide for applying accessibility across social media, meetings, presentations, emails, and AI. Learn inclusive communication through engaging visuals and real-world examples.

Key Features

• Learn accessibility through a unique graphic novel format with real-world scenarios
• Practical tips for social media, meetings, presentations, emails, and AI tools
• Actionable guidance to create inclusive, accessible digital communication

Book Description

What you will learn

• Use AI responsibly for accessible content creation
• Make social media, emails, documents, and presentations accessible
• Host meetings and events where everyone can participate
• Build accessibility into your everyday work
• Communicate respectfully with disabled people
• Apply inclusive communication etiquette and avoid common accessibility mistakes

Who this book is for

This book is for professionals, content creators, educators, marketers, and teams who want to make their communication more inclusive and accessible to their many colleagues, friends and family members with disabilities. Whether you work in corporate environments, digital media, education, or tech, this guide helps you apply accessibility best practices in everyday scenarios. It’s ideal for beginners looking to understand accessibility fundamentals, as well as professionals seeking practical ways to improve their workflows and create more inclusive experiences for diverse audiences.

Use AWS Glue to integrate growing data sources with serverless ETL, building secure, observable pipelines that support reliable analytics while managing performance and cost across a governed AWS data platform as workloads grow

Key Features

• Use runnable code, console walkthroughs, and downloadable examples for core AWS Glue workflows
• Apply DataOps practices with AWS CDK, Docker, and CI/CD in real-world scenarios
• Learn from six data specialists with AWS, Spark, Apache Iceberg, and data lake expertise

Book Description

What you will learn

• Design scalable serverless ETL pipelines with AWS Glue
• Ingest data from files, streams, SaaS, and JDBC sources
• Optimize file formats, partitions, compression, and layouts
• Manage schemas, partitions, and lineage in AWS Glue Data Catalog
• Secure data with access control, encryption, and auditing
• Automate testing and multi account CI/CD using AWS CDK and Docker
• Monitor, tune, and troubleshoot AWS Glue and Spark workloads
• Apply Apache Iceberg, Hudi, and Delta Lake to data lakes with AWS Glue

Who this book is for

This book is for data engineers, ETL developers, cloud architects, and analytics professionals who build or operate data platforms on AWS. It suits readers working on serverless data lakes, Spark ETL, governance, data sharing, reliability, or cost control. It is especially useful if you aim to improve pipeline reliability, governance, or cost visibility as workloads grow. Basic familiarity with the AWS Management Console, Amazon S3, and IAM is recommended. Experience with Python, SQL, or Apache Spark will help with the code examples, and an AWS account is useful for following the walkthroughs.

Build smarter .NET applications by transforming complex data and delivering relevant search experiences with MongoDB aggregation, Search, and Vector Search.

Key Features

• Transform complex data with MongoDB aggregation pipelines
• Build relevant search functionality in .NET with MongoDB Search
• Add semantic search to C# applications with MongoDB Vector Search
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

What you will learn

• Build aggregation pipelines to reshape complex application data
• Integrate aggregation pipelines into C#/.NET applications
• Improve search relevance with MongoDB Search
• Add full-text search to .NET applications
• Implement semantic search with MongoDB Vector Search
• Integrate vector search into C# applications
• Apply best practices to aggregation and search

Who this book is for

This book is for C#/.NET developers and backend engineers who use MongoDB and want to move beyond basic queries. It suits readers who need to transform complex data, improve application search, or add semantic search. A working knowledge of C#/.NET and basic familiarity with MongoDB is recommended.

Pourquoi certains jeux sont-ils plus agréables à jouer ?

Quel est le rôle de l'UX designer dans le jeu vidéo ?

Comment identifier les différents profils de joueurs ?

Dans une industrie du jeu vidéo aussi créative que compétitive, comprendre réellement comment les joueuses et les joueurs vivent leurs expériences de jeu est devenu primordial. Cet ouvrage replace l’expérience utilisateur au centre de la conception vidéoludique et aborde la psychologie du joueur... à travers :

• la perception ;
• l’engagement ;
• l’apprentissage ;
• la diversité des profils de joueurs.

L’auteur partage les bonnes pratiques de la game user research avec des méthodes concrètes telles que :

• les questionnaires ;
• les playtests ;
• les game analytics ;
• la biométrie.

Vous retrouverez également différentes perspectives sur :

• l’éthique ;
• la diversité ;
• l’inclusion ;
• la représentation.

Vous serez ainsi capable de concevoir des expériences alignées avec l’intention du studio, d’anticiper et d’analyser le comportement des joueurs avec précision afin de prendre des décisions éclairées pour améliorer durablement leurs jeux.

À QUI S’ADRESSE CE LIVRE ?

• Aux créateurs de jeux vidéo indépendants et des studios.
• Aux game designers et UX designer curieux.
• Aux développeurs et autres professionnels du monde vidéoludique avec une appétence pour l’UX et le jeu vidéo.
• Aux étudiants et amateurs de jeux vidéo intrigués par l’UX design.

Master modern 3D graphics shader programming with Computer Graphics Programming in OpenGL with Java, Fourth Edition. This newly revised and expanded edition is the definitive resource for undergraduate students, educators, and industry professionals seeking a practical and accessible guide to modern OpenGL 4.0+ shader programming using Java, as well as its theoretical foundations. Designed in a 4-color, "teach-yourself" approach, the book simplifies complex concepts and delivers hands-on learning with comprehensive examples and running code.

FEATURES

• Shaders and the Graphics Pipeline: Understand vertex, geometry, tessellation, and fragment shaders for rendering models with textures, lighting, shadows, height mapping, noise maps, skyboxes, simulating water, wood, marble, clouds, and more.
• Managing 3D Graphics Data: Learn how to organize, store, and manipulate data to efficiently render 3D objects. Includes a new chapter on building a camera controller for viewing 3D scenes.
• Ray Tracing and Complex Models: Delve into ray tracing techniques, including a new chapter on bounding volume hierarchies for handling complex models.
• Stereoscopy for VR and 3D glasses: Discover how to render immersive stereoscopy such as used in 3D movies and virtual reality.
• Running Code examples: Every technique is backed by running code in modern OpenGL 4.0+ with GLSL and Java, for PC/Windows and Macintosh. Everything needed to install the libraries and run each example yourself.
• Optimization: Explains how to optimize GPU shader code with modern graphics debugging tools such as Nsight and RenderDoc.
• Downloadable companion files: All the code, object models, figures, and more.

Start game development with Godot 4.6 and no prior coding experience. Explore nodes, scenes, 3D tools, and GDScript while building, polishing, and exporting a playable starter project.

Key Features

• Beginner-first coverage of Godot 4.6, 3D scene tools, GDScript, controls, and export skills
• Clear explanations show why nodes, scenes, transforms, and scripts form every Godot project
• Complete project files reveal how a player controller and collectible combine in a working game

Book Description

What you will learn

• Navigate the Godot 4.6 editor confidently
• Organize projects with nodes and scenes
• Build 3D scenes with materials and lighting
• Write GDScript with variables and functions
• Create player controls and collectible logic
• Polish and export a working Godot project

Who this book is for

Complete beginners who want to enter game development with Godot 4.6 and have no prior coding or engine experience. The material also suits aspiring indie developers, students, and creative learners seeking a carefully explained foundation in 3D scenes, GDScript, player controls, and project export.

Build scalable Unity 6 gameplay with ECS, DOTS, the Job System, and Burst. Create entities, components, bakers, systems, and large simulations while learning practical debugging and data-oriented control techniques.

Key Features

• Data-oriented coverage connects entities, components, bakers, systems, Jobs, and Burst code
• Performance context explains why ECS can process large simulations with greater efficiency
• Complete Unity projects show how scalable spawning, debugging, and player control work together

Book Description

What you will learn

• Explain data-oriented design and ECS benefits
• Configure Unity 6 packages and Play Mode
• Create entities, components, and bakers
• Build movement systems with Unity Jobs
• Enable Burst for high-performance code
• Debug and control large ECS simulations

Who this book is for

Intermediate Unity developers who are comfortable with C# and want to learn ECS, DOTS, and data-oriented gameplay. It is especially relevant to game programmers working with large simulations, scalable spawning, the Unity Job System, Burst compilation, entity debugging, and performance-focused architecture.

Bridge the gap between AI hype and software reality by learning how to evaluate agents, redesign team responsibilities, and introduce structured controls that improve delivery without sacrificing clarity, safety, or maintainability.

Key Features

• Use RACM to match AI capabilities to SDLC tasks and supervision needs
• Apply Execution Plans and Logbooks to make agent work visible and auditable
• Set autonomy limits, guardrails, and review practices for safer adoption

Book Description

What you will learn

• Distinguish agents from simpler AI coding assistants
• Assess tool fit using capability and autonomy criteria
• Structure prompts through richer Context Engineering
• Use plans and logs to supervise non-trivial AI tasks
• Design workflows for prototyping, refactoring, and QA
• Prevent hidden risk from churn, bias, and hallucinations
• Reorganize teams around emerging AI-native roles
• Build skills for orchestration, review, and governance

Who this book is for

This book is for developers,, tech leads, architects, and engineering managers who are actively building and delivering software while adapting to AI-driven change. It is especially valuable for mid-level and senior developers working across web, backend, and platform systems who want to stay relevant as their role shifts from writing code to guiding and validating AI-generated work.

Comprehensive guide to Codex CLI: prompting, AGENTS.md, MCP, hooks, skills, sub-agents, orchestration, CI/CD, security, and enterprise deployment, with exercises

Key Features

• Move from first principles to production workflows and team-scale agentic practice.
• Apply proven patterns for orchestration, code review, migration, testing, and CI/CD delivery.
• Harden agent sessions with approval modes, kernel-level sandboxing, and security practices.
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

What you will learn

• Set up, authenticate, and prompt Codex CLI effectively
• Write AGENTS.md rules and apply patterns that avoid common pitfalls
• Choose approval modes, kernel-level sandboxing, and trust boundaries
• Manage model selection, reasoning effort, context windows, and cost
• Extend the agent with MCP servers, hooks, and skills
• Coordinate sub-agents, multi-agent orchestration, and worktrees
• Integrate Codex into CI/CD, security hardening, and enterprise deployment
• Apply Codex to code review, migration, backend, frontend, and infrastructure as code

Who this book is for

This book is for software developers who are comfortable in a terminal and want to use AI agents for real engineering work rather than isolated code suggestions. It is also useful for tech leads and engineering managers who need a framework for adopting agentic coding safely at team or enterprise scale. DevOps practitioners and architects interested in integrating agent workflows into delivery pipelines will also find it relevant. Some experience with version control and command-line tools is assumed; no prior knowledge of Codex CLI is required.

Build AI-assisted network troubleshooting workflows that parse CLI output, call approved tools, use MCP, and keep evidence visible for review

Key Features

• Build local LLM workflows for NetOps using Python, Ollama, and validated CLI data
• Create troubleshooting agents that use memory, approved tools, and clear evidence
• Package reusable network tools with MCP and plan controlled read-only pilots

Book Description

What you will learn

• Run local LLM workflows with Ollama and Python
• Shape reliable NetOps prompts using RACE
• Parse CLI and BGP output into structured JSON
• Build chatbots that remember troubleshooting context
• Connect AI agents to approved network tools
• Create evidence-based troubleshooting loops
• Expose reusable network tools with MCP
• Plan read-only pilots with safety controls

Who this book is for

This book is for network engineers, NetOps engineers, NOC engineers, SREs, DevOps engineers, and network automation professionals who want to apply AI to troubleshooting without losing control. Basic networking and CLI familiarity will help, beginner Python knowledge is useful for following the labs.

Configure OpenCode for controlled agentic coding across cloud, built-in, and local models. Explore codebases, separate planning from changes, manage permissions, and complete practical terminal-based development workflows.

Key Features

• Open provider support connects OpenCode with cloud, built-in, and private local AI models today
• Control-focused guidance explains why plans, permissions, and grounded context improve results
• Project files demonstrate how exploration, planning, and implementation fit together safely

Book Description

What you will learn

• Install OpenCode and connect model providers
• Explore codebases with /init and AGENTS.md
• Switch between Build and Plan agents
• Configure permissions for safer agent actions
• Write grounded instructions for reliable outputs
• Run local models for private offline coding

Who this book is for

Developers who are comfortable with basic coding and terminal use and want an open alternative to closed AI coding tools. It is suitable for software engineers, technical learners, and agentic coding newcomers interested in provider choice, safer permissions, codebase exploration, and private local-model workflows.