prescott jonah (17 resultados)

Paperback. Condición: New.

Paperback. Condición: new. Paperback. Data systems outlive applications, frameworks, and infrastructure.They encode decisions that shape what a system can become-and what it can never safely change.Designing Modern Data Systems is a deep, decision-driven guide to building data systems that are reliable, scalable, and adaptable over time. Rather than focusing on tools or trends, this book teaches how to reason about architecture itself: how guarantees are chosen, where authority lives, how failures manifest, and how systems evolve under real-world pressure.Written for experienced engineers and architects, the book treats data systems as long-lived sociotechnical systems-not just databases or pipelines. It focuses on clarity of responsibility, explicit trade-offs, and preserving meaning as data moves, changes, and ages.This book takes a structured journey through modern data system design: How to define data systems as distinct from applications and infrastructureHow non-functional requirements like reliability, availability, latency, and cost shape architecture long before technology choicesHow to design data models, storage engines, and indexing strategies that survive product evolutionHow to reason about replication, partitioning, coordination, and distributed transactions without accidental complexityHow batch and stream processing fit into a unified view of data over timeHow logs, history, and derived data enable recovery, reprocessing, and safe changeHow to operate systems in production with observability, backpressure, and failure isolationHow to design data systems that support machine learning and large language model platforms, including feature pipelines and embeddingsHow to migrate, evolve, and decommission systems without outages or loss of trustThroughout the book, ideas are grounded in a single evolving reference system, allowing readers to see how architectural decisions accumulate and interact as requirements change.What Makes This Book DifferentDecision-focused, not tool-drivenThe book avoids product comparisons and instead teaches how to evaluate any technology within clear architectural constraints.Explicit trade-offs, not recipesEvery design choice is examined in terms of what it enables, what it forbids, and what it costs.Modern, without being trendyAI and LLM systems are addressed where they introduce real architectural pressure-without hype or speculation.Written for longevityThe principles in this book are designed to remain relevant as tools, platforms, and organizational structures change.This book is written for: Software engineers designing backend and platform systemsData engineers responsible for storage, processing, and pipelinesStaff, principal, and senior engineers shaping architectural directionArchitects and technical leaders responsible for long-term system evolutionPractitioners preparing for system design interviews who want judgment, not templatesThis is not: A beginner's introduction to databasesA step-by-step tutorial for specific toolsA catalog of technologies or patternsInstead, it is a book about how to think clearly about data systems, and how to design them so they remain understandable, trustworthy, and changeable over time.If you are responsible for making architectural decisions-and living with their consequences-Designing Modern Data Systems is written for you. This item is printed on dema Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condición: New.

Paperback. Condición: New.

Paperback. Condición: new. Paperback. Operational architecture for long-lived data systems.Modern data systems rarely fail because of broken code. They fail because architectural intent erodes under time, pressure, and continuous change. Operating Modern Data Systems is a deep, architecture-first examination of what happens after systems leave the whiteboard and enter production. It reframes operations as an architectural discipline-where guarantees are defended or lost, authority is exercised under stress, and reliability is proven over years rather than releases.This book is not about tools, dashboards, or incident checklists. It focuses instead on the structural forces that shape real production systems: failure as a normal condition, time and ordering ambiguity, load and pressure propagation, migration risk, cost as a signal, security as operational trust, and the human and organizational realities embedded in every system.Written for experienced practitioners, the book develops architectural judgment rather than prescribing solutions. It examines how systems drift, how meaning degrades silently, and how design decisions are continuously rewritten through operational action.What This Book CoversWhy correct designs still fail after deploymentHow operational shortcuts quietly become architectural commitmentsReliability as preserved meaning-not just uptimeFailure as a continuous condition, not an exceptional eventTime, ordering, and partial truth in distributed systemsRecovery, migration, and change as extended failure modesLoad, pressure, backpressure, and containmentObservability as the ability to explain behaviorCost, security, and governance as architectural signalsHuman judgment and organizational structure as part of the systemHow systems age-and what allows architecture to hold over timeWhat Makes This Book DifferentOperations treated as architectureProduction behavior, failure, and recovery are examined as structural concerns, not operational afterthoughts.Decision- and consequence-focusedThe book emphasizes how choices accumulate, constrain future change, and shape long-term reliability.Tool-agnostic and durableConcepts are designed to remain relevant as platforms, frameworks, and AI systems evolve.Reliability redefinedAvailability alone is not success. Reliability is the preservation of meaning, guarantees, and trust under stress.Written for the AI era without hypeThe book situates modern data and AI-driven systems within the same architectural forces, showing where automation amplifies risk and responsibility.Who This Book Is ForThis book is written for: Software engineers operating backend and platform systemsData engineers responsible for production pipelines and storageSenior, staff, and principal engineers shaping system architectureArchitects and technical leaders accountable for long-term reliabilityPractitioners working with distributed data systems and AI platformsIt assumes familiarity with production systems and distributed environments.Who This Book Is Not ForBeginners seeking introductions or tutorialsReaders looking for step-by-step guides or tool-specific instructionsThose expecting quick fixes, patterns, or checklistsOrder now to develop architectural judgment for systems that must endure pressure, change, and time. This item is printed on d Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condición: new. Paperback. Data systems outlive applications, frameworks, and infrastructure.They encode decisions that shape what a system can become-and what it can never safely change.Designing Modern Data Systems is a deep, decision-driven guide to building data systems that are reliable, scalable, and adaptable over time. Rather than focusing on tools or trends, this book teaches how to reason about architecture itself: how guarantees are chosen, where authority lives, how failures manifest, and how systems evolve under real-world pressure.Written for experienced engineers and architects, the book treats data systems as long-lived sociotechnical systems-not just databases or pipelines. It focuses on clarity of responsibility, explicit trade-offs, and preserving meaning as data moves, changes, and ages.This book takes a structured journey through modern data system design: How to define data systems as distinct from applications and infrastructureHow non-functional requirements like reliability, availability, latency, and cost shape architecture long before technology choicesHow to design data models, storage engines, and indexing strategies that survive product evolutionHow to reason about replication, partitioning, coordination, and distributed transactions without accidental complexityHow batch and stream processing fit into a unified view of data over timeHow logs, history, and derived data enable recovery, reprocessing, and safe changeHow to operate systems in production with observability, backpressure, and failure isolationHow to design data systems that support machine learning and large language model platforms, including feature pipelines and embeddingsHow to migrate, evolve, and decommission systems without outages or loss of trustThroughout the book, ideas are grounded in a single evolving reference system, allowing readers to see how architectural decisions accumulate and interact as requirements change.What Makes This Book DifferentDecision-focused, not tool-drivenThe book avoids product comparisons and instead teaches how to evaluate any technology within clear architectural constraints.Explicit trade-offs, not recipesEvery design choice is examined in terms of what it enables, what it forbids, and what it costs.Modern, without being trendyAI and LLM systems are addressed where they introduce real architectural pressure-without hype or speculation.Written for longevityThe principles in this book are designed to remain relevant as tools, platforms, and organizational structures change.This book is written for: Software engineers designing backend and platform systemsData engineers responsible for storage, processing, and pipelinesStaff, principal, and senior engineers shaping architectural directionArchitects and technical leaders responsible for long-term system evolutionPractitioners preparing for system design interviews who want judgment, not templatesThis is not: A beginner's introduction to databasesA step-by-step tutorial for specific toolsA catalog of technologies or patternsInstead, it is a book about how to think clearly about data systems, and how to design them so they remain understandable, trustworthy, and changeable over time.If you are responsible for making architectural decisions-and living with their consequences-Designing Modern Data Systems is written for you. This item is pr Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condición: New.

Paperback. Condición: new. Paperback. Data systems outlive applications, frameworks, and infrastructure.They encode decisions that shape what a system can become-and what it can never safely change.Designing Modern Data Systems is a deep, decision-driven guide to building data systems that are reliable, scalable, and adaptable over time. Rather than focusing on tools or trends, this book teaches how to reason about architecture itself: how guarantees are chosen, where authority lives, how failures manifest, and how systems evolve under real-world pressure.Written for experienced engineers and architects, the book treats data systems as long-lived sociotechnical systems-not just databases or pipelines. It focuses on clarity of responsibility, explicit trade-offs, and preserving meaning as data moves, changes, and ages.This book takes a structured journey through modern data system design: How to define data systems as distinct from applications and infrastructureHow non-functional requirements like reliability, availability, latency, and cost shape architecture long before technology choicesHow to design data models, storage engines, and indexing strategies that survive product evolutionHow to reason about replication, partitioning, coordination, and distributed transactions without accidental complexityHow batch and stream processing fit into a unified view of data over timeHow logs, history, and derived data enable recovery, reprocessing, and safe changeHow to operate systems in production with observability, backpressure, and failure isolationHow to design data systems that support machine learning and large language model platforms, including feature pipelines and embeddingsHow to migrate, evolve, and decommission systems without outages or loss of trustThroughout the book, ideas are grounded in a single evolving reference system, allowing readers to see how architectural decisions accumulate and interact as requirements change.What Makes This Book DifferentDecision-focused, not tool-drivenThe book avoids product comparisons and instead teaches how to evaluate any technology within clear architectural constraints.Explicit trade-offs, not recipesEvery design choice is examined in terms of what it enables, what it forbids, and what it costs.Modern, without being trendyAI and LLM systems are addressed where they introduce real architectural pressure-without hype or speculation.Written for longevityThe principles in this book are designed to remain relevant as tools, platforms, and organizational structures change.This book is written for: Software engineers designing backend and platform systemsData engineers responsible for storage, processing, and pipelinesStaff, principal, and senior engineers shaping architectural directionArchitects and technical leaders responsible for long-term system evolutionPractitioners preparing for system design interviews who want judgment, not templatesThis is not: A beginner's introduction to databasesA step-by-step tutorial for specific toolsA catalog of technologies or patternsInstead, it is a book about how to think clearly about data systems, and how to design them so they remain understandable, trustworthy, and changeable over time.If you are responsible for making architectural decisions-and living with their consequences-Designing Modern Data Systems is written for you. This item is pr Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Condición: New.

Condición: New. Print on Demand.

Paperback. Condición: new. Paperback. Operational architecture for long-lived data systems.Modern data systems rarely fail because of broken code. They fail because architectural intent erodes under time, pressure, and continuous change. Operating Modern Data Systems is a deep, architecture-first examination of what happens after systems leave the whiteboard and enter production. It reframes operations as an architectural discipline-where guarantees are defended or lost, authority is exercised under stress, and reliability is proven over years rather than releases.This book is not about tools, dashboards, or incident checklists. It focuses instead on the structural forces that shape real production systems: failure as a normal condition, time and ordering ambiguity, load and pressure propagation, migration risk, cost as a signal, security as operational trust, and the human and organizational realities embedded in every system.Written for experienced practitioners, the book develops architectural judgment rather than prescribing solutions. It examines how systems drift, how meaning degrades silently, and how design decisions are continuously rewritten through operational action.What This Book CoversWhy correct designs still fail after deploymentHow operational shortcuts quietly become architectural commitmentsReliability as preserved meaning-not just uptimeFailure as a continuous condition, not an exceptional eventTime, ordering, and partial truth in distributed systemsRecovery, migration, and change as extended failure modesLoad, pressure, backpressure, and containmentObservability as the ability to explain behaviorCost, security, and governance as architectural signalsHuman judgment and organizational structure as part of the systemHow systems age-and what allows architecture to hold over timeWhat Makes This Book DifferentOperations treated as architectureProduction behavior, failure, and recovery are examined as structural concerns, not operational afterthoughts.Decision- and consequence-focusedThe book emphasizes how choices accumulate, constrain future change, and shape long-term reliability.Tool-agnostic and durableConcepts are designed to remain relevant as platforms, frameworks, and AI systems evolve.Reliability redefinedAvailability alone is not success. Reliability is the preservation of meaning, guarantees, and trust under stress.Written for the AI era without hypeThe book situates modern data and AI-driven systems within the same architectural forces, showing where automation amplifies risk and responsibility.Who This Book Is ForThis book is written for: Software engineers operating backend and platform systemsData engineers responsible for production pipelines and storageSenior, staff, and principal engineers shaping system architectureArchitects and technical leaders accountable for long-term reliabilityPractitioners working with distributed data systems and AI platformsIt assumes familiarity with production systems and distributed environments.Who This Book Is Not ForBeginners seeking introductions or tutorialsReaders looking for step-by-step guides or tool-specific instructionsThose expecting quick fixes, patterns, or checklistsOrder now to develop architectural judgment for systems that must endure pressure, change, and time. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condición: Neu. Designing Modern Data Systems | Decision-Focused Software Architecture for Data Engineering, System Design, and Large Language Model Platforms | Jonah Prescott | Taschenbuch | Englisch | 2025 | Richa Publishing Minds | EAN 9798233501340 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data systems outlive applications, frameworks, and infrastructure.They encode decisions that shape what a system can become-and what it can never safely change.Designing Modern Data Systems is a deep, decision-driven guide to building data systems that are reliable, scalable, and adaptable over time. Rather than focusing on tools or trends, this book teaches how to reason about architecture itself: how guarantees are chosen, where authority lives, how failures manifest, and how systems evolve under real-world pressure.Written for experienced engineers and architects, the book treats data systems as long-lived sociotechnical systems-not just databases or pipelines. It focuses on clarity of responsibility, explicit trade-offs, and preserving meaning as data moves, changes, and ages.This book takes a structured journey through modern data system design:How to define data systems as distinct from applications and infrastructureHow non-functional requirements like reliability, availability, latency, and cost shape architecture long before technology choicesHow to design data models, storage engines, and indexing strategies that survive product evolutionHow to reason about replication, partitioning, coordination, and distributed transactions without accidental complexityHow batch and stream processing fit into a unified view of data over timeHow logs, history, and derived data enable recovery, reprocessing, and safe changeHow to operate systems in production with observability, backpressure, and failure isolationHow to design data systems that support machine learning and large language model platforms, including feature pipelines and embeddingsHow to migrate, evolve, and decommission systems without outages or loss of trustThroughout the book, ideas are grounded in a single evolving reference system, allowing readers to see how architectural decisions accumulate and interact as requirements change.What Makes This Book DifferentDecision-focused, not tool-drivenThe book avoids product comparisons and instead teaches how to evaluate any technology within clear architectural constraints.Explicit trade-offs, not recipesEvery design choice is examined in terms of what it enables, what it forbids, and what it costs.Modern, without being trendyAI and LLM systems are addressed where they introduce real architectural pressure-without hype or speculation.Written for longevityThe principles in this book are designed to remain relevant as tools, platforms, and organizational structures change.This book is written for:Software engineers designing backend and platform systemsData engineers responsible for storage, processing, and pipelinesStaff, principal, and senior engineers shaping architectural directionArchitects and technical leaders responsible for long-term system evolutionPractitioners preparing for system design interviews who want judgment, not templatesThis is not:A beginner's introduction to databasesA step-by-step tutorial for specific toolsA catalog of technologies or patternsInstead, it is a book about how to think clearly about data systems, and how to design them so they remain understandable, trustworthy, and changeable over time.If you are responsible for making architectural decisions-and living with their consequences-Designing Modern Data Systems is written for you.