Cloud architecture engineering (16 Ergebnisse)

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- Internationale Ausgabe
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Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed… on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.
Weitere Bilder- Hardcover
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Zustand: As New. Like New and Unread.

Sprache: Englisch
Verlag: Orange Education Pvt Ltd, 2024
Serie: Buch 1 von 2 - Cloud Data Engineering — Warehousing Path
- Softcover
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Zustand: New. In.

- Softcover
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Zustand: New.

Sprache: Englisch
Verlag: Independently Published Jun 2026, 2026
- Softcover
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Taschenbuch. Zustand: Neu. Neuware - Walk into your data engineering interview ready for every round.Most people don't fail data engineering interviews because they lack skill. They fail because no one showed them what each round is really testing, or how to answer under pressure. This book fixes that. Data Engineering Interview… Mastery & System Design is a complete, end-to-end preparation guide that follows the real shape of a modern DE interview, from SQL and Python fundamentals to the senior system design rounds where the best offers are won and lost. What you'll master: - SQL interview problems: joins, window functions, CTEs, indexing, and query optimization- Python for data engineers: generators, decorators, OOP, concurrency, and 'what does this print ' questions- Warehousing & modeling: OLTP vs OLAP, star and snowflake schemas, slowly changing dimensions, and Data Vault- Lakes & lakehouses: Delta/Iceberg, ACID on files, schema evolution, and the medallion architecture- Big data & cloud: Spark internals, shuffles and data skew, Kafka delivery guarantees, AWS, and Airflow- System design: a repeatable framework plus four full designs - Batch ETL, Real-Time Streaming, Data Lakehouse, and a 5-billion-events/day Clickstream platform- Career mastery: resume, LinkedIn, portfolio projects, mock interviews, and salary negotiationWhy this book is different : Every key question follows a proven 8-part format - Question, Why Interviewers Ask, Simple Answer, Detailed Explanation, Real Business Example, Common Mistakes, Follow-up Questions, and Difficulty - so you don't just memorize an answer, you understand it and handle the follow-ups that actually decide the outcome. You also get 285+ rapid-fire questions in the appendices (Top 100 SQL, Top 50 Python, Top 50 Spark, Top 30 Kafka, Top 30 AWS, Top 25 System Design) and quick-reference cheat sheets for last-minute revision the night before. Who it's for : Freshers and career switchers, ETL/QA/analyst professionals moving into data engineering, software engineers crossing over, and experienced engineers targeting senior roles. Nobody is talked down to, and nothing is padded. This isn't a list of facts to memorize. It teaches you to think the way a data engineer thinks: clarify the problem, reason about how systems behave and fail, weigh the trade-offs, and say it all clearly out loud. The work ahead is real, and it's learnable. Scroll up, grab your copy, and start preparing the way the engineers who get hired do.

- Hardcover
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Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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EUR 33,00
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Taschenbuch. Zustand: Neu. Neuware - Build scalable, resilient, and cost efficient systems without managing serversServerless is not just about running code without servers.It is about designing systems that respond to events, scale automatically, and reduce operational overhead.'Serverless at Scale' is a practical, engineering…focused guide to building production ready serverless applications using modern cloud services, event driven patterns, and cost aware architecture.This book teaches you how to design systems that are fast to ship, easy to operate, and ready for real world demand.Why serverless architecture mattersTraditional infrastructure often requires constant provisioning, scaling, patching, and maintenance.Serverless systems help teams: - scale automatically with demand- reduce infrastructure management- respond to events in real time- lower operational costs- build faster with managed servicesBut serverless only works well when designed with the right patterns. This book shows you how.What you will learn- fundamentals of serverless architecture- event driven system design- Lambda function patterns and best practices- API driven and queue based workflows- asynchronous processing strategies- data storage and integration patterns- observability, logging, and tracing- security and access control for serverless systems- performance tuning and cold start reduction- cost optimization for cloud workloadsFrom functions to scalable systemsThroughout the book, you will learn how to: - design event driven applications- connect functions, queues, APIs, and databases- handle retries, failures, and dead letter queues- build resilient serverless workflows- monitor production systems effectively- optimize cost without sacrificing reliabilityEach chapter focuses on real production engineering practices.Practical applications- serverless APIs- workflow automation systems- event driven microservices- real time data processing- cloud native SaaS backends- cost efficient startup infrastructureThese examples reflect real world cloud engineering use cases.Who this book is for- cloud engineers- backend developers- DevOps engineers- software architects- startup builders- teams moving to event driven systemsIf you want to build scalable cloud systems without managing servers, this book provides the roadmap.Design around events.Scale automatically.Engineer serverless systems that last.

- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Neuware - Kubernetes dominates container orchestration because it solved a real problem: human operators cannot manually place, recover, and scale workloads across hundreds of nodes. Yet the system that eliminated one layer of complexity introduced another. Born from Google's Borg but stripped of its h…omogeneous, privileged environment, Kubernetes evolved into a modular federation of semi-independent components-each with distinct failure modes, version cycles, and vendor priorities.This book examines Kubernetes not as a finished product, but as an ongoing architectural compromise. You will learn why the Container Runtime, Network, and Storage interfaces that freed the ecosystem from vendor lock-in simultaneously created unpredictable latency surfaces and policy conflicts. You will see how scheduler decisions collide with resource quotas, how network overlays amplify latency under pressure, and how autoscaling controllers can trigger destabilizing feedback loops. Through production postmortems from large-scale environments, the text reveals why workload failures are rarely singular-and why reasoning about cascading interactions is now the central skill of platform engineering.The book also confronts unresolved scaling tensions. Kubernetes was originally optimized for clusters of thousands of nodes; modern environments routinely exceed that boundary, forcing painful choices between vertical cluster growth and multi-cluster coordination. It traces the shift from treating clusters as permanent infrastructure to viewing them as disposable scheduling domains-a conceptual change that redefines reliability engineering for cloud-native systems.What You Will Learn - Why Kubernetes rejected Mesos's two-level scheduling-and how that centralized decision created today's fairness and preemption challenges - How CRI, CNI, and CSI abstractions solved vendor politics while fragmenting operational predictability - The real reason production postmortems blame interaction patterns, not individual components - Why autoscaling, resource quotas, and network overlays form a hidden feedback loop that can destabilize utilization - The architectural entropy created by admission controllers, custom resource definitions, and policy engines - When to scale vertically versus distributing across clusters, and why hybrid federation is becoming the dominant patternIf your team runs production Kubernetes at scale, this book delivers the architectural clarity and operational rigor to build systems that fail gracefully rather than catastrophically. Read it before your next postmortem.

- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
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Zustand: New. In.

- Hardcover
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Zustand: Used. pp. 218.

- Hardcover
Anbieter: Biblios, frankfurt am main, HESSE, DeutschlandBiblios
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Zustand: Used. pp. 218.

- Hardcover
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Zustand: New.

- Hardcover
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Hardcover. Zustand: Brand New. 218 pages. 11.00x8.90x0.80 inches. In Stock.

- Hardcover
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Zustand: New. Contains novel subject matter that is relevant to computer scienceIncludes the expertise of contributing authorsPresents an easy to comprehend writing styleVolume Editor: Pushan Kumar DuttaDr. Pushan Kumar.

- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
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Zustand: New. In.

Sprache: Englisch
Verlag: Elsevier Science & Technology, Academic Press Feb 2026, 2026
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Buch. Zustand: Neu. Neuware - Cloud-native Architecture (CNA) and Artificial Intelligence (AI) for the Future of Software Engineering: The Principles, Patterns, Platforms and Practices, Volume 141 in the Advances in Computers series, explores the convergence of artificial intelligence, machine learning, and modern software engin…eering practices. Chapters in this new release include Demystifying the Cloud-native Artificial Intelligence (CNAI) Paradigm, Articulating Machine and Deep Learning Models for Next-Generation Software Development, Delineating Artificial Intelligence (AI) and Its Potentials for Automated Software Engineering, Leveraging Machine and Deep Learning (ML/DL) Algorithms towards AI Models for Automating Software Development, and more.Other sections cover Artificial Intelligence (AI) Technologies and Tools for Accelerated Software Development, Demystifying the Agentic AI Paradigm for Accelerated Software Engineering, Detailing AI Techniques and Tools for Software Engineering Acceleration and Automation, Generative AI Tools for Accelerated Software Engineering, Empowering Software Engineering Automation through Explainable AI, and much more.