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Building Reliable and Scalable Digital Systems: An Engineering Practitioner's Account of Durable Systems
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- FormatePub
- ISBN8235918542
- EAN9798235918542
- Date de parution29/05/2026
- Protection num.pas de protection
- Infos supplémentairesepub
- ÉditeurIoakim Ioakim
Résumé
Building Reliable and Scalable Digital Systems: An Engineering Practitioner's Account of Durable Systems is a comprehensive exploration of how modern software systems are designed, operated, and evolved to remain dependable under massive scale, unpredictable workloads, and real-world operational failures. Written from the perspective of an experienced engineering practitioner, the book bridges the gap between theoretical system design and the practical realities of building resilient digital platforms that support millions of users and mission-critical operations.
The book begins by introducing the foundations of digital system reliability and scalability. It explains why modern enterprises-from banking and healthcare to e-commerce, transportation, cloud computing, and telecommunications-depend on systems that can sustain continuous growth without sacrificing stability or performance. Readers are introduced to the core engineering principles behind durable systems, including fault tolerance, distributed architectures, redundancy, graceful degradation, observability, and operational resilience.
A major focus of the book is the evolution of software architecture from traditional monolithic systems to cloud-native and microservices-based ecosystems. Through practical examples and engineering narratives, the author demonstrates how organizations redesign applications to achieve elasticity, modularity, and faster deployment cycles. Topics such as containerization, orchestration platforms, service meshes, API gateways, and event-driven architectures are explored in detail, helping readers understand how modern platforms achieve scalability while maintaining reliability.
The book also provides deep insights into infrastructure engineering and cloud scalability. It explains how compute, storage, networking, and distributed databases interact to support high-throughput digital platforms. Readers learn how engineering teams design systems capable of handling traffic spikes, regional outages, hardware failures, and latency-sensitive workloads. The discussion extends to multi-cloud deployments, edge computing, autoscaling strategies, infrastructure-as-code, and cost-performance optimization.
The book begins by introducing the foundations of digital system reliability and scalability. It explains why modern enterprises-from banking and healthcare to e-commerce, transportation, cloud computing, and telecommunications-depend on systems that can sustain continuous growth without sacrificing stability or performance. Readers are introduced to the core engineering principles behind durable systems, including fault tolerance, distributed architectures, redundancy, graceful degradation, observability, and operational resilience.
A major focus of the book is the evolution of software architecture from traditional monolithic systems to cloud-native and microservices-based ecosystems. Through practical examples and engineering narratives, the author demonstrates how organizations redesign applications to achieve elasticity, modularity, and faster deployment cycles. Topics such as containerization, orchestration platforms, service meshes, API gateways, and event-driven architectures are explored in detail, helping readers understand how modern platforms achieve scalability while maintaining reliability.
The book also provides deep insights into infrastructure engineering and cloud scalability. It explains how compute, storage, networking, and distributed databases interact to support high-throughput digital platforms. Readers learn how engineering teams design systems capable of handling traffic spikes, regional outages, hardware failures, and latency-sensitive workloads. The discussion extends to multi-cloud deployments, edge computing, autoscaling strategies, infrastructure-as-code, and cost-performance optimization.