Isbn: 9798868827112 - fault detection in microservice architectures: integrating software fault prediction with devsecops (19 resultados)

Condición: New.

Paperback. Condición: New. In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify high-risk services before deployment, improving reliability and security. This book revisits the classical approach of using object-oriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a fault-aware DevSecOps culture. It helps you connect predictive insights to real-time decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding fault-prediction engines into Kubernetes-based orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in real-time distributed systems.What You Will LearnHow to apply statistical fault prediction using factor analysis in modern SDLC workflowsHow to integrate fault detection engines into CI/CD pipelines using DevSecOps practicesReduce production failures in microservices-based systemsApply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems.…

Paperback. Condición: New. In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify high-risk services before deployment, improving reliability and security. This book revisits the classical approach of using object-oriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a fault-aware DevSecOps culture. It helps you connect predictive insights to real-time decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding fault-prediction engines into Kubernetes-based orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in real-time distributed systems.What You Will LearnHow to apply statistical fault prediction using factor analysis in modern SDLC workflowsHow to integrate fault detection engines into CI/CD pipelines using DevSecOps practicesReduce production failures in microservices-based systemsApply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems.…

Condición: New.

Taschenbuch. Condición: Neu. Neuware -In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify high risk services before deployment, improving reliability and security. This book revisits the classical approach of using object oriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a fault aware DevSecOps culture. It helps you connect predictive insights to real time decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding fault prediction engines into Kubernetes based orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in real time distributed systems.What You Will LearnHow to apply statistical fault prediction using factor analysis in modern SDLC workflowsHow to integrate fault detection engines into CI/CD pipelines using DevSecOps practicesReduce production failures in microservices-based systemsApply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems. 210 pp. Englisch.…

Taschenbuch. Condición: Neu. Neuware -In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify high¿risk services before deployment, improving reliability and security. This book revisits the classical approach of using object¿oriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a fault¿aware DevSecOps culture. It helps you connect predictive insights to real¿time decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding fault¿prediction engines into Kubernetes¿based orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in real¿time distributed systems.What You Will Learn- How to apply statistical fault prediction using factor analysis in modern SDLC workflows- How to integrate fault detection engines into CI/CD pipelines using DevSecOps practices- Reduce production failures in microservices-based systems- Apply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems.…

Taschenbuch. Condición: Neu. Neuware - In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify high risk services before deployment, improving reliability and security. This book revisits the classical approach of using object oriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a fault aware DevSecOps culture. It helps you connect predictive insights to real time decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding fault prediction engines into Kubernetes based orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in real time distributed systems.What You Will LearnHow to apply statistical fault prediction using factor analysis in modern SDLC workflowsHow to integrate fault detection engines into CI/CD pipelines using DevSecOps practicesReduce production failures in microservices-based systemsApply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems.…

Condición: NEW.

Paperback. Condición: New. In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify high-risk services before deployment, improving reliability and security. This book revisits the classical approach of using object-oriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a fault-aware DevSecOps culture. It helps you connect predictive insights to real-time decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding fault-prediction engines into Kubernetes-based orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in real-time distributed systems.What You Will LearnHow to apply statistical fault prediction using factor analysis in modern SDLC workflowsHow to integrate fault detection engines into CI/CD pipelines using DevSecOps practicesReduce production failures in microservices-based systemsApply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems.…

Taschenbuch. Condición: Neu. Fault Detection in Microservice Architectures | Integrating Software Fault Prediction with DevSecOps | Deepak Sharma (u. a.) | Taschenbuch | xxi | Englisch | 2026 | Apress | EAN 9798868827112 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Taschenbuch. Condición: Neu. Neuware -In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify high¿risk services before deployment, improving reliability and security. This book revisits the classical approach of using object¿oriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a fault¿aware DevSecOps culture. It helps you connect predictive insights to real¿time decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding fault¿prediction engines into Kubernetes¿based orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in real¿time distributed systems.What You Will Learn- How to apply statistical fault prediction using factor analysis in modern SDLC workflows- How to integrate fault detection engines into CI/CD pipelines using DevSecOps practices- Reduce production failures in microservices-based systems- Apply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 210 pp. Englisch.…

Condición: New.

Paperback. Condición: New. In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify high-risk services before deployment, improving reliability and security. This book revisits the classical approach of using object-oriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a fault-aware DevSecOps culture. It helps you connect predictive insights to real-time decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding fault-prediction engines into Kubernetes-based orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in real-time distributed systems.What You Will LearnHow to apply statistical fault prediction using factor analysis in modern SDLC workflowsHow to integrate fault detection engines into CI/CD pipelines using DevSecOps practicesReduce production failures in microservices-based systemsApply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems.…

Taschenbuch. Condición: Neu. Neuware -In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify high¿risk services before deployment, improving reliability and security. This book revisits the classical approach of using object¿oriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a fault¿aware DevSecOps culture. It helps you connect predictive insights to real¿time decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding fault¿prediction engines into Kubernetes¿based orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in real¿time distributed systems.What You Will LearnHow to apply statistical fault prediction using factor analysis in modern SDLC workflowsHow to integrate fault detection engines into CI/CD pipelines using DevSecOps practicesReduce production failures in microservices-based systemsApply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems. 232 pp. Englisch.…

Paperback. Condición: new. Paperback. In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify highrisk services before deployment, improving reliability and security. This book revisits the classical approach of using objectoriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a faultaware DevSecOps culture. It helps you connect predictive insights to realtime decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding faultprediction engines into Kubernetesbased orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in realtime distributed systems.What You Will LearnHow to apply statistical fault prediction using factor analysis in modern SDLC workflowsHow to integrate fault detection engines into CI/CD pipelines using DevSecOps practicesReduce production failures in microservices-based systemsApply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condición: new. Questo è un articolo print on demand.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify high risk services before deployment, improving reliability and security. This book revisits the classical approach of using object oriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a fault aware DevSecOps culture. It helps you connect predictive insights to real time decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding fault prediction engines into Kubernetes based orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in real time distributed systems.What You Will LearnHow to apply statistical fault prediction using factor analysis in modern SDLC workflowsHow to integrate fault detection engines into CI/CD pipelines using DevSecOps practicesReduce production failures in microservices-based systemsApply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems. 210 pp. Englisch.…

Paperback. Condición: new. Paperback. In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify highrisk services before deployment, improving reliability and security. This book revisits the classical approach of using objectoriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a faultaware DevSecOps culture. It helps you connect predictive insights to realtime decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding faultprediction engines into Kubernetesbased orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in realtime distributed systems.What You Will LearnHow to apply statistical fault prediction using factor analysis in modern SDLC workflowsHow to integrate fault detection engines into CI/CD pipelines using DevSecOps practicesReduce production failures in microservices-based systemsApply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condición: new. Paperback. In the age of continuous delivery and microservices, the difference between resilient software and production chaos lies in proactive fault detection. This book shows how to harness the power of predictive analytics and DevSecOps to find weaknesses before they cause outages or security issues.Blending software engineering theory with actionable implementation guidance for distributed, containerized environments, the book will teach you how to identify highrisk services before deployment, improving reliability and security. This book revisits the classical approach of using objectoriented metrics and linear regression but significantly enhances it through factor analysis. Beyond the math and metrics, this book offers a practical roadmap for building a faultaware DevSecOps culture. It helps you connect predictive insights to realtime decisions, improving reliability, security, and deployment confidence across distributed systems. You will also learn about architectural guidelines on embedding faultprediction engines into Kubernetesbased orchestration platforms for runtime monitoring.Bridging a critical gap between predictive analytics in software quality assurance and modern DevSecOps practices, it establishes a viable pathway for using statistical modeling techniques not just to predict defects, but to inform actionable security and operational decisions in realtime distributed systems.What You Will LearnHow to apply statistical fault prediction using factor analysis in modern SDLC workflowsHow to integrate fault detection engines into CI/CD pipelines using DevSecOps practicesReduce production failures in microservices-based systemsApply OO metrics like CK and Halstead in predictive modelsWho This Book Is ForThis book is for software engineers, DevOps and DevSecOps professionals, SREs, and researchers interested in building reliable, fault-tolerant systems. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…