Fault Detection in Microservice Architectures

Integrating Software Fault Prediction with DevSecOps

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Éditeur :

Apress

Paru le : 2026-06-10

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. Blend...
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Éditeur

Collection
n.c

Parution
2026-06-10

Pages
210 pages

EAN papier
9798868827112

Auteur(s) du livre


Deepak Sharma is Associate Director at the School of Open Learning, University of Delhi, and a seasoned researcher in software engineering and fault prediction, with over a decade years of experience . He holds a Ph.D. in Computer Science and multiple advanced degrees in technology and applications. His academic work focuses on software quality improvement, defect prediction models, and statistical analysis of software metrics. He has published extensively in international journals and conferences and has been recognized by several government bodies for his research contributions. Aamiruddin Syed is a cybersecurity engineer and DevSecOps practitioner with deep expertise in secure software development, cloud-native architectures, and supply chain security . He has led DevSecOps implementations across global enterprises, integrating predictive risk models into CI/CD pipelines and Kubernetes-based environments. Aamiruddin is the author of Supply Chain Software Security: AI, IoT, and Application Security (Apress, 2024) and a frequent speaker at DEFCON, Black Hat MEA, RSA and other international cybersecurity forums. His insights ensure that the book translates rigorous models into actionable, real-world strategies for developers, security engineers, and SRE teams.  

Caractéristiques détaillées - droits

EAN PDF
9798868827129
Prix
62,11 €
Nombre pages copiables
2
Nombre pages imprimables
21
Taille du fichier
5274 Ko
EAN EPUB
9798868827129
Prix
62,11 €
Nombre pages copiables
2
Nombre pages imprimables
21
Taille du fichier
860 Ko

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