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- Aditya Rautaray
Aditya Rautaray

Dernière sortie
“The AI Ops Convergence: Unifying MLOps, DataOps, and Cyber Defense in the Cloud".
This book explores the convergence of AIOps, MLOps, DataOps, and SecOps in modern cloud-native environments. It examines how artificial intelligence, automation, and advanced analytics are transforming IT operations, enabling organizations to manage complex infrastructures with greater efficiency, reliability, and security. The text covers key domains such as machine learning lifecycle engineering, modern data architectures, cloud-native infrastructure, and cybersecurity operations, while highlighting the role of observability, governance, and responsible AI practices.
It also discusses technologies including containers, Kubernetes, infrastructure as code, and automated security frameworks that support scalable AI-driven operations. Designed for cloud architects, data engineers, security professionals, and IT leaders, the book provides practical insights into building unified AIOps platforms that integrate data, machine learning, and security operations for resilient enterprise systems.
It also discusses technologies including containers, Kubernetes, infrastructure as code, and automated security frameworks that support scalable AI-driven operations. Designed for cloud architects, data engineers, security professionals, and IT leaders, the book provides practical insights into building unified AIOps platforms that integrate data, machine learning, and security operations for resilient enterprise systems.
This book explores the convergence of AIOps, MLOps, DataOps, and SecOps in modern cloud-native environments. It examines how artificial intelligence, automation, and advanced analytics are transforming IT operations, enabling organizations to manage complex infrastructures with greater efficiency, reliability, and security. The text covers key domains such as machine learning lifecycle engineering, modern data architectures, cloud-native infrastructure, and cybersecurity operations, while highlighting the role of observability, governance, and responsible AI practices.
It also discusses technologies including containers, Kubernetes, infrastructure as code, and automated security frameworks that support scalable AI-driven operations. Designed for cloud architects, data engineers, security professionals, and IT leaders, the book provides practical insights into building unified AIOps platforms that integrate data, machine learning, and security operations for resilient enterprise systems.
It also discusses technologies including containers, Kubernetes, infrastructure as code, and automated security frameworks that support scalable AI-driven operations. Designed for cloud architects, data engineers, security professionals, and IT leaders, the book provides practical insights into building unified AIOps platforms that integrate data, machine learning, and security operations for resilient enterprise systems.
