Synopsis

Authored by Vikram Singh Sankhala, "AI-Powered Agricultural Analytics Platform: DevOps Implementation Plan" serves as a comprehensive, hands-on guide to building a sophisticated cloud-native platform that integrates IoT sensor data and satellite imagery with ML models for real-time agricultural insights like yield prediction and pest detection. The book directly addresses the challenges of creating scalable, secure, and compliant analytics systems, providing a detailed, stage-by-stage implementation plan. It guides readers through infrastructure provisioning, CI/CD pipeline setup, microservice deployment, monitoring, and disaster recovery, leveraging state-of-the-art tools like Terraform, Kubernetes, Jenkins, ArgoCD, Prometheus, and more, demonstrating their practical application in a real-world agricultural context. Beyond theoretical concepts, this book focuses on actionable learning, showing how to automate builds, tests, deployments, and security checks, and how to ensure system resilience and observability. It emphasizes the integration of various tools and technologies to achieve continuous integration, delivery, and improvement. By walking through a sample workflow and detailing tool choices within the context of project stages, the book empowers DevOps Engineers, Software Developers, SREs, and other technical professionals to immediately apply Next-Gen DevOps principles to their own complex projects, fostering collaboration and driving efficiency in their organizations.

AI-Powered Agricultural Analytics Platform: DevOps Implementation Plan

Vikram Singh Sankhala

English

AI-Powered Agricultural Analytics Platform: DevOps Implementation Plan

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