LLMs for Modern Software Delivery and DevOps by Gu Huangliang (.ePUB)+
File Size: 40 MB
LLMs for Modern Software Delivery and DevOps: Applying Large Language Models to Software Delivery and SRE by Gu Huangliang, Zheng Qingzheng, Niu Xiaoling, Che Xin
Requirements: .ePUB reader, 40 mb / .PDF reader, 21 mb
Overview: If you work in software engineering, DevOps, SRE, or platform teams, this book written by enterprise digital transformation specialists demonstrates how large language models (LLMs) can enhance automation, software delivery, and operational reliability across modern engineering organizations.
To build familiarity, the book begins hands-on with the technical underpinnings of LLMs, including Transformers, GPT architectures, and fine-tuning techniques such as LoRA and QLoRA. It then develops these foundations to demonstrate how retrieval-augmented generation (RAG) and agent-based systems can be embedded into real enterprise workflows. Across development, testing, operations, security, and project management scenarios, you will see how LLMs enhance code generation, automate testing, improve log analysis and incident response, support root cause analysis, and assist in risk-based decision-making.
By the end of the book, you will be able to move from isolated model experimentation to scalable enterprise practice, designing intelligent DevOps and SRE workflows that are efficient, reliable, and strategically aligned.
Genre: Non-Fiction > Tech & Devices
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