EasyRAG is a retrieval-augmented generation framework designed for automated network operations. It combines dual-route sparse retrieval with BM25 for coarse ranking, a BGE-based LLM reranker for refinement, and LLM-based answer generation and optimization. The system requires no fine-tuning, uses minimal VRAM, and provides efficient inference through acceleration schemes. It achieved top positions in the GLM4 track of the CCF AIOps International Challenge 2024.