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Inference Engine Internals: Continuous Batching, Prefix Cache, Speculative Decoding Deployment and Operations Advanced Throughput and tail latency pull against each other, and the tension comes down to scheduling and memory. Why static batching wastes capacity, what Continuous Batching and chunked prefill cost to build, how PagedAttention pages memory, when a high Prefix Cache hit rate backfires, and why the acceptance rate of Speculative Decoding sets your speedup. 2026-10 ·76 min read DeepSeek Performance Tuning Tutorial Deployment and Operations Advanced Complete DeepSeek performance tuning guide: GPU memory optimization, batching strategies, quantization techniques, concurrency control, and latency optimization. Includes profiling tool usage, performance benchmarking, and best practices to achieve an optimal balance between throughput and latency. 2025-06 ·25 min read DeepSeek Inference Acceleration In-Depth Tutorial Deployment and Operations Advanced Comprehensively master DeepSeek model inference acceleration techniques. In-depth comparison of four major engines: vLLM, SGLang, TensorRT-LLM, and llama.cpp, from deployment to tuning, from single GPU to distributed, providing a complete inference acceleration solution. 2025-06 ·25 min read LLM Inference Performance Optimization: vLLM and Continuous Batching Deployment and Operations Advanced After model deployment, throughput and latency are core metrics. This article provides an in-depth analysis of vLLM's PagedAttention and Continuous Batching principles, and gives a complete optimization roadmap from benchmark testing, parameter tuning to production deployment. 2026-08 ·23 min read DSH Plugin Release, Defensive Programming & Incident Review Deployment and Operations Advanced Three ways to distribute DSH plugins, version conventions, pre-release checks, five defensive patterns, and the dsh incident review discipline for your team. 2026-09 ·39 min read Plugin Config & Bundle/Profile Layers: How dsh Resolves Effective Config Deployment and Operations Advanced How dsh layers plugin schema defaults, Profile, Bundle, user overrides and CLI patches. Use dsh --dump-config to trace effective values, manifest roles and override priority. 2026-09 ·52 min read Best Practices for Large Model API Service Deployment and Operations Advanced API-fying LLM capabilities is a key step for enterprise-level applications. This article systematically explains best practices for LLM API services from dimensions such as architecture design, rate limiting strategies, cache optimization, and security protection. 2025-06 ·20 min read GPU Cluster Management and Scheduling Deployment and Operations Advanced Managing a cluster of dozens of GPUs requires professional scheduling strategies. This article explains practical experience in GPU resource management, task priority scheduling, memory fragmentation cleanup, and multi-tenant isolation. 2026-07 ·23 min read In-Depth Guide to GPU-Accelerated Inference Optimization Deployment and Operations Advanced GPU inference optimization is key to reducing the cost of large model deployment. This article provides an in-depth explanation of core technologies such as FlashAttention, quantized inference, TensorRT acceleration, and continuous batching to help you maximize GPU utilization. 2025-07 ·19 min read Monitoring and Observability for AI Applications Deployment and Operations Advanced Observability for AI applications is far more complex than for traditional applications—it requires monitoring multiple dimensions such as LLM call latency, token consumption, hallucination rate, and user satisfaction. This article builds a complete AI application monitoring system, covering metric collection, alert configuration, cost tracking, and quality monitoring. 2026-07 ·20 min read