5 papers
From Inference Engine to Inference Control Plane: Connecting vLLM, llm-d, and the Evolution of Efficient Distributed LLM Serving
Twinkll Sisodia
Large language model (LLM) inference is evolving from an engine-local optimization problem into a distributed control problem involving reusable state, phase placement, heterogeneo…
Toward Sustainable Distributed LLM Inference: A Systems Synthesis and Research Agenda for an Energy-, Carbon-, and Cache-Aware llm-d Control Plane
Twinkll Sisodia
Large language model (LLM) sustainability is increasingly a serving-systems problem, not only a training problem. In production, energy and carbon impact depend on more than model…
AI Observability for Large Language Model Systems: A Multi-Layer Analysis of Monitoring Approaches from Confidence Calibration to Infrastructure Tracing
Twinkll Sisodia
The deployment of large language models (LLMs) in production environments has created an urgent need for observability systems that span the full stack -- from model internals to G…
AI Observability for Developer Productivity Tools: Bridging Cost Awareness and Code Quality
Happy Bhati, Twinkll Sisodia
As AI-assisted development tools proliferate, developers face a growing challenge: understanding the cost, quality, and behavioral patterns of AI interactions across their workflow…
From Natural Language to PromQL: A Catalog-Driven Framework with Dynamic Temporal Resolution for Cloud-Native Observability
Twinkll Sisodia
Modern cloud-native platforms expose thousands of time series metrics through systems like Prometheus, yet formulating correct queries in domain-specific languages such as PromQL r…