3 papers
cs.SE2026
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…
cs.SE2026
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…
cs.DB2026
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…