Tag: MLOps

3 articles

• LLM Model Artifact Supply Chain in Production: Protecting Against Weight Tampering with Safetensors, Signatures, and Admission Scanning

  A practical guide to securing the LLM model supply chain—from download, signing, and scanning to production admission. Covers safetensors, source verification, SBOMs, canary releases, and rollback strategies to mitigate weight contamination risks for open-source and internal model registries.

  07/06/2026 LLM / MLOps / Supply Chain Security / Model Registry / safetensors

• LLM Fine-Tuning Data Governance: Stabilizing Model Quality with Versioning, Deduplication, and Contamination Detection

  An engineering deep dive into governing LLM fine-tuning datasets as production assets. Covers data version tracking, multi-level deduplication, train/validation contamination detection, quality gates, and model release rollback for trustworthy, reproducible, and auditable management.

  07/03/2026 LLM Fine-Tuning / Data Governance / Data Versioning / MLOps / Production AI

• Continuous Batching in Production: Boosting LLM Serving Throughput with Dynamic Batching

  A systematic deep dive into Continuous Batching for LLM inference serving—covering principles, scheduling, engineering deployment, monitoring metrics, and go-live checklists to reduce queuing waste and maximize GPU throughput.

  07/01/2026 LLM Serving / Continuous Batching / Inference Optimization / KV Cache / MLOps