Platform and DevOps engineer working on Kubernetes, AWS, and cloud-native infrastructure. CKA certified. Ex-Atlan, LFX mentee at CNCF Thanos, Kubeflow contributor.https://milinddethe15.tech/https://milinddethe15.tech/posts/mlops/day7/https://milinddethe15.tech/posts/mlops/day7/Learn how model serving, monitoring, drift detection, and retraining complete the MLOps lifecycle after deployment.Fri, 19 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/mlops/day6/https://milinddethe15.tech/posts/mlops/day6/Learn about feature stores, training-serving skew, and why machine learning teams use platforms like Feast to keep training and production data consistent.Thu, 18 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/mlops/day5/https://milinddethe15.tech/posts/mlops/day5/Learn why machine learning workflows evolve from Python scripts into pipelines and how Kubeflow Pipelines orchestrates reproducible ML workflows on Kubernetes.Wed, 17 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/mlops/day4/https://milinddethe15.tech/posts/mlops/day4/Learn how machine learning teams improve model performance using cross validation, hyperparameter tuning, AutoML, and parallel experimentation.Tue, 16 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/mlops/day3/https://milinddethe15.tech/posts/mlops/day3/Learn why machine learning teams need data versioning and experiment tracking, and how tools like DVC and MLflow help make experiments reproducible.Mon, 15 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/mlops/day2/https://milinddethe15.tech/posts/mlops/day2/Learn why Jupyter notebooks are great for experimentation but insufficient for reproducible machine learning workflows.Sun, 14 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/mlops/day1/https://milinddethe15.tech/posts/mlops/day1/Why DevOps alone is not enough for machine learning and how MLOps addresses data, models, and training-serving skew.Sat, 13 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/day-7-ai-platform-engineering/https://milinddethe15.tech/posts/day-7-ai-platform-engineering/A complete AI platform: layers, services, infrastructure, and where tools like vLLM, Ray, and Kubernetes fit together.Wed, 10 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/day-6-ai-platform-engineering/https://milinddethe15.tech/posts/day-6-ai-platform-engineering/Why vLLM exists: batching, PagedAttention, and efficient GPU memory management for LLM serving.Tue, 09 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/day-5-ai-platform-engineering/https://milinddethe15.tech/posts/day-5-ai-platform-engineering/Why Ray exists: scheduling computation (tasks & actors) vs infrastructure for distributed AI workloads.Mon, 08 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/day-4-ai-platform-engineering/https://milinddethe15.tech/posts/day-4-ai-platform-engineering/Why AI scheduling differs from traditional apps: gang scheduling, topology awareness, and specialized schedulers.Sun, 07 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/day-3-ai-platform-engineering/https://milinddethe15.tech/posts/day-3-ai-platform-engineering/Why GPU utilization is hard: resource fragmentation, sharing strategies (MIG, time-slicing, batching), and cost impacts.Sat, 06 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/day-2-ai-platform-engineering/https://milinddethe15.tech/posts/day-2-ai-platform-engineering/How Kubernetes discovers GPUs: drivers, device plugins, and making GPUs schedulable resources.Fri, 05 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/day-1-ai-platform-engineering/https://milinddethe15.tech/posts/day-1-ai-platform-engineering/Why AI workloads demand different platform engineering: GPUs change bottlenecks and resource priorities.Thu, 04 Jun 2026 00:00:00 GMThttps://milinddethe15.tech/posts/lfx-mentorship/https://milinddethe15.tech/posts/lfx-mentorship/Wed, 04 Dec 2024 00:00:00 GMT