Self-Hosted Databricks Alternative: Homelab Data Lakehouse (AI/ML Data Factory)
Self-Hosted Databricks Alternative: Homelab Data Lakehouse Part of the homelab build series. Trino, Apache Iceberg, Project Nessie, dbt, Spark, MLfl…
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MLOps: models that survive production · 2. Data versioning
MLOps: models that survive production · Chapter 2 of 12 · AI Engineering · new chapter every Thursday night By the end of this chapter: Reproduce a…
Your AI Code Can Be Elegant Too
As the Machine Learning Engineering Manager at an AI-powered SaaS company, I get a front-row seat to the machine learning (ML) code written by data…
Moving Your Local Airflow to GCP for under $150 a month
My team runs ML training and prediction pipelines on Vertex AI. For a long time, the thing telling those pipelines when to run was Apache Airflow, i…
Owning vs. Renting Intelligence: Why Enterprises Are Building Sovereign AI
When Mythos went dark in June 2026, the reaction across the tech ecosystem wasn’t just disappointment. It was a collective chill down the spine of e…
Mastering LLM-as-Judge: Automated Annotation and Triage for Production AI Failures
Mastering LLM-as-Judge: Automated Annotation and Triage for Production AI Failures Every single time you push a new system prompt or swap out an und…
Deploying Kubeflow as an Azure ML Alternative
Azure Machine Learning is Microsoft's cloud-native machine learning platform that provides experiment tracking, managed compute, pipelines, a model…
MLOps Best Practices 2026
MLOps Best Practices 2026 {"title": "MLOps Best Practices 2026: Scaling AI from Prototype to Enterprise Production", "content": "### Introduction\n\…
Why LLM Cascades Fail for Interactive Apps — Use Router
Stop Defaulting to Cascades: Why Router-First Wins for Interactive Apps (LLM routing vs cascading) The question of "LLM routing vs cascading" is not…
Building a Production-Grade End-to-End MLOps Pipeline from Scratch
Building a Production-Grade End-to-End MLOps Pipeline from Scratch Most machine learning tutorials end at model.fit() . But in the real world, train…
How to Build an Enterprise-Grade, Automated MLOps Pipeline on AWS
A comprehensive blueprint for orchestrating continuous training, governance, and canary deployments with automated rollbacks. Executive Summary &…
Migrating to Native Git in SageMaker Unified Studio
Version control in analytical data platforms has always been a second-class citizen — tolerated, not designed. SageMaker Unified Studio just changed…
Four bugs from building a platform where AI agents publish autonomously
I spent six weeks building a publication where AI agents write articles, an automated moderator approves or rejects them, and no human reviews anyth…
When Should You Retrain Your ML Model? A New Study Says Most Teams Are Solving the Wrong Problem
Every production ML model starts degrading the moment it ships. Customer behavior shifts, fraud patterns evolve, market conditions change — the tech…
[Перевод] Масштабирование LLM: от одного чипа до ЦОДа. Глава 5. Инференс
Предыдущая глава Ну а теперь рассмотрим, как нам применить обученный трансформер. И применение уже обученной модели сильно отличается от тренировки,…
The Serverless Equation: Conquering the Cold Start in Real-Time AI Inference
In our inaugural issue , we established that the future of enterprise AI lies not merely in raw model parameters, but in the architectural paradigms…
You're Not Paying for Compute. You're Paying for Memory Bandwidth
TL;DR— Inference cost conversations obsess over FLOPs and token prices, but the real constraint on LLM serving is memory bandwidth— specifically the…
От legacy до промышленной платформы: инженерная эволюция OSA в «Магнит»
Как мы провели проект через четыре «эпохи» — от ручных запусков на Windows‑планировщике до Spark + k8s на масштабе сет…
Can your AI agent actually manage ML infrastructure?
I’ve spent enough time in production environments to know that 'chatting with an AI' is a useless metric if the AI can't touch the actual hardware o…
Your Guardrails Are a Firewall. Your Failures Are a Cascade
TL;DR— Most production AI teams build safety layers using the content-moderation mental model: classify input, classify output, block or pass. But t…
Three weeks before the enterprise contract, the voice agent wasnt operator-ready.
Three weeks before the enterprise contract, the voice agent wasn't operator-ready Look. We had 99.2% uptime in staging. We had eval coverage on 1,40…
Azure Databricks for MLOps and Feature Engineering at Scale with Apache Spark, Delta Lake, and MLflow
Raw data doesn't win model competitions. Features do. And when your raw data is tens of billions of rows sitting across multiple sources, you can't…
What Is an Agent Registry? (And What We Broke Before We Had One)
TL;DR An AI agent registry is a centralized catalog of every agent in your organization — what each agent does, what tools it can access, what versi…
MLOps for LLM: A Case Study on Dresscode
I've recently participated in the Gemma 4 challenge here on DEV.to, but fell short compared to many amazing projects. I really liked LIKAS . I encou…
Channels-last memory format cut our conv backbone latency 22%
TL;DR: Switching our convolutional segmentation backbone to PyTorch's channels-last memory format cut inference latency by about 22% on A100s, with…
The SDXL VAE overflow that decoded black images in fp16
TL;DR: The SDXL VAE decoder pushes activations past 65504, the max value fp16 can hold, so the last decode step overflows to inf and you get a fully…
AI Workloads Are Reshaping Kubernetes in 2026: GPU Scheduling, MLOps, and the Platform Engineering Reckoning
How GPU scheduling complexity and MLOps integration are forcing platform teams to rearchitect Kubernetes clusters before operational debt becomes in…
Why multi-agent orchestration is harder than it looks
One AI agent answering a question is useful. Five agents that divide a complex task, pass state to each other, and act on live enterprise systems is…
Почему пилоты ИИ не масштабируются? У них нет системы управления
Пилот ИИ может хорошо работать на демонстрации и всё равно быть не готовым к промышленной эксплуатации. В статье разберем, какие элементы управления…
RLAIF Is Eating RLHF — Here Are the Four Places Human Feedback Still Wins
RLAIF is having a moment. Walk through any alignment paper or vendor pitch from the last six months and you'll see the same claim: replace your huma…