Showing 9 articles
How to Persist State in Time-Series Models with Docker and Redis
Have you ever built a brilliant time-series model, one that could forecast sales or predict stock prices, only to watch it fail in the real world? Well, this is a common frustration. Your model works perfectly on your machine, but the moment you deploy it in a Docker container, it seems to develop amnesia. It forgets everything it knew yesterday, making its predictions for tomorrow useless.
Slimming Down Docker Images: Base Image Choices and The Power of Multi-Stage Builds
Multi-stage Docker builds separate build-time dependencies from runtime requirements, dramatically reducing production image sizes.
Expert Techniques to Trim Your Docker Images and Speed Up Build Times
Use -slim base images, multi-stage builds, smart layer caching, and chained RUN commands to build lean, fast, and production-ready Docker images.
Make Docker Builds Faster with Layer Caching
Dockerfile is an immutable ledger. Look at it this way and optimizing containers becomes intuitive and obvious.
I spent $80 and 14 hours to build this, welcome to my new website!
My refreshed personal blog, built with the help of Claude Code.
Unpacking Docker image with `dive`
Docker images bloat from AI libraries and OS components. This articles suggests using docker history and dive tools to diagnose layer-by-layer bloat sources for targeted optimization.
Deploying Transformers in Production: Simpler Than You Think
A beginner-friendly guide showing developers how to easily deploy transformer models (like DistilBERT) using Docker, Flask, Gunicorn, and AWS SageMaker.
Demystifying Google’s Data Gemma
Unmasking AI’s Illusions: Inside Google’s Data Gemma
Unlocking the Power of Efficient Vector Search in RAG Applications
A Comprehensive Guide to Choosing the Right Vector Index for Efficient Similarity Search