Migrating ML Workloads from EC2 to Scalable Amazon EKS
Step-by-step architectural breakdown for migrating standalone EC2 model deployments to fully orchestrated, scalable EKS clusters.
Blog
Articles on data science, machine learning, bioinformatics, and AI.
Scalable Genomic Pipeline Optimization with Nextflow and Singularity
An engineering deep-dive into resolving dependency conflicts and compute scaling bottlenecks in biomedical data workflows using Nextflow and containerization.
Introduction to Graph Attention Networks in Biology
How Graph Attention Networks work, why they matter for biological structure, and how to prototype them with PyTorch Geometric.
Infrastructure as Code for Data Engineers: Terraform Basics
How to use Terraform to provision basic AWS storage and access controls for ML workloads without turning simple infrastructure into manual drift.
Why Docker Fails in HPC and How Singularity Fixes It
How user privileges, filesystem mounts, and scheduler constraints make Docker a poor default in HPC and why Apptainer remains the better execution model.
Introduction to Experiment Tracking without the Overhead
How to get useful experiment tracking with MLflow, cloud object storage, and minimal infrastructure instead of an oversized MLOps stack.
Writing Your First Production-Ready Nextflow Pipeline
How to structure channels, processes, and configuration so your first Nextflow pipeline is production-ready instead of tutorial-only.
Local to Multi-Node: Packaging ML Code with Docker
How to build lean Docker images for ML workloads without carrying notebook-era assumptions into production clusters.
Processing Single-Cell RNA-Seq Data at Scale
How to design a cluster-friendly scRNA-seq workflow for QC, normalization, dimensionality reduction, and clustering without exhausting memory.
Setting Up a Clean CI/CD Pipeline for Python ML Packages
How to structure testing, packaging, and trusted publishing for Python ML libraries without turning your release workflow into a bottleneck.