<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Aws on Victoria Dyster, PhD</title><link>http://victoriadyster.com/tags/aws/</link><description>Recent content in Aws on Victoria Dyster, PhD</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>© 2026 Victoria Dyster, PhD</copyright><lastBuildDate>Mon, 01 Sep 2025 00:00:00 +0000</lastBuildDate><atom:link href="http://victoriadyster.com/tags/aws/index.xml" rel="self" type="application/rss+xml"/><item><title>Building a Private MLOps Platform on AWS</title><link>http://victoriadyster.com/projects/private-mlops-platform-aws/</link><pubDate>Mon, 01 Sep 2025 00:00:00 +0000</pubDate><guid>http://victoriadyster.com/projects/private-mlops-platform-aws/</guid><description>How I deployed MLflow as a authenticated experiment tracking server on AWS and integrated it into a reusable ML toolkit.</description></item><item><title>CI/CD for a Genomic Data Pipeline: Testing, Security, and Multi-Environment Deployment</title><link>http://victoriadyster.com/projects/ci-cd-genomic-data-pipeline/</link><pubDate>Mon, 23 Jun 2025 00:00:00 +0000</pubDate><guid>http://victoriadyster.com/projects/ci-cd-genomic-data-pipeline/</guid><description>How I built a CI/CD system for a Nextflow methylation sequencing pipeline: from pre-commit linting through four layers of testing to automated promotion across development, staging, and production, all backed by reusable GitHub Actions and container image promotion via ECR.</description></item><item><title>Scaling ML Training for Epigenetic Age Prediction</title><link>http://victoriadyster.com/projects/epigenetic-age-prediction/</link><pubDate>Fri, 15 Nov 2024 00:00:00 +0000</pubDate><guid>http://victoriadyster.com/projects/epigenetic-age-prediction/</guid><description>How parallelising hyperparameter tuning on SageMaker turned a single-instance grid search into a 100x faster training workflow.</description></item><item><title>Building a Self-Service Analysis Environment for Data Scientists</title><link>http://victoriadyster.com/projects/self-service-ec2-platform/</link><pubDate>Fri, 15 Mar 2024 00:00:00 +0000</pubDate><guid>http://victoriadyster.com/projects/self-service-ec2-platform/</guid><description>Designing and building a Python CLI that lets data scientists create, manage, and safely shut down cloud research environments without needing to know Terraform or the AWS console.</description></item></channel></rss>