Posts tagged "sagemaker"

Fully Automated MLOps Pipeline – Part 2

THE OBJECTIVE In our previous blog post, we started to explore the training of a forecasting model using ingested data through SageMaker. In this final post, we will complete the presentation...

14.03.2025 0 Read More

MLOps vs. DevOps: Bridging the Gap with SageMaker Pipelines

### Real-World Scenario: Automating Loan Approval ModelsImagine a financial institution deploying a machine learning model to automate loan approvals. Initially, the model performs well, but over time...

23.03.2025 0 Read More

When COBOL Fails: Real-Time Error Management with S3 and JSON

Introduction In any system that processes large volumes of data, failure is inevitable. And when you're running legacy COBOL applications as part of a modern pipeline, error handling becomes ...

03.04.2025 0 Read More

Managing ML Workloads with Amazon SageMaker

In a world where data powers everything, machine learning (ML) has become a game-changer for businesses looking to uncover insights, streamline tasks, and spark new ideas. But let’s be honest—mana...

06.04.2025 0 Read More

Predicting Legacy Failures: Training and Hosting ML Models in SageMaker

Introduction Legacy systems are infamous for failing silently—or catastrophically—with no early warning signs. In our eks_cobol pipeline, COBOL batch jobs handle sensitive data transforma...

07.04.2025 0 Read More

Amazon SageMaker for Data Scientists: Unifying Your Machine Learning Workflow on AWS in 2025

Data scientists juggle numerous tasks: wrangling data, experimenting with algorithms, training models, deploying them, and monitoring performance. Often, this involves switching between disparate tool...

08.04.2025 0 Read More

Getting Started with SageMaker HyperPod: A Practical Guide

Amazon SageMaker HyperPod is revolutionizing how we train large-scale machine learning models, especially when it comes to demanding workloads like Large Language Models (LLMs). In this practical guid...

09.04.2025 0 Read More