AWS Open Source Blog

Category: Technical How-to

Deploying OpenMRS Electronic Health Record (EHR) system on AWS

Digitization in the healthcare industry, led by electronic health record (EHR) system adoption, has positively impacted the workflow of healthcare professionals (HCP) and patient care. Now EHR systems are a critical tool in healthcare delivery. The design and functionality of a good EHR system closely follows the overall healthcare system design. In his book The […]

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Simplifying Kubernetes configurations using AWS Lambda

In this blog post, we explain how to create a multi-stage Dockerfile that uses eksctl, kubectl, and aws-auth. This will allow you to call Kubernetes APIs to create and manage resources through a unified control plane. You will interact with the Kubernetes API using Python, and the config map is created using a Jinja2 template. […]

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Overview of workflow described in article

Getting started with Feast, an open source feature store running on AWS Managed Services

This post was written by Willem Pienaar, Principal Engineer at Tecton and creator of Feast. Feast is an open source feature store and a fast, convenient way to serve machine learning (ML) features for training and online inference. Feast lets you build point-in-time correct training datasets from feature data, allows you to deploy a production-grade […]

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Automating a DAG deployment with Amazon Managed Workflows for Apache Airflow

Many developers and data engineers use Managed Workflows for Apache Airflow (Amazon MWAA), a managed service for open source Apache Airflow, to programmatically author, schedule, and monitor workflows. With Amazon MWAA, you can focus on business logic and build workflows without worrying about the management responsibilities such as setup, patching, upgrades, security, scaling, and so […]

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Security features of Bottlerocket, an open source Linux-based operating system

Bottlerocket is an open source Linux-based operating system from Amazon that was purpose built for running containers with a strong emphasis on security. The result is an operating system that comes with a variety of built-in controls for creating a secure environment for running containerized workloads. In this post, we’ll explore several of the security […]

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Adding StatefulSet support in the OpenTelemetry Operator

In this post, AWS interns, software engineers Huy Vo and Iris Song, share their experience with adding StatefulSet support in the OpenTelemetry Operator and their design approach to building a scrape target update service into the OpenTelemetry Collector’s Prometheus receiver. OpenTelemetry (OTEL) is a popular open source framework used for observability. It provides a set […]

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Solving the Traveling Salesperson Problem with deep reinforcement learning on Amazon SageMaker

The Traveling Salesperson Problem (TSP) is one of the most popular NP-hard combinatorial problems in the theoretical computer science and operations research (OR) community. It asks the following question: “Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and […]

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Building a series deletion API in Cortex

In this post, Ilan Gofman, an intern on the Amazon Managed Service for Prometheus team, shares his experience of designing and implementing the series deletion feature inside of the Cortex open source project. This new API will provide the ability to delete series from Cortex using the blocks storage engine. This blog post details the […]

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AWS Lambda metrics support for Amazon Managed Service for Prometheus now available in AWS Distro for OpenTelemetry

In this blog post, intern engineers Karen Xu and Kelvin Lo describe how they added metric support to the OpenTelemetry and AWS Distro for OpenTelemetry Lambda layers, and built and tested the metric pipeline to generate, collect, and export application metrics from AWS Lambda to Amazon Managed Service for Prometheus (AMP). The demand for observability […]

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How to use InfluxDB and Grafana to visualize ML output with AWS IoT Greengrass

Machine learning (ML) algorithms are widely used for computer vision (CV) applications, such as image classification, object detection, and semantic segmentation. With the latest development of the Industrial Internet of Things (IIoT), ML algorithms can be directly implemented at the edge device to process image data and perform anomaly detection, such as for product quality […]

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