AWS Open Source Blog
Category: Learning Levels
Building a multi-tenant Kubeflow environment on Amazon EKS using Amazon Cognito and ADFS
The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable, and scalable. The project’s goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open source systems for ML to diverse infrastructures. Many of our enterprise customers need to integrate Kubeflow with […]
Read MoreIntroducing AWS Cloud Map MCS Controller for K8s
Modern applications built using microservices patterns are distributed and dynamic by nature. Deploying these applications to Kubernetes clusters tightly couples the application and cluster together. Increasingly, customers are asking for the ability to deploy applications across clusters to allow for easier upgrades and migrations and to break down isolation boundaries. However, bridging the gap between […]
Read MorePerforming canary deployments and metrics-driven rollback with Amazon Managed Service for Prometheus and Flagger
This post was written by Kevin Bell and Stefan Prodan. Canary deployments are a popular tool to reduce risk when deploying software, by exposing a new version to a small subset of traffic before rolling it out more broadly. Creating the machinery to do this kind of controlled rollout, and monitoring for possible problems and […]
Read MoreImplementing a hub and spoke dashboard for multi-account data science projects
Modern data science environments often involve many independent projects, each spanning multiple accounts. In order to maintain a global overview of the activities within the projects, a mechanism to collect data from the different accounts into a central one is crucial. In this post, we show how to leverage existing services—Amazon DynamoDB, AWS Lambda, Amazon […]
Read MoreDeploying and scaling Apache Solr on Kubernetes
Apache Solr is an open source enterprise search platform built on Apache Lucene. Solr has been powering large-scale web and enterprise applications across industries such as retail, financial services, healthcare, and more. Its features include full-text search, hit highlighting, faceted search, real-time indexing, dynamic clustering, and rich document handling. Apache Solr’s distributed deployment comes with […]
Read MoreSetting up Amazon Managed Grafana cross-account data source using customer managed IAM roles
Amazon Managed Grafana is a fully managed and secure data visualization service for open source Grafana that enables customers to instantly query, correlate, and visualize operational metrics, logs, and traces for their applications from multiple data sources. Amazon Managed Grafana integrates with multiple Amazon Web Services (AWS) security services, and supports AWS Single Sign-On (AWS […]
Read MoreDeploying 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 […]
Read MoreSecurity 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 […]
Read MoreHow 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 […]
Read MoreHow being open led to greater customer value with the AWS IoT Device SDK for Embedded C
The AWS IoT Device SDK for Embedded C (C-SDK) is composed of a set of MIT-licensed libraries that demonstrate simplified, lightweight, and secure connectivity to AWS IoT Core and device-side operations to AWS IoT services. The AWS IoT C-SDK can work on a variety of operating systems, such as Linux, macOS, and Windows, or a […]
Read More