Articles tagged with "level-200"

Struggling with URL redirections for your AWS-hosted website? If you’re using an S3 bucket as your origin, you might have noticed that S3 alone doesn’t support dynamic redirects via server-side rules. That’s where AWS CloudFront Functions come in—offering a fast, simple, and cost-effective way to manage redirections. In this guide, we’ll show you how CloudFront can handle your URL redirections without requiring separate S3 buckets or CloudFront distributions, streamlining your architecture and improving your website’s SEO and user experience.

When discussing AWS pricing with customers, limitations in the official AWS Pricing Calculator can sometimes hinder accurate cost estimations. This blog post addresses a specific challenge encountered with AWS CloudWatch Synthetics pricing and provides a solution by building a custom calculator using the AWS Pricing API.

Switching the Identity Provider in the IAM Identity Center while keeping all permissions intact and minimizing disruptions can be a daunting task. In this post I’m explaining how we solved this for one of our customers.

AWS DataSync is a service that simplifies and accelerates data migrations not only to but also from and between AWS storage services. In this blog post we will see how to leverage it to migrate data from an EFS file system to an Amazon S3 bucket.

IAM Identity Center, formerly AWS SSO, is often used as an access management solution in front of one or more AWS accounts. More often than not, its purpose is to grant access to AWS accounts within an AWS organization. Today we’ll shed some light on the basic concepts and explain how this solution can be integrated with Azure AD which has recently been renamed to Entra ID to provide Single-Sign-On to your AWS environment.

Finding the right set of hyperparameters when training machine learning models is a resource-consuming and costly task. In this post, we try to simplify this by exploring hyperparameter tuning for reinforcement learning models with Ray 2.x on AWS Sagemaker.

The RAG - Retrieval Augmented Generation is an approach to reduce hallucination using LLMs (Large Language Models). With RAG you need a storage solution, which is a vector-store in most cases. When you have the task to build the infrastructure for such a use case, you have to decide which database to use. Sometimes, the best solution is not the biggest one. Then you should go serverless to a smaller solution, which fits the use-case better. In this post, I introduce some of the solutions and aid you in deciding which one to choose.

A few years ago Amazon SageMaker introduced direct support for reinforcement learning (RL) through integration of RL-frameworks, including Ray. However, support has not been kept up to date and the supported versions are no longer what you might call current.