Containers

Tag: Containers

Amazon EKS now supports Kubernetes version 1.29

Introduction The Amazon Elastic Kubernetes Service (Amazon EKS) team is pleased to announce support for Kubernetes version 1.29 in Amazon EKS, Amazon EKS Distro, and Amazon EKS Anywhere (v0.19.0). The theme for this version was chosen for the beautiful art form that is Mandala—a symbol of the universe in its perfection. Hence, the fitting release […]

A deep dive into resilience and availability on Amazon Elastic Container Service

Introduction In this post, we’ll deep dive into the architecture principles we use in Amazon Elastic Container Service (Amazon ECS). We’ll outline some of the features that Amazon ECS delivers to make it easy for your application to achieve high availability and resilience. We explore how Amazon ECS is designed to use AWS availability and […]

Explore etcd Defragmentation in Amazon EKS

Introduction Amazon Elastic Kubernetes Service (Amazon EKS) has gained significant popularity as a managed Kubernetes service, providing a scalable and reliable platform for running containerized applications. Behind the scenes, Amazon EKS uses etcd, a distributed key-value store, to store cluster configuration, state, and metadata. In this post, we delve into the defragmentation functionality in etcd and discuss the […]

GPU sharing on Amazon EKS with NVIDIA time-slicing and accelerated EC2 instances

In today’s fast-paced technological landscape, the demand for accelerated computing is skyrocketing, particularly in areas like artificial intelligence (AI) and machine learning (ML). One of the primary challenges the enterprises face is the efficient utilization of computational resources, particularly when it comes to GPU acceleration, which is crucial for ML tasks and general AI workloads. […]

Improving operational visibility with AWS Fargate task retirement notifications

Introduction AWS Fargate, the serverless compute engine for containerized workloads, removes the undifferentiated heavy lifting of securing and patching the underlying infrastructure. In this blog post we dive into AWS Fargate task retirement, one of the ways AWS keeps the infrastructure secure and up to date. AWS has recently updated the AWS Fargate task retirement […]

Using SBOM to find vulnerable container images running on Amazon EKS clusters

Introduction When you purchase a packaged food item in your local grocery store, you probably check the list of ingredients written to understand what’s inside and make sure you aren’t consuming ingredients inadvertently that you don’t want to or are known to have adverse health effects. Do you think in a similar way when you […]

Implementing application load balancing of Amazon ECS Anywhere workloads using Traefik Proxy

Introduction With Amazon ECS Anywhere, you can run and manage containers on any customer-managed infrastructure using the same cloud-based, fully managed, and highly scalable container orchestration service you use in AWS today. Amazon ECS Anywhere provides support for registering an external instance, such as an on-premises server or virtual machine (VM), to your Amazon ECS […]

Happy 5th Birthday Amazon EKS!

Today we’re thrilled to celebrate the 5th anniversary of Amazon Elastic Kubernetes Service (Amazon EKS), and it’s an opportune moment to reflect on our journey so far. Since its launch in 2018, Amazon EKS has served tens of thousands of customers worldwide in running resilient, secure, and scalable container-based applications. Amazon EKS, using upstream Kubernetes, […]

AWS Lambda for the containers developer

Introduction When building an application on AWS, one of the common decision points customers encounter is building on AWS Lambda versus building on a containers product like Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). To make this decision, there are many factors to consider such as cost, scaling properties, […]

Start Pods faster by prefetching images

Introduction Many AWS customers use Amazon Elastic Kubernetes Service (Amazon EKS) to run machine learning workloads. Containerization allows machine learning engineers to package and distribute models easily, while Kubernetes helps in deploying, scaling, and improving. When working with customers that run machine learning training jobs in Kubernetes, we ‘ve seen that as the data set […]