Containers
Category: Amazon Elastic Container Registry
Announcing AWS App Runner support for Bitbucket
Introduction AWS App Runner is a fully managed container application service that lets you build, deploy, and run containerized web applications and API services without prior infrastructure or container experience. Starting today, AWS App Runner supports building and deploying services from Bitbucket repositories. This post walks you through the process of deploying a sample AWS […]
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 […]
Shift left to secure your container supply chain
Introduction When we talk about securing container solutions, most of the focus is on securing the orchestrator or the infrastructure that the orchestrator runs on. However, at the heart of your container solutions are the containers themselves. In this post, we show you how we ensured that before we even push a container into our […]
Building better container images
Introduction Many applications built today or modernized from monoliths are done so using microservice architectures. The microservice architecture makes applications easier to scale and faster to develop, which enables innovation and accelerating time-to-market for new features. In addition, microservices also provide lifecycle autonomy enabling applications to have independent build and deploy processes, which provides technological […]
Under the hood: Lazy Loading Container Images with Seekable OCI and AWS Fargate
AWS Fargate, a serverless compute engine for containerized workloads, now supports lazy loading container images that have been indexed using Seekable OCI (SOCI). Lazy loading container images with SOCI reduces the time taken to launch Amazon Elastic Container Service (Amazon ECS) Tasks on AWS Fargate. Donnie Prakoso’s launch post provides details on how to get […]
Scaling IaC and CI/CD pipelines with Terraform, GitHub Actions, and AWS Proton
Introduction Modern applications run on a variety of compute platforms in AWS including serverless services such as AWS Lambda, AWS App Runner, and AWS Fargate. Organizations today are often required to support architectures using a variety of these AWS services, each offering unique runtime characteristics, such as concurrency and scaling, which can be purpose fit […]
How Quora modernized MLOps on Amazon EKS to improve customer experience with scalable ML applications
This blog post was co-written by Lida Li of Quora Introduction Quora is a leading Q&A platform with a mission to share and grow the world’s knowledge, serving hundreds of millions of users worldwide every month. Quora uses machine learning (ML) to generate a custom feed of questions, answers, and content recommendations based on each […]
Announcing Container Image Signing with AWS Signer and Amazon EKS
Introduction Today we are excited to announce the launch of AWS Signer Container Image Signing, a new capability that gives customers native AWS support for signing and verifying container images stored in container registries like Amazon Elastic Container Registry (Amazon ECR). AWS Signer is a fully managed code signing service to ensure trust and integrity […]
Announcing pull through cache for registry.k8s.io in Amazon Elastic Container Registry
Introduction Container images are stored in registries and pulled into environments where they run. There are many different types of registries from private, self-run registries to public, unauthenticated registries. The registry you use is a direct dependency that can have an impact on how fast you can scale, the security of the software you run, […]
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 […]