Category: Management Tools

Introduction We have observed a growing adoption of container services among both startups and established companies. This trend is driven by the ease of deploying applications and migrating from on-premises environments to the cloud. One platform of choice for many of our customers is Amazon Elastic Container Service (Amazon ECS). The powerful simplicity of Amazon […]

Introduction In part 1 and part 2 of this series, the importance of measuring time accuracy and relevant concepts were discussed. Additionally, we covered specifics on ways to put those concepts into practice, track metrics using Amazon CloudWatch and implement a practical solution for Amazon Elastic Compute Cloud (Amazon EC2) instances. In this part 3, […]

Introduction The majority of the enterprise customers tend to establish centralize control and well-architected organization-wide policies when it comes to distribution of cloud resources in multiple teams. These teams are primarily divided into three categories: IT operations, Enterprise Security, and Application (App)-development. While delivery of business value from application standpoint falls under the purview of […]

Introduction For improved observability and troubleshooting, it is recommended to ship container logs from the compute platform to a container running on to a centralized logging server. In the real world, the logging server may occasionally be unreachable or unable to accept logs. There is an architectural tradeoff when designing for log server failures. Service […]

Introduction Amazon CloudWatch Container Insights allows you to collect, aggregate, and analyze metrics, logs, and traces for your container-based applications and infrastructure on AWS. Container Insights captures metrics for various resources, such as CPU, memory, disk, and network, along with diagnostic data like container restart failures, which enables you to efficiently isolate and resolve problems. […]

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 […]

Introduction Application Auto Scaling is a web service for developers and system administrators who need a solution for automatically scaling their scalable resources for AWS services such as Amazon Elastic Container Service (Amazon ECS) services, Amazon DynamoDB tables, AWS Lambda Provisioned Concurrency, and more. Application Auto Scaling now offers support for scaling such resources using […]

This blog was co-authored by Aurelijus Banelis, Senior Software Engineer at home24 Introduction Home24 is a leading pure-play home & living e-commerce platform in continental Europe and Brazil. It has third-party and private-label assortments combined with a tailored user experience — and that is a good foundation for a sustainable technology business. Aurelijus is proud […]

To meet user demand, dynamic HTTP-based applications require constant scaling of Kubernetes pods. For applications exposed through Kubernetes ingress objects, the AWS Application Load Balancer (ALB) distributes incoming traffic automatically across the newly scaled replicas. When Kubernetes applications scale down due to a decline in demand, certain situations will result in brief interruptions for end […]

Note: Since this post was published, Amazon ECS added built-in detection and repair of impaired agent connectivity, which is now the recommended approach. For more information, see Monitor Amazon ECS container instance health. Introduction Amazon Elastic Container Service (Amazon ECS) is a fully managed container orchestration service that allows organizations to deploy, manage, and scale […]