Tag: Prometheus

This post was co-authored by Cezar Guimarães, Sr. Software Engineer, VTEX Introduction Customers across the globe are increasingly adopting Amazon Elastic Kubernetes Service (Amazon EKS) to run their Windows workloads. This is a result of customers figuring out that refactoring existing Windows-based applications into an open-source environment, while ideal, is a very complex task. It […]

“Sir, your application is continually getting throttled,” I repeated. The highly skilled team that I was brought in to help with an outage was in disbelief. They had been using the same limits configuration in production for over two years. Yet, the Grafana chart was definitive: CPU throttling was causing the outage they were currently […]

It’s every on-call’s nightmare—awakened by a text at 3 a.m. from your alert system that says there’s a problem with the cluster. You need to quickly determine if the issue is with the Amazon EKS managed control plane or the new custom application you just rolled out last week. Even though you installed the default […]

This blog provides a step-by-step guide on how to monitor your containerized workload running on Amazon EKS Anywhere by publishing metrics to Amazon Managed Service for Prometheus and using Amazon Managed Grafana to visualize. Amazon EKS Anywhere is a deployment option for Amazon EKS that enables you to easily create and operate Kubernetes clusters on a customer-managed […]

An earlier blog published last year (Part 1 in the series), Metrics collection from Amazon ECS using Amazon Managed Service for Prometheus, demonstrated how to deploy Prometheus server on an Amazon ECS cluster, dynamically discover the services to collect metrics from, and send metrics to Amazon Managed Service for Prometheus for subsequent query and visualization. […]

You can use CloudWatch Container Insights to monitor, troubleshoot, and alarm on your containerized applications and microservices. Amazon CloudWatch collects, aggregates, and summarizes compute utilization information like CPU, memory, disk, and network data. It also helps you isolate issues and resolve them quickly by providing diagnostic information like container restart failures. Container Insights gives you […]

Introduction Horizontal scalability is a critical aspect of cloud native applications. Microservices deployed to Amazon ECS leverage the Application Auto Scaling service to automatically scale based on observed metrics data. Amazon ECS measures service utilization based on CPU and memory resources consumed by the tasks that belong to a service and publishes CloudWatch metrics, namely, […]

Imaya Kumar Jagannathan, TP Kohli, and Michael Hausenblas In Using Prometheus Metrics in Amazon CloudWatch we showed you how to use the beta version of the Amazon CloudWatch supporting the ingestion of Prometheus metrics. Now that we made this feature generally available we explore its benefits in greater detail and show you how to use […]

Introduction In a Kubernetes cluster, the Horizontal Pod Autoscaler can automatically scale the number of Pods in a Deployment based on observed CPU utilization and memory usage. The autoscaler depends on the Kubernetes metrics server, which collects resource metrics from Kubelets and exposes them in Kubernetes API server through Metrics API. The metrics server has […]

Imaya Kumar Jagannathan, Justin Gu, Marc Chéné, and Michael Hausenblas Update 2020-09-08: The feature described in this post is now in GA, see details in the Amazon CloudWatch now monitors Prometheus metrics from Container environments What’s New item. Earlier this week we announced the public beta support for monitoring Prometheus metrics in CloudWatch Container Insights. […]