Helm install stable/nginx-ingress -generate-name -version 1.33.5 \ Next, we install the NGINX Ingress controller in the dedicated Kubernetes namespace nginx-ingress-sample, using Helm: kubectl create namespace nginx-ingress-sample Expect the provisioning to take something like 15 min end to end. ![]() Under the hood, eksctl uses CloudFormation, so you can have a look in the console there on the progress. You can then provision the EKS cluster with the following command: eksctl create cluster -f clusterconfig.yaml If you want to follow along, you will need eksctl installed to provision the EKS cluster as well as Helm 3 for the application installation.įor the EKS cluster we’re using the following cluster configuration (save as clusterconfig.yaml and note that you potentially want to change the region to something geographically closer): apiVersion: eksctl.io/v1alpha5 We have three namespaces in the EKS cluster: amazon-cloudwatch which hosts the CW Prometheus agent, nginx-ingress-sample where we have the NGINX Ingress controller running, and nginx-sample-traffic which hosts our sample app, incl. We use NGINX as an Ingress Controller as the scrape target and a dedicated app generating traffic for it. In this first example we’re using an EKS cluster as the runtime environment and deploy the CW Prometheus agent for ingesting them as EMF events into CloudWatch. With that said, let us now move on to the practical part where we will show you how to use the CloudWatch Container Insights Prometheus metrics in two setups: we start with a simple example of scraping NGINX and then have a look at how to use custom metrics by instrumenting a ASP.NET Core app. You can also analyze the high-fidelity Prometheus metrics using CloudWatch Logs Insights query language to isolate specific pods and labels impacting the health and performance of your containerized environments. Publishing aggregated Prometheus metrics as CloudWatch custom metrics statistics reduces the number of metrics needed to monitor, alarm, and troubleshoot performance problems and failures. Each event creates metric data points as CloudWatch custom metrics for a curated set of metric dimensions that is fully configurable. The agent now supports Prometheus configuration, discovery, and metric pull features, enriching and publishing all high fidelity Prometheus metrics and metadata as Embedded Metric Format (EMF) to CloudWatch Logs. How does it work? You need to run the CloudWatch agent in your Kubernetes cluster. ![]() We’re aiming at supporting any Prometheus exporters compatible with OpenMetrics, allowing you to scrape any containerized workload using one of the 150+ open source third party exporters. By default, preselected services are scraped and pre-aggregated every 60 seconds and automatically enriched with metadata such as cluster and pod names. It automatically collects, filters, and creates aggregated custom CloudWatch metrics visualized in dashboards for workloads such as AWS App Mesh, NGINX, Java/JMX, Memcached, and HAProxy. Amazon CloudWatch Container Insights automates the discovery and collection of Prometheus metrics from containerized applications. Prometheus is a popular open source monitoring tool that graduated as a Cloud Native Compute Foundation (CNCF) project, with a large and active community of practitioners. With this post we want to show you how you can use this new Amazon CloudWatch feature for containerized workloads in Amazon Elastic Kubernetes Service (EKS) and Kubernetes on AWS cluster provisioned by yourself. Update : 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.Įarlier this week we announced the public beta support for monitoring Prometheus metrics in CloudWatch Container Insights. ![]() Imaya Kumar Jagannathan, Justin Gu, Marc Chéné, and Michael Hausenblas
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |