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* working first run * removing core module dependencies * adding CW datasource * alarms MVP * readmes * Adding Screenshot * Adding billing note * adding billing module * Revert "adding billing module" This reverts commit 40d667e37db1036cd71a471ef2fde83ec02aaa13. reverting * adding billing module * Updating Screenshot * resolving feedback * removing unused modules * fmt * Support for tf 1.3.x * removing unused variables * support alarms for multiple workspaces * Updating Readme * docs first draft * indigo nav fix * Simplify docs * RUM White Logo * amp docs * removing billing docs * Change docs structure, reword infrastructure monitoring doc * Pre-commit fixes * drop dead code * Add concepts page * Update contributors * Update java * Update docs * Docs for workloads * Update docs site * typos * pre-commit fixes * Update pre-commit * Update pre-commit Co-authored-by: Rodrigue Koffi <bonclay7@users.noreply.github.com>
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Kevin Lewin
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# Monitor Nginx applications running on Amazon EKS
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The current example deploys the [nginx workload module](https://github.com/aws-observability/terraform-aws-observability-accelerator/tree/main/modules/workloads/nginx),
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to provide an existing EKS cluster with an OpenTelemetry collector,
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curated Grafana dashboards, Prometheus alerting and recording rules with multiple
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configuration options on the cluster infrastructure.
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## Prerequisites
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Make sure to complete the [prerequisites section](/terraform-aws-observability-accelerator/concepts/#prerequisites)
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before proceeding.
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## Setup
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### 1. Download sources and initialize Terraform
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```bash
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git clone https://github.com/aws-observability/terraform-aws-observability-accelerator.git
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cd examples/existing-cluster-nginx
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terraform init
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```
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### 2. AWS Region
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Specify the AWS Region where the resources will be deployed:
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```bash
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export TF_VAR_aws_region=xxx
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```
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### 3. Amazon EKS Cluster
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To run this example, you need to provide your EKS cluster name. If you don't
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have a cluster ready, visit [this example](/terraform-aws-observability-accelerator/helpers/new-eks-cluster.md)
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first to create a new one.
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Specify your cluster name:
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```bash
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export TF_VAR_eks_cluster_id=xxx
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```
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### 4. Amazon Managed Service for Prometheus workspace (optional)
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By default, we create an Amazon Managed Service for Prometheus workspace for you.
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However, if you have an existing workspace you want to reuse, edit and run:
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```bash
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export TF_VAR_managed_prometheus_workspace_id=ws-xxx
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```
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To create a workspace outside of Terraform's state, simply run:
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```bash
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aws amp create-workspace --alias observability-accelerator --query '.workspaceId' --output text
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```
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### 5. Amazon Managed Grafana workspace
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To run this example you need an Amazon Managed Grafana workspace. If you have an existing workspace, edit and run:
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```bash
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export TF_VAR_managed_grafana_workspace_id=g-xxx
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```
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To create a new one, within this example's Terraform state (sharing the same lifecycle with all the other resources):
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- Edit main.tf and set `enable_managed_grafana = true`
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- Run
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```bash
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terraform init
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terraform apply -target "module.eks_observability_accelerator.module.managed_grafana[0].aws_grafana_workspace.this[0]"
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export TF_VAR_managed_grafana_workspace_id=$(terraform output --raw managed_grafana_workspace_id)
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```
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### 6. Grafana API Key
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Amazon Managed Grafana provides a control plane API for generating Grafana API keys.
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As a security best practice, we will provide to Terraform a short lived API key to
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run the `apply` or `destroy` command.
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Ensure you have necessary IAM permissions (`CreateWorkspaceApiKey, DeleteWorkspaceApiKey`)
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```bash
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export TF_VAR_grafana_api_key=`aws grafana create-workspace-api-key --key-name "observability-accelerator-$(date +%s)" --key-role ADMIN --seconds-to-live 1200 --workspace-id $TF_VAR_managed_grafana_workspace_id --query key --output text`
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```
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## Deploy
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Simply run this command to deploy.
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```bash
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terraform apply
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```
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## Visualization
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### 1. Prometheus datasource on Grafana
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Open your Grafana workspace and under Configuration -> Data sources, you will see `aws-observability-accelerator`. Open and click `Save & test`. You will see a notification confirming that the Amazon Managed Service for Prometheus workspace is ready to be used on Grafana.
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### 2. Grafana dashboards
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Go to the Dashboards panel of your Grafana workspace. You will see a list of dashboards under the `Observability Accelerator Dashboards`
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<img width="1208" alt="image" src="https://user-images.githubusercontent.com/97046295/190665211-60faef71-d83d-4d59-ac80-bf4309d8c082.png">
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Open the NGINX dashboard and you will be able to view its visualization
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<img width="1850" alt="image" src="https://user-images.githubusercontent.com/97046295/196226043-e49afeb9-7828-467f-9199-5707cdc69aa9.png">
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### 3. Amazon Managed Service for Prometheus rules and alerts
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Open the Amazon Managed Service for Prometheus console and view the details of your workspace. Under the `Rules management` tab, you will find new rules deployed.
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<img width="1054" alt="image" src="https://user-images.githubusercontent.com/97046295/190665728-ae8bb709-ad93-4629-b845-85c158dd1925.png">
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To setup your alert receiver, with Amazon SNS, follow [this documentation](https://docs.aws.amazon.com/prometheus/latest/userguide/AMP-alertmanager-receiver.html)
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## Deploy an Example Application to Visualize
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In this section we will deploy sample application and extract metrics using AWS OpenTelemetry collector
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### 1. Add the helm incubator repo:
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```sh
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helm repo add ingress-nginx https://kubernetes.github.io/ingress-nginx
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```
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### 2. Enter the following command to create a new namespace:
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```sh
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kubectl create namespace nginx-ingress-sample
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```
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### 3. Enter the following commands to install NGINX:
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```sh
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helm install my-nginx ingress-nginx/ingress-nginx \
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--namespace nginx-ingress-sample \
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--set controller.metrics.enabled=true \
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--set-string controller.metrics.service.annotations."prometheus\.io/port"="10254" \
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--set-string controller.metrics.service.annotations."prometheus\.io/scrape"="true"
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```
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### 4. Set an EXTERNAL-IP variable to the value of the EXTERNAL-IP column in the row of the NGINX ingress controller.
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```sh
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EXTERNAL_IP=your-nginx-controller-external-ip
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```
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### 5. Start some sample NGINX traffic by entering the following command.
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```sh
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SAMPLE_TRAFFIC_NAMESPACE=nginx-sample-traffic
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curl https://raw.githubusercontent.com/aws-samples/amazon-cloudwatch-container-insights/master/k8s-deployment-manifest-templates/deployment-mode/service/cwagent-prometheus/sample_traffic/nginx-traffic/nginx-traffic-sample.yaml |
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sed "s/{{external_ip}}/$EXTERNAL_IP/g" |
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sed "s/{{namespace}}/$SAMPLE_TRAFFIC_NAMESPACE/g" |
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kubectl apply -f -
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```
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### 6. Verify if the application is running
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```sh
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kubectl get pods -n nginx-ingress-sample
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```
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### 7. Visualize the Application's dashboard
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Log back into your Managed Grafana Workspace and navigate to the dashboard side panel, click on `Observability Accelerator Dashboards` Folder and open the `NGINX` Dashboard.
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## Destroy resources
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If you leave this stack running, you will continue to incur charges. To remove all resources
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created by Terraform, [refresh your Grafana API key](#6-grafana-api-key) and run the command below.
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Be careful, this command will removing everything created by Terraform. If you wish
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to keep your Amazon Managed Grafana or Amazon Managed Service for Prometheus workspaces. Remove them
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from your terraform state before running the destroy command.
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```bash
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terraform destroy
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```
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To remove resources from your Terraform state, run
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```bash
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# grafana workspace
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terraform state rm "module.eks_observability_accelerator.module.managed_grafana[0].aws_grafana_workspace.this[0]"
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# prometheus workspace
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terraform state rm "module.eks_observability_accelerator.aws_prometheus_workspace.this[0]"
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```
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