terraform-aws-observability-accelerator/docs/workloads/nginx.md

Monitor Nginx applications running on Amazon EKS

The current example deploys the nginx workload module, to provide an existing EKS cluster with an OpenTelemetry collector, curated Grafana dashboards, Prometheus alerting and recording rules with multiple configuration options on the cluster infrastructure.

Prerequisites

!!! note Make sure to complete the prerequisites section before proceeding.

Setup

1. Download sources and initialize Terraform

git clone https://github.com/aws-observability/terraform-aws-observability-accelerator.git
cd examples/existing-cluster-nginx
terraform init

2. AWS Region

Specify the AWS Region where the resources will be deployed:

export TF_VAR_aws_region=xxx

3. Amazon EKS Cluster

To run this example, you need to provide your EKS cluster name. If you don't have a cluster ready, visit this example first to create a new one.

Specify your cluster name:

export TF_VAR_eks_cluster_id=xxx

4. Amazon Managed Service for Prometheus workspace (optional)

By default, we create an Amazon Managed Service for Prometheus workspace for you. However, if you have an existing workspace you want to reuse, edit and run:

export TF_VAR_managed_prometheus_workspace_id=ws-xxx

To create a workspace outside of Terraform's state, simply run:

aws amp create-workspace --alias observability-accelerator --query '.workspaceId' --output text

5. Amazon Managed Grafana workspace

To run this example you need an Amazon Managed Grafana workspace. If you have an existing workspace, edit and run:

export TF_VAR_managed_grafana_workspace_id=g-xxx

To create a new one, within this example's Terraform state (sharing the same lifecycle with all the other resources):

• Edit main.tf and set enable_managed_grafana = true
• Run

terraform init
terraform apply -target "module.eks_observability_accelerator.module.managed_grafana[0].aws_grafana_workspace.this[0]"
export TF_VAR_managed_grafana_workspace_id=$(terraform output --raw managed_grafana_workspace_id)

6. Grafana API Key

Amazon Managed Grafana provides a control plane API for generating Grafana API keys. As a security best practice, we will provide to Terraform a short lived API key to run the apply or destroy command.

Ensure you have necessary IAM permissions (CreateWorkspaceApiKey, DeleteWorkspaceApiKey)

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`

Deploy

Simply run this command to deploy.

terraform apply

Visualization

1. Prometheus datasource on Grafana

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.

2. Grafana dashboards

Go to the Dashboards panel of your Grafana workspace. You will see a list of dashboards under the Observability Accelerator Dashboards

Open the NGINX dashboard and you will be able to view its visualization

3. Amazon Managed Service for Prometheus rules and alerts

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.

!!! note To setup your alert receiver, with Amazon SNS, follow this documentation

Deploy an Example Application to Visualize

In this section we will deploy sample application and extract metrics using AWS OpenTelemetry collector

1. Add the helm incubator repo:

helm repo add ingress-nginx https://kubernetes.github.io/ingress-nginx

2. Enter the following command to create a new namespace:

kubectl create namespace nginx-ingress-sample

3. Enter the following commands to install NGINX:

helm install my-nginx ingress-nginx/ingress-nginx \
--namespace nginx-ingress-sample \
--set controller.metrics.enabled=true \
--set-string controller.metrics.service.annotations."prometheus\.io/port"="10254" \
--set-string controller.metrics.service.annotations."prometheus\.io/scrape"="true"

4. Set an EXTERNAL-IP variable to the value of the EXTERNAL-IP column in the row of the NGINX ingress controller.

EXTERNAL_IP=your-nginx-controller-external-ip

5. Start some sample NGINX traffic by entering the following command.

SAMPLE_TRAFFIC_NAMESPACE=nginx-sample-traffic
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 |
sed "s/{{external_ip}}/$EXTERNAL_IP/g" |
sed "s/{{namespace}}/$SAMPLE_TRAFFIC_NAMESPACE/g" |
kubectl apply -f -

6. Verify if the application is running

kubectl get pods -n nginx-ingress-sample

7. Visualize the Application's dashboard

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.

Destroy resources

If you leave this stack running, you will continue to incur charges. To remove all resources created by Terraform, refresh your Grafana API key and run the command below.

!!! warning Be careful, this command will removing everything created by Terraform. If you wish to keep your Amazon Managed Grafana or Amazon Managed Service for Prometheus workspaces. Remove them from your terraform state before running the destroy command.

terraform destroy

To remove resources from your Terraform state, run

# grafana workspace
terraform state rm "module.eks_observability_accelerator.module.managed_grafana[0].aws_grafana_workspace.this[0]"

# prometheus workspace
terraform state rm "module.eks_observability_accelerator.aws_prometheus_workspace.this[0]"