AWS EKS Microservice Application

Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Roadmap
5. Contact
6. Acknowledgments

About The Project

Project details

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Built With

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• TODO: Add Grafana, Prometheus, Loki, Tempo, Mimir, and other

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Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.

Prerequisites

This is an example of how to list things you need to use the software and how to install them.

• AWS Account - Sign up
  • Create User
  • Configure Credentials
• AWS CLI - Install steps
• Terraform - Install steps
• Python - Install steps
  • Macs can use brew install python
• Docker - Install steps
• Kind - Install steps

Getting Started

Locally

1. Clone the repo

   git clone https://github.com/cxmiller21/aws-eks-microservices.git

2. Create the Kind Kubernetes cluster

   # Creates a local Kubernetes cluster using Docker containers
   # Creates the Grafa LGTM (Loki, Grafana, Tempo, and Mimir/Prometheus - aka "Looks Good to Me") Stack
   ./scripts/create-kind-cluster.sh

3. Access ArgoCD and Grafana

   # Enable port-forwarding to ArgoCD
   kubectl port-forward service/argo-cd-argocd-server -n argocd 8080:80
   # Get the ArgoCD password
   kubectl -n argocd get secret argocd-initial-admin-secret -o jsonpath="{.data.password}" | base64 -d
   # Visit `localhost:8080` and login with the username `admin` and the password from the command above
   
   # View Grafana at
   kubectl port-forward service/grafana 3000:80 -n monitoring

4. Create Online Boutique microservices application in the Kind cluster

   # View Grafana at 127.0.0.1:3000 (username: admin, password: prom-operator)
   # Start online-boutique application
   kubectl apply -f ./kubernetes/local/online-boutique.yaml
   # Expose the application via a NodePort
   kubectl port-forward service/frontend-service 8080:8080 -n online-boutique

5. Cleanup

   kind get clusters # List clusters (should be names demo-cluster)
   kind delete cluster --name demo-cluster

Deploy to AWS EKS

1. Clone the repo

   git clone https://github.com/cxmiller21/aws-eks-microservices.git

2. (optional) Create a new AWS CLI profile

   # Create a new AWS User or Access Keys for the project
   aws configure --profile aws-eks-demo
   # Enter AWS Access Key ID, AWS Secret Access Key, Default region (us-east-1) name, and Default output format (press enter for default)

3. Create Terraform AWS Resources (~20 minutes)

   cd ./terraform
   terraform init
   # TODO: create .terraform.tfvars file and add federated_role_name = "xyz"
   terraform plan # Confirm resources
   terraform apply # Enter `yes` when prompted

4. Allow local connections to EKS cluster (if not done already)

   # Add the EKS Cluster to the ~/.kube/conf file to execute local kubectl commands
   aws eks --region us-east-1 update-kubeconfig --name aws-eks-demo

5. Get the ArgoCD password

   # Visit the AWS ALB URL for ArgoCD and login with the username `admin` and the password from the command below
   kubectl -n argocd get secret argocd-initial-admin-secret -o jsonpath="{.data.password}" | base64 -d

6. Create the Online Boutique microservices application in the EKS Cluster (run from project root) (TBD Have ArgoCD Application auto-create this)

./scripts/install-online-boutique.sh

7. View the "Online Boutique" from the ALB URL output in the previous step and start shopping!

Congrats! The project is now up and running!

AWS EKS Cleanup

1. Delete the Online Boutique application

   ./scripts/delete-online-boutique.sh

2. Run the cleanup-eks.py script (TBD)

   # Having trouble deleting EKS Ingress/ALB resources via Terraform, so this script will delete the resources to
   successfully run Terraform destroy
   ./scripts/cleanup-eks.py

Grafana Dashboards

Data Sources

1. Add the Loki data source
   1. Name: Loki
   2. Type: Loki
   3. URL: http://loki-distributed-gateway.monitoring.svc.cluster.local:80
   4. Access: Server
   5. Save & Test
2. Add the Tempo data source
   1. Name: Tempo
   2. Type: Tempo
   3. URL: http://tempo-query-frontend.monitoring.svc.cluster.local:3100
   4. Access: Server
   5. Trace to Logs
      1. datasource: Loki
      2. spanEndTimeShift: 5m
      3. Tags: http.status as http_status, component as ""
      4. Custom query: {${__tags}}|="${__trace.traceId}"
   6. Service graph: Prometheus data source
   7. Save & Test
3. Add the Mimir data source
   1. Name: Mimir
   2. Type: Prometheus
   3. URL: http://mimir-nginx.monitoring.svc:80/prometheus
   4. Access: Server
   5. Save & Test

Dashboards

1. View the Grafana dashboard via the AWS Load Balancer DNS address
2. Add new dashboards to view Loki logs and Tempo traces (Dashboards --> New --> Import)
   1. Loki stack monitoring (Promtail, Loki) Dashboard ID: 14055
   2. Loki Logs/App Dashboard ID: 13639

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Usage

Examples TBD

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Roadmap

• Validate EKS cluster logging and monitoring
• Create AWS EKS cluster with Terraform and validate logging, monitoring, and tracing
• Create AWS EKS cluster diagram that shows key Cluster components (Auth, ALBs, Logging, Monitoring, and Tracing)
• Create diagram that shows the Online Boutique microservices application components

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