NOTE : IF USE Terraform for create infra

                                Canary Deployment Custom  ,  Prometheus  ,HPA  TERRAFORM

NOTE : IF USE Terraform for create infra

CTEATE S3 Bucket and DynomoDB (Configration gives in last this file )

Create Cluster

eksctl create cluster --profile ram --name my-eks-cluster --region us-west-2 --version 1.29 --nodegroup-name standard-workers --node-type t2.medium --nodes 1 --nodes-min 1 --nodes-max 3 --node-volume-size 20 --managed --with-oidc

canary-deployment

✅ Step 1: Enable IAM OIDC Provider for your EKS cluster

export AWS_PROFILE=ram # aws profile name

eksctl utils associate-iam-oidc-provider
--cluster CLUSTER_NAME
--region us-west-2
--approve

✅ Step 2: Create IAM Policy for ALB Controller

curl -o iam-policy.json https://raw.githubusercontent.com/kubernetes-sigs/aws-load-balancer-controller/main/docs/install/iam_policy.json

aws iam create-policy
--policy-name AWSLoadBalancerControllerIAMPolicy
--region us-west-2
--policy-document file://iam-policy.json

✅ Step 3: Create IAM Role for ServiceAccount (IRSA)

find account id : 
aws_account_id=$(aws sts get-caller-identity --query Account --output text)

eksctl create iamserviceaccount \
   --cluster $CLUSTER_NAME \
   --namespace kube-system \
   --region $REGION \
   --name aws-load-balancer-controller \
   --attach-policy-arn arn:aws:iam::${aws_account_id}:policy/AWSLoadBalancerControllerIAMPolicy \
   --approve

OR

eksctl create iamserviceaccount \
      --cluster $CLUSTER_NAME \
      --namespace kube-system \
      --region us-west-2 \
      --name aws-load-balancer-controller \
      --attach-policy-arn arn:aws:iam::<ACCOUNT_ID>:policy/AWSLoadBalancerControllerIAMPolicy \
      --approve

✅ cert-manager Install with kubectl (v1.14.4)

kubectl apply -f https://github.com/cert-manager/cert-manager/releases/download/v1.14.4/cert-manager.yaml

✅ Step 4: Install AWS Load Balancer Controller using Helm

Add Helm repo & update:

   helm repo add eks https://aws.github.io/eks-charts
   helm repo update

🔹 Install the controller:

helm install aws-load-balancer-controller eks/aws-load-balancer-controller \
-n kube-system \
--set clusterName=<your-cluster-name> \
--set serviceAccount.create=false \
--set region=<your-region> \
--set vpcId=<your-vpc-id> \
--set serviceAccount.name=aws-load-balancer-controller

Note : vpc-id cmd: aws eks describe-cluster --region us-west-2 --name my-eks-cluster --query "cluster.resourcesV pcConfig.vpcId" --output text

OP Upgrade the controller:

 helm upgrade -i aws-load-balancer-controller eks/aws-load-balancer-controller \
     -n kube-system \
     --set clusterName=$CLUSTER_NAME \
     --set serviceAccount.create=false \
     --set serviceAccount.name=aws-load-balancer-controller \
     --set region=$REGION \
     --set vpcId=<VPC_ID> \
    --set image.tag="v2.7.1"

✅ Step 5: Validate Controller is Running

kubectl get deployment -n kube-system aws-load-balancer-controller kubectl describe ingress

Delete Ingress

kubectl delete ingress -n

Alternate (Hard Force)

kubectl delete ingress -n --grace-period=0 --force

Restart controller

kubectl -n kube-system rollout restart deployment aws-load-balancer-controller

projects :

project-root/ ├── Jenkinsfile |- ---- monitoring / |-- prometheus-configmap.yaml |---- prometheus-deployment -services.yaml ├── manifests/ │ ├── deployment-app-v1.yaml │ ├── deployment-app-v2.yaml │ ├── service-app-v1.yaml │ ├── service-app-v2.yaml │ └── ingress-canary.yaml ├── scripts/ │ ├── monitor_metrics.sh │ └── update_ingress_weight.sh └── README.md

✅ Option 1: Helm के ज़रिए Prometheus Setup (Recommended for Production)

helm repo add prometheus-community https://prometheus-community.github.io/helm-charts helm repo update helm install prometheus prometheus-community/kube-prometheus-stack
--namespace monitoring
--set prometheus.prometheusSpec.podMonitorSelectorNilUsesHelmValues=false

✅ Step-by-Step: Install Prometheus in monitoring and Scrape Django Pod

🔹 Step 1: Add Prometheus Helm Repo

helm repo add prometheus-community https://prometheus-community.github.io/helm-charts helm repo update

🔹 Step 2: Create monitoring Namespace

kubectl create namespace monitoring

🔹 Step 3: Install Prometheus Stack in monitoring

bash helm install prometheus prometheus-community/kube-prometheus-stack
--namespace monitoring
--set prometheus.prometheusSpec.podMonitorSelectorNilUsesHelmValues=false

Note This tells Prometheus to scrape all PodMonitors in the same namespace (monitoring), without needing label selectors.

🔹 Step 4: Deploy Django App in monitoring Namespace

Example Deployment.yaml:

yaml apiVersion: apps/v1 kind: Deployment metadata: name: django-app namespace: monitoring labels: app: django-app spec: replicas: 1 selector: matchLabels: app: django-app template: metadata: labels: app: django-app spec: containers: - name: django image: : shailesh49/myappv2 ports: - containerPort: 8000

Example Service.yaml:

yaml apiVersion: v1 kind: Service metadata: name: django-service namespace: monitoring labels: app: django-app spec: selector: app: django-app type: NodePort ports: - name: http port: 8000 targetPort: 8000 nodePort: 30000

🔹 Step 5: Create PodMonitor.yaml

yaml apiVersion: monitoring.coreos.com/v1 kind: PodMonitor metadata: name: django-podmonitor namespace: monitoring labels: release: prometheus spec: selector: matchLabels: app: django-app podMetricsEndpoints: - path: /metrics port: http interval: 30s namespaceSelector: matchNames: - monitoring

Ensure port: http matches the port name in your Service.

🔹 Step 6: Verify Targets in Prometheus UI

Port forward Prometheus:

bash kubectl port-forward svc/prometheus-kube-prometheus-prometheus 9090 -n monitoring

Visit:

http://localhost:9090/targets

✅ You should see:

/metrics from django-podmonitor
Status: UP

🧪 Optional: Check with curl

To debug inside the cluster:

bash kubectl exec -n monitoring -it -- curl http://localhost:8000/metrics

Promethuas install

🔹 Step 2: Create Namespace

 kubectl create namespace monitoring

Create a custom values.yaml file

prometheus-values.yaml

server: service: type: NodePort # 👈 NodePort enable nodePort: 30090 # 👈 Custom NodePort (access at :30090)

persistentVolume: enabled: false # Disable PVC for simplicity

global: scrape_interval: 15s # Default scrape interval

podMonitor: enabled: true

resources: {} tolerations: [] affinity: {}

alertmanager: enabled: true persistentVolume: enabled: false # Disable PVC for Alertmanager

Collect pod metrics

kubelet: serviceMonitor: enabled: true https: true insecureSkipVerify: true port: 10250

Helm Install Command

helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
helm repo update

helm install prometheus prometheus-community/prometheus
--namespace monitoring
--create-namespace
-f prometheus-values.yaml

If use ClusterIP service UI Access (Port Forward)

kubectl port-forward -n monitoring svc/prometheus-server 9090:80

PUBLIC IP EKS NODES

aws ec2 describe-instances --filters "Name=tag:eks:cluster-name,Values=my-eks-cluster" "Name=instance-state-name,Values=running" --region us-west-2 --query "Reservations[].Instances[].PublicIpAddress" --output text

CUSTOM INSTALL PROMETHEUS NOT USE MOSTLY

===============================

PROMETHEUS SETUP WITH CUSTOM YAML (NodePort + LoadBalancer Option)

===============================

apiVersion: v1 kind: Namespace metadata: name: monitoring

apiVersion: v1 kind: ConfigMap metadata: name: prometheus-config namespace: monitoring data: prometheus.yml: | global: scrape_interval: 15s

scrape_configs:
  - job_name: 'kubernetes-nodes'
    static_configs:
      - targets: ['localhost:9100']
  - job_name: 'kubernetes-pods'
    kubernetes_sd_configs:
      - role: pod

apiVersion: apps/v1 kind: Deployment metadata: name: prometheus namespace: monitoring spec: replicas: 1 selector: matchLabels: app: prometheus template: metadata: labels: app: prometheus spec: containers: - name: prometheus image: prom/prometheus:v2.52.0 args: - "--config.file=/etc/prometheus/prometheus.yml" ports: - containerPort: 9090 volumeMounts: - name: config-volume mountPath: /etc/prometheus/ volumes: - name: config-volume configMap: name: prometheus-config

apiVersion: v1 kind: Service metadata: name: prometheus-service-nodeport namespace: monitoring spec: type: NodePort selector: app: prometheus ports: - name: web port: 80 targetPort: 9090 nodePort: 30090 # Accessible on :30090

apiVersion: v1 kind: Service metadata: name: prometheus-service-lb namespace: monitoring spec: type: LoadBalancer selector: app: prometheus ports: - name: web port: 80 targetPort: 9090

kubectl apply -f prometheus-deployment.yaml

Not Tested

✅ HPA: Configure HPA with Prometheus (Using Prometheus Adapter

🔷 1. Install Prometheus Adapter using Helm

helm repo add prometheus-community https://prometheus-community.github.io/helm-charts

helm repo update

helm install prometheus-adapter prometheus-community/prometheus-adapter
--namespace monitoring
--create-namespace
--set prometheus.url=http://prometheus-service-clusterip.monitoring.svc
--set prometheus.port=9090

Note: prometheus-service-clusterip = ClusterIP Services

🔷 2. Verify API Aggregation (Prometheus Adapter custom metrics expose)

kubectl get --raw /apis/custom.metrics.k8s.io/v1beta1 | jq .

Custom Metrics for Prometheus Adapter

apiVersion: v1 kind: ConfigMap metadata: name: custom-metrics-config namespace: monitoring data: config.yaml: | rules: - seriesQuery: 'http_requests_total{namespace!="",pod!=""}'
resources: overrides: namespace: resource: namespace pod: resource: pod name: matches: "http_requests_total" as: "http_requests_per_second" metricsQuery: rate(http_requests_total{<<.LabelMatchers>>}[1m])

👉 Note : only who pods consider that Namespace an pod are defined (- seriesQuery: 'http_requests_total{namespace!="",pod!=""}' ) 👉 Meaning: A way to link a Prometheus label to a Kubernetes object. resources: overrides: namespace: resource: namespace pod: resource: pod 👉 Meaning: HPA will get a metric named "http_requests_per_second". name: matches: "http_requests_total" as: "http_requests_per_second"

👉 Meaning: The Prometheus adapter dynamically extracts metrics of the correct pod by adding labels at runtime. (metricsQuery: rate(http_requests_total{<<.LabelMatchers>>}[1m]))

OR Second Way to write Above file

rules: external: - seriesQuery: 'http_requests_total{kubernetes_namespace!="",kubernetes_pod_name!=""}' resources: overrides: kubernetes_namespace: {resource: "namespace"} kubernetes_pod_name: {resource: "pod"} name: matches: "http_requests_total" as: "http_requests" metricsQuery: sum(rate(http_requests_total{job="my-app"}[2m]))

HPA YAML

apiVersion: autoscaling/v2 kind: HorizontalPodAutoscaler metadata: name: my-app-hpa spec: scaleTargetRef: apiVersion: apps/v1 kind: Deployment name: my-app minReplicas: 1 maxReplicas: 10 metrics: - type: External external: metric: name: http_requests target: type: Value value: 100

TERRAFORM

                                                           Use Terraform

#🔹 2. Create S3 bucket :

  aws s3api create-bucket \
    --bucket my-eks-terraform-state \
    --region us-west-2 \
   --create-bucket-configuration LocationConstraint=us-west-2

NOTE Not use -- create-bucket-configuration LocationConstraint in us-east-1

🛡️ 3. Optional: Enable versioning and encryption (recommended for Terraform)

Enable versioning:

aws s3api put-bucket-versioning \
   --bucket my-eks-terraform-state \
   --versioning-configuration Status=Enabled

Enable server-side encryption:

aws s3api put-bucket-encryption
--bucket my-eks-terraform-state
--server-side-encryption-configuration '{ "Rules": [{ "ApplyServerSideEncryptionByDefault": { "SSEAlgorithm": "AES256" } }] }'

🛠️ Create DynamoDB Table for State Locking

aws dynamodb create-table
--table-name terraform-lock-table
--attribute-definitions AttributeName=LockID,AttributeType=S
--key-schema AttributeName=LockID,KeyType=HASH
--billing-mode PAY_PER_REQUEST
--region us-west-2

Verify Table Created

aws dynamodb list-tables --region us-west-2

NOW # Ready to Use with Terraform

-- backend.tf

       terraform {
                 backend "s3" {
                                 bucket         = "my-eks-terraform-state"
                                key            = "eks/terraform.tfstate"
                               region         = "us-west-2"
                              dynamodb_table = "terraform-lock-table"
                               encrypt        = true
                                            }
                           }

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

                            #    Second way create S3 Bucket and DynomoDB

📁 bootstrap-backend.tf (Terraform script to create backend infra):

provider "aws" { region = "us-east-1" }

resource "aws_s3_bucket" "terraform_state" { bucket = "my-eks-shailesh"

versioning { enabled = true }

server_side_encryption_configuration { rule { apply_server_side_encryption_by_default { sse_algorithm = "AES256" } } }

tags = { Name = "Terraform State Bucket" Environment = "dev" } }

resource "aws_dynamodb_table" "terraform_locks" { name = "terraform-lock-table" billing_mode = "PAY_PER_REQUEST" hash_key = "LockID"

attribute { name = "LockID" type = "S" }

tags = { Name = "Terraform Lock Table" Environment = "dev" } }

NOTE : process – Create a Folder in local and create a above file in folder after that Run Following CMD into the folder: terraform init terraform apply -auto-approve

this script created S3 bucket and DynamoDB table on AWS ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Create a short Example file : terraform { required_version = ">= 1.3.0"

required_providers { aws = { source = "hashicorp/aws" version = "~> 5.0" } }

backend "s3" { bucket = "my-eks-shailesh" # 🔁 S3 bucket name (must exist) key = "eks-cluster/terraform.tfstate" # 📄 path to tfstate file inside the bucket region = "us-west-2" # 🌍 AWS region dynamodb_table = "terraform-lock-table" # 🔒 DynamoDB table for state locking encrypt = true } }

provider "aws" { region = "us-east-1" profile = "ram" }

VPC

resource "aws_vpc" "main" { cidr_block = var.vpc_cidr enable_dns_support = true enable_dns_hostnames = true

tags = { Name = "${var.name_prefix}-vpc" } }

Name		Name	Last commit message	Last commit date
Latest commit History 77 Commits
.github/workflows		.github/workflows
infra/terraform		infra/terraform
manifests		manifests
monitoring		monitoring
nginx-prometheus-exporter		nginx-prometheus-exporter
projects/mysite		projects/mysite
scripts		scripts
Jenkinsfile		Jenkinsfile
README.md		README.md

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NOTE : IF USE Terraform for create infra

Create Cluster

canary-deployment

✅ Step 1: Enable IAM OIDC Provider for your EKS cluster

✅ Step 2: Create IAM Policy for ALB Controller

✅ Step 3: Create IAM Role for ServiceAccount (IRSA)

OR

✅ cert-manager Install with kubectl (v1.14.4)

✅ Step 4: Install AWS Load Balancer Controller using Helm

Add Helm repo & update:

🔹 Install the controller:

OP Upgrade the controller:

✅ Step 5: Validate Controller is Running

Delete Ingress

Alternate (Hard Force)

Restart controller

✅ Option 1: Helm के ज़रिए Prometheus Setup (Recommended for Production)

✅ Step-by-Step: Install Prometheus in monitoring and Scrape Django Pod

🔹 Step 1: Add Prometheus Helm Repo

🔹 Step 2: Create monitoring Namespace

🔹 Step 3: Install Prometheus Stack in monitoring

🔹 Step 4: Deploy Django App in monitoring Namespace

Example Deployment.yaml:

Example Service.yaml:

🔹 Step 5: Create PodMonitor.yaml

🔹 Step 6: Verify Targets in Prometheus UI

Port forward Prometheus:

Visit:

🧪 Optional: Check with curl

🔹 Step 2: Create Namespace

Create a custom values.yaml file

prometheus-values.yaml

Collect pod metrics

Helm Install Command

If use ClusterIP service UI Access (Port Forward)

PUBLIC IP EKS NODES

CUSTOM INSTALL PROMETHEUS NOT USE MOSTLY

===============================

PROMETHEUS SETUP WITH CUSTOM YAML (NodePort + LoadBalancer Option)

===============================

kubectl apply -f prometheus-deployment.yaml

Not Tested

✅ HPA: Configure HPA with Prometheus (Using Prometheus Adapter

🔷 1. Install Prometheus Adapter using Helm

🔷 2. Verify API Aggregation (Prometheus Adapter custom metrics expose)

Custom Metrics for Prometheus Adapter

OR Second Way to write Above file

HPA YAML

TERRAFORM

🛡️ 3. Optional: Enable versioning and encryption (recommended for Terraform)

Enable versioning:

Enable server-side encryption:

🛠️ Create DynamoDB Table for State Locking

Verify Table Created

NOW # Ready to Use with Terraform

VPC

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