Skip to content

README.md

Latest commit

 

History

History
243 lines (167 loc) · 3.5 KB

README.md

File metadata and controls

243 lines (167 loc) · 3.5 KB
Raw

🚀 Kubesage – AI Kubernetes Debugger

An AI-powered Kubernetes debugging CLI that works with both:

  • 🖥️ Local clusters (Kind)
  • ☁️ AWS EKS clusters

📋 Prerequisites

Make sure you have:

  • 🐧 Linux (Ubuntu recommended)
  • 🐍 Python 3.9+
  • ☁️ AWS Account
  • 💳 Billing enabled on AWS
  • 🧠 Basic knowledge of Kubernetes

🔐 Step 1: Setup AWS IAM

1️⃣ Create IAM User

Go to:

👉 IAM → Users → Create User

Create user:

eks-admin

Attach policy:

AdministratorAccess

⚠️ For production use, avoid AdministratorAccess. Create a scoped policy instead.

2️⃣ Generate Access Keys

Go to:

IAM → Users → eks-admin → Security Credentials

Create:

Access Key ID Secret Access Key

⚠️ Save them securely.

🛠️ Step 2: Install Required Tools

☁️ Install AWS CLI v2

curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
sudo apt install unzip -y
unzip awscliv2.zip
sudo ./aws/install

aws --version

🔑 Configure AWS Credentials

aws configure

Enter:

  • Access Key
  • Secret Key
  • Region → us-east-1
  • Output → json

🐳 Install Docker

sudo apt update
sudo apt install docker.io -y
sudo systemctl enable docker
sudo systemctl start docker

Add your user to docker group:

sudo usermod -aG docker $USER
newgrp docker

Verify:

docker --version
docker ps

☸️ Install kubectl

curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"

sudo install -o root -g root -m 0755 kubectl /usr/local/bin/kubectl

kubectl version --client

🧩 Install eksctl

ARCH=amd64
PLATFORM=$(uname -s)_$ARCH

curl -sLO "https://github.com/eksctl-io/eksctl/releases/latest/download/eksctl_$PLATFORM.tar.gz"

tar -xzf eksctl_$PLATFORM.tar.gz -C /tmp
sudo install -m 0755 /tmp/eksctl /usr/local/bin

Verify:

eksctl version

☁️ Step 3: Create EKS Cluster

eksctl create cluster \
  --name kubesage-demo \
  --region us-east-1 \
  --node-type t2.medium \
  --nodes-min 2 \
  --nodes-max 2

⏳ Takes ~10–15 minutes.

🔗 Connect kubectl to EKS

aws eks update-kubeconfig --region us-east-1 --name kubesage-demo

Verify:

kubectl get nodes

You should see 2 worker nodes ✅

📦 Step 4: Deploy Application

kubectl apply -f ./k8s/

Check:

kubectl get pods

🤖 Step 5: Run AI Debugger CLI

Setup Virtual Environment using pip

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python cli.py \
  -p <pod_name> \
  --cluster-type eks \
  --cluster-name kubesage-demo \
  --region us-east-1

Example:

python cli.py -p oom-deployment-xxxxx \
  --cluster-type eks \
  --cluster-name kubesage-demo \
  --region us-east-1

🔍 Step 6: Observe AI Debugging

kubectl get pods
kubectl describe pod <pod_name>
kubectl logs <pod_name>

🖥️ (Optional) Run on Local Kubernetes (Kind)

If using Kind:

kind create cluster
kubectl get nodes

Switch context:

kubectl config use-context kind-kind

Run CLI:

python cli.py -p <pod_name> --cluster-type local

💰 VERY IMPORTANT: Cleanup (Avoid AWS Bill Shock 😭)

After testing:

eksctl delete cluster \
  --name kubesage-demo \
  --region us-east-1

Also verify:

  • EC2 instances deleted
  • Load balancers deleted
  • EBS volumes deleted