import pandas as pd

customers = pd.read_parquet('customers.parquet')
orders = pd.read_parquet('orders.parquet')

assert customers['customer_id'].is_unique, 'customer table must be unique by customer_id'

import pandas as pd

df = pd.read_parquet('events.parquet')
df['event_date'] = pd.to_datetime(df['event_date'])
df['month'] = df['event_date'].dt.to_period('M').astype(str)

import pandas as pd

df = pd.read_csv('customers.csv')

df.columns = df.columns.str.strip().str.lower().str.replace(' ', '_', regex=False)

import pandas as pd

df = pd.read_csv(
    'orders.csv',
    parse_dates=['created_at'],
    dtype={

#!/usr/bin/env bash
set -euo pipefail

# ==========================================================
# Production Incident Response Runbook
# ==========================================================

// k6 Load Test Configuration
// Run: k6 run load-test.js --env BASE_URL=https://api.example.com

import http from 'k6/http';
import { check, sleep, group } from 'k6';
import { Rate, Trend, Counter } from 'k6/metrics';

#!/usr/bin/env bash
set -euo pipefail

# Container Registry Management & Image Lifecycle

# ============================================

# AWS Lambda Function with API Gateway trigger

# === Lambda function ===
resource "aws_lambda_function" "api_handler" {
  function_name = "${var.project}-api-handler"
  description   = "API request handler for ${var.project}"

# === Vault Agent Injector: Auto-inject secrets into pods ===
apiVersion: apps/v1
kind: Deployment
metadata:
  name: api-server
  namespace: production

# === ArgoCD Application: Single app deployment ===
apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
  name: myapp-production
  namespace: argocd

# AWS VPC with public/private subnets across 3 AZs

data "aws_availability_zones" "available" {
  state = "available"
}

# === One-off Job: Database migration ===
apiVersion: batch/v1
kind: Job
metadata:
  name: db-migrate
  namespace: production