Dirga36

package terraform.finops

deny[msg] {
    resource := input.resource_changes[_]
    resource.type == "aws_instance"
    allowed_types := {"t3.micro", "t3.small", "t3.medium"}
    not allowed_types[resource.change.after.instance_type]

    msg := sprintf(
        "Instance type %v is not in the approved list for this environment",

Dirga36

import boto3
from datetime import datetime, timedelta

def find_idle_instances(cpu_threshold=5.0, days=7):
    ec2 = boto3.client("ec2")
    cloudwatch = boto3.client("cloudwatch")
    idle_instances = []

    instances = ec2.describe_instances(
        Filters=[{"Name": "instance-state-name", "Values": ["running"]}]

Dirga36

import boto3

REQUIRED_TAGS = {"team", "environment", "project"}

def lambda_handler(event, context):
    ec2 = boto3.client("ec2")
    detail = event["detail"]

    if detail["eventName"] != "RunInstances":
        return

Dirga36

from sklearn.cluster import KMeans
import pandas as pd

def classify_workload_patterns(usage_df, n_clusters=4):
    """
    Cluster storage volumes by access frequency, size, and
    read/write ratio to recommend appropriate storage tiers.
    """
    features = usage_df[["avg_daily_accesses", "size_gb", "read_write_ratio"]]

Dirga36

import numpy as np
from statsmodels.tsa.holtwinters import ExponentialSmoothing

def forecast_storage_demand(historical_usage, periods_ahead=24):
    """
    Forecast storage utilization for the next N hours using
    Holt-Winters exponential smoothing.
    """
    model = ExponentialSmoothing(
        historical_usage,

Dirga36

import time
import random
import boto3
from botocore.exceptions import ClientError

s3 = boto3.client("s3")

def upload_with_retry(local_path: str, bucket: str, s3_key: str, max_retries: int = 5) -> bool:
    for attempt in range(max_retries):
        try:

Dirga36

import boto3
import json

s3 = boto3.client("s3")

def lambda_handler(event, context):
    for record in event["Records"]:
        bucket = record["s3"]["bucket"]["name"]
        key = record["s3"]["object"]["key"]

Dirga36

import hashlib
import boto3
from pathlib import Path

s3 = boto3.client("s3")

def file_hash(path: Path) -> str:
    return hashlib.md5(path.read_bytes()).hexdigest()

def sync_directory(local_dir: str, bucket: str, prefix: str = "") -> None:

Dirga36

import boto3
from pathlib import Path

s3 = boto3.client("s3")

def upload_file(local_path: str, bucket: str, s3_key: str) -> None:
    """Upload a single file to S3, preserving content type where possible."""
    path = Path(local_path)
    if not path.exists():
        raise FileNotFoundError(f"No such file: {local_path}")

Dirga36

pip install boto3
export AWS_ACCESS_KEY_ID="your-access-key"
export AWS_SECRET_ACCESS_KEY="your-secret-key"
export AWS_DEFAULT_REGION="us-east-1"