fabidick22

Cross-Cloud Uniform Infra Automation

Hybrid Cloud

1. K8s, MicroK8s and Netmaker

Type	Limitation	Solution
Etcd	It is the brain of your cluster and is not latency tolerant.	MicroK8s
Networking	Nodes need to be able to talk to each other directly and securely.	Netmaker
Latency	High latency is unacceptable for enterprise applications.	Netmaker

fabidick22

Free Tools

Terraform

• terraform-docs:
  1. Generate documentation from Terraform modules in various output formats.
  2. Can be imported in your project as a library (Go).
  3. GitHub Actions available (terraform-docs/gh-actions@main)
• mkdocs-terraform-monorepo-plugin
  1. This plugin enables you to build multiple sets of documentation in a single Mkdocs

fabidick22

export AWS_REGION=us-east-1
export REGISTRY_USER=AWS
export REGISTRY_PASSWORD=$(aws ecr get-login-password --region $AWS_REGION)
export REGISTRY=000000000000.dkr.ecr.$AWS_REGION.amazonaws.com

# needed the SOCI snapshotter which runs as root
echo $REGISTRY_PASSWORD | sudo nerdctl login -u $REGISTRY_USER --password-stdin $REGISTRY

# Pull and push image
sudo nerdctl pull docker.io/library/rabbitmq:latest

fabidick22

name: SOCI
on: [push]
env:
  NERDCTL_VERSION: "1.6.2"
  SOCI_VERSION: "0.4.0"
jobs:
  build-push:
    name: Build and push image
    runs-on: ubuntu-latest
    steps:

fabidick22

import boto3
import sqlite3
from datetime import datetime
from dateutil import tz

CLUSTER = 'sh-runners'
REGION = 'us-east-1'

ecs_client = boto3.client('ecs', region_name=REGION)

fabidick22

import plotly.graph_objects as go
import sqlite3


conn = sqlite3.connect('ecs_data_v1.sqlite')
conn_v2 = sqlite3.connect('ecs_data_v2.sqlite')

cursor = conn.cursor()
cursor_v2 = conn_v2.cursor()

fabidick22

vcpu_used_by_instance = 1   # Resource used by sh-runner-small-teamS-ruby              
gb_used_by_instance = 4     # Resource used by sh-runner-small-teamS-ruby
vcpu_hourly_rate = 0.04048  # Cost per vCPU hour
gb_hourly_rate = 0.004445   # Cost per GB-hour of RAM
workflow_executions = 150   # Number of monthly executions
jobs_per_execution = 30     # Number of jobs per execution
job_duration_hours = 0.0667 # Duration of each job in hours (4 min)
start_time_hours = 0.0333   # Start time in hours (2 min)
optimization_percentage = 0.72  # Start time optimization percentage
hourly_cost_fargate_instance = (vcpu_hourly_rate * vcpu) + (gb_hourly_rate * gb)

fabidick22

from tabulate import tabulate

def get_fargate_spot_cost(region, vcpu_cost=None, gb_cost=None):
    """
    If vcpu_cost and vcpu_cost are 'None', the current value is retrived from AWS
    """
    import requests
    endpoint = "https://dftu77xade0tc.cloudfront.net/fargate-spot-prices.json"
    try:
        if vcpu_cost is not None and gb_cost is not None: