세모데

mysql db timezone 변경

세모데 — Fri, 29 Mar 2024 15:42:56 +0900

1. timezone 정보 생성 ( ex Asia/Seoul )

mysql_tzinfo_to_sql /usr/share/zoneinfo | mysql -u root -p mysql

2. 서버 timezone 변경

timedatectl set-timezone Asia/Seoul

3. mysql db에서 timezone 변경

set global time_zone = 'Asia/Seoul';

set session time_zone = 'Asia/Seoul';

참고...) 서버 캐릭터셋 변경

localectl set-locale LANG=ko_KR.utf8

module code for terraform

세모데 — Wed, 23 Aug 2023 15:56:56 +0900

You can refer the following example for building google cloud resource

git clone https://github.com/terraform-google-modules/terraform-google-network
cd terraform-google-network

1. directory structure

├── LICENSE
├── README.md
├── main.tf
├── variables.tf
├── outputs.tf

LICESE : describe the license like apache or gpl

README.md : explain the source code

main.tf : call the module in .terraform directory

variables.tf : define variables using module api

outputs.tf : define output result after making the resource

In addition, the .terraform directory includes module directory calling main and plugin directory.

2. main.tf

module "test-vpc-module" {
  source       = "terraform-google-modules/network/google"
  version      = "~> 6.0"
  project_id   = var.project_id # Replace this with your project ID
  network_name = var.network_name
  mtu          = 1460
  subnets = [
    {
      subnet_name   = "subnet-01"
      subnet_ip     = "10.10.10.0/24"
      subnet_region = "us-west1"
    },
    {
      subnet_name           = "subnet-02"
      subnet_ip             = "10.10.20.0/24"
      subnet_region         = "us-west1"
      subnet_private_access = "true"
      subnet_flow_logs      = "true"
    },
    {
      subnet_name               = "subnet-03"
      subnet_ip                 = "10.10.30.0/24"
      subnet_region             = "us-west1"
      subnet_flow_logs          = "true"
      subnet_flow_logs_interval = "INTERVAL_10_MIN"
      subnet_flow_logs_sampling = 0.7
      subnet_flow_logs_metadata = "INCLUDE_ALL_METADATA"
      subnet_flow_logs_filter   = "false"
    }
  ]
}

3. variables.tf

variable "project_id" {
description = "The project ID to host the network in"
default = "FILL IN YOUR PROJECT ID HERE"
}

variable "network_name" {
description = "The name of the VPC network being created"
default = "examplevpc"
}

4. output.tf

output "network_name" {
  value       = module.test-vpc-module.network_name
  description = "The name of the VPC being created"
}
output "network_self_link" {
  value       = module.test-vpc-module.network_self_link
  description = "The URI of the VPC being created"
}
output "project_id" {
  value       = module.test-vpc-module.project_id
  description = "VPC project id"
}
output "subnets_names" {
  value       = module.test-vpc-module.subnets_names
  description = "The names of the subnets being created"
}
output "subnets_ips" {
  value       = module.test-vpc-module.subnets_ips
  description = "The IP and cidrs of the subnets being created"
}
output "subnets_regions" {
  value       = module.test-vpc-module.subnets_regions
  description = "The region where subnets will be created"
}
output "subnets_private_access" {
  value       = module.test-vpc-module.subnets_private_access
  description = "Whether the subnets will have access to Google API's without a public IP"
}
output "subnets_flow_logs" {
  value       = module.test-vpc-module.subnets_flow_logs
  description = "Whether the subnets will have VPC flow logs enabled"
}
output "subnets_secondary_ranges" {
  value       = module.test-vpc-module.subnets_secondary_ranges
  description = "The secondary ranges associated with these subnets"
}
output "route_names" {
  value       = module.test-vpc-module.route_names
  description = "The routes associated with this VPC"
}

5. terraform command when above resource make

# in advance, the module is making into .terraform directory like below command

terraform init

#and then, we make the resource regarding modules.

terraform apply

how to use terraform regarding google cloud

세모데 — Mon, 21 Aug 2023 21:43:56 +0900

1. main configuration file (main.tf)

terraform {
  required_providers {
    google = {
      source = "hashicorp/google" # cloud provider
    }
  }
}
provider "google" {
  version = "3.5.0" # provider version
  project = "<PROJECT_ID>"
  region  = "us-central1"
  zone    = "us-central1-c"
}
resource "google_compute_network" "vpc_network" {
  name = "terraform-network"
}

resource "google_storage_bucket" "example_bucket" {
  name     = "<UNIQUE-BUCKET-NAME>"
  location = "US"
  website {
    main_page_suffix = "index.html"
    not_found_page   = "404.html"
  }
}

# Create a new instance that uses the bucket
resource "google_compute_instance" "another_instance" {
  # Tells Terraform that this VM instance must be created only after the
  # storage bucket has been created.
  depends_on = [google_storage_bucket.example_bucket] # depend option between resources.
  name         = "terraform-instance-2"
  machine_type = "e2-micro"
  boot_disk {
    initialize_params {
      image = "cos-cloud/cos-stable"
    }
  }
  network_interface {
    network = google_compute_network.vpc_network.self_link
    access_config {
    }
  }
}

2. terraform initialize

terraform init

3. create resource ( based on above main.tf )

terraform apply (after showing plan, it can create if you answer yes at the confirmation prompt to proceed)

# the sign means when showing the plan.

+ : add resource

~ : update resource

- : delete resource

+/- : remove and recreate resource

4. destroy resource

terraform destroy

google cloud storage and database

세모데 — Fri, 18 Aug 2023 15:58:22 +0900

google terraform IAC example

세모데 — Wed, 16 Aug 2023 16:23:18 +0900

This is iac example of google cloud.

terraform {
  required_providers {
    google = {
      source = "hashicorp/google"
    }
  }
}
provider "google" {
  version = "3.5.0"
  project = "<PROJECT_ID>"
  region  = "us-central1"
  zone    = "us-central1-c"
}
resource "google_compute_network" "vpc_network" {
  name = "test-network"
}

resource "google_compute_instance" "vm_instance" {
  name         = "terraform-instance"
  machine_type = "e2-micro"
  boot_disk {
    initialize_params {
      image = "debian-cloud/debian-11"
    }
  }
  network_interface {
    network = google_compute_network.vpc_network.name
    access_config {
    }
  }
}

# New resource for the storage bucket our application will use.
resource "google_storage_bucket" "example_bucket" {
  name     = "<UNIQUE-BUCKET-NAME>"
  location = "US"
  website {
    main_page_suffix = "index.html"
    not_found_page   = "404.html"
  }
}
# Create a new instance that uses the bucket
resource "google_compute_instance" "another_instance" {
  # Tells Terraform that this VM instance must be created only after the
  # storage bucket has been created.
  depends_on = [google_storage_bucket.example_bucket]
  name         = "terraform-instance-2"
  machine_type = "e2-micro"
  boot_disk {
    initialize_params {
      image = "cos-cloud/cos-stable"
    }
  }
  network_interface {
    network = google_compute_network.vpc_network.self_link
    access_config {
    }
  }
}

GKE - Kubernetes

세모데 — Tue, 15 Aug 2023 17:21:28 +0900

HTTP LB Load test

세모데 — Mon, 14 Aug 2023 12:39:58 +0900

1. note public ip of http load balancer and export it in stress VM server.

export LB_IP=xx.xx.xx.xx

2. execute stress test in stress VM server. (based on Ubuntu)

ab -n 500000 -c 1000 http://$LB_IP/

3. capture execution screen of ab command as stress test

4. capture monitoring screen of LB

encoding for class labels

세모데 — Mon, 3 Jul 2023 15:50:52 +0900

1. use pandas

import numpy as np

""" coverted string class to integer """
class-map = { label : idx for idx, label in enumerate(np.unique(df['class']))}

""" reversed integer to strings """
df['class'] = df['class'].map(class-map)

2. use scikit-learn

from sklearn.preprocessing import LabelEncoder
enc = LabelEncoder()

""" converted integer to strings """"
y = enc.fit_transform(df['class'].values)

""" reversed integer to strings """
enc.inverse_transform(y)

imputing missing values in pandas

세모데 — Mon, 3 Jul 2023 14:46:26 +0900

1. use sklearn

from sklearn.impute import SimpleImputer
import numpy as np

im = SimpleImputer(missing_values=np.nan, strategy='mean')
im = im.fit(df.values)
imputed_data = im.transform(df.values)

2. use dataframe method

df.fillna(df.mean())

drop missing data in dataframe

세모데 — Mon, 3 Jul 2023 14:36:51 +0900

1. null or NaN or missing data check

df.isnull().sum()

2. drop data based on X-axis

df.dropna(axis=0)

3. drop data in terms of Y-axis

df.dropna(axis=1)

4. drop data included all NaN in Columns

df.dropna(how='all')

5. drop rows that have fewer than 4 values

df.dropna(thresh=4)

6. drop data in specific columns

df.dropna(subset=['C'])