Arno  Bradtke

Arno Bradtke

1597944180

Getting wildcard SSL certificate in Kubernetes with cert-manager

In this article, I’ll shortly describe how to get an SSL certificate with HTTP01 validation and a wildcard certificate with DNS01 validation on AWS example.

Image for post

https://letsencrypt.org/


So we already have some ingress and HELM for our k8s cluster, and we want to get some certs for domain dummy.example.com.

Let’s install cert-manager using HELM:

helm install --namespace kube-system -n cert-manager stable/cert-manager

If you prefer to use the latest chart version for cert-manager you can follow the instructions here.

For issuing some certificates we need to have at least one Issuer or ClusterIssuer. The difference between them that Issuer works only inside one namespace, unlike ClusterIssuer which works globally for the cluster.

Let’s create ClusterIssuer:

cat <<EOF | kubectl create -f -
apiVersion: certmanager.k8s.io/v1alpha1
kind: ClusterIssuer
metadata:
  name: le-clusterissuer
  namespace: kube-system
spec:
  acme:
    server: https://acme-v02.api.letsencrypt.org/directory
    email: devops@example.com
    privateKeySecretRef:
      name: le-clusterissuer
    http01: {}
EOF

What’s there:

  • le-clusteissuer — ClusterIssuer name
  • devops@example.com — mailbox for receiving emails from Let’s Encrypt
  • http01: {} — validation method

After creating ClusterIssuer we can check the status:

kubectl describe clusterissuer le-clusterissuer -n kube-system | egrep "Status|Message"
Status:
    Message:    The ACME account was registered with the ACME server
    Status:     True

So now we have ClusterIssuer, and we can create new certificates.

#aws #kubernetes #lets-encrypt #cert-manager #ssl

What is GEEK

Buddha Community

Getting wildcard SSL certificate in Kubernetes with cert-manager
Christa  Stehr

Christa Stehr

1602964260

50+ Useful Kubernetes Tools for 2020 - Part 2

Introduction

Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.

According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.

(State of Kubernetes and Container Security, 2020)

And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.

(State of Kubernetes and Container Security, 2020)

#blog #tools #amazon elastic kubernetes service #application security #aws kms #botkube #caylent #cli #container monitoring #container orchestration tools #container security #containers #continuous delivery #continuous deployment #continuous integration #contour #developers #development #developments #draft #eksctl #firewall #gcp #github #harbor #helm #helm charts #helm-2to3 #helm-aws-secret-plugin #helm-docs #helm-operator-get-started #helm-secrets #iam #json #k-rail #k3s #k3sup #k8s #keel.sh #keycloak #kiali #kiam #klum #knative #krew #ksniff #kube #kube-prod-runtime #kube-ps1 #kube-scan #kube-state-metrics #kube2iam #kubeapps #kubebuilder #kubeconfig #kubectl #kubectl-aws-secrets #kubefwd #kubernetes #kubernetes command line tool #kubernetes configuration #kubernetes deployment #kubernetes in development #kubernetes in production #kubernetes ingress #kubernetes interfaces #kubernetes monitoring #kubernetes networking #kubernetes observability #kubernetes plugins #kubernetes secrets #kubernetes security #kubernetes security best practices #kubernetes security vendors #kubernetes service discovery #kubernetic #kubesec #kubeterminal #kubeval #kudo #kuma #microsoft azure key vault #mozilla sops #octant #octarine #open source #palo alto kubernetes security #permission-manager #pgp #rafay #rakess #rancher #rook #secrets operations #serverless function #service mesh #shell-operator #snyk #snyk container #sonobuoy #strongdm #tcpdump #tenkai #testing #tigera #tilt #vert.x #wireshark #yaml

Shubham Ankit

Shubham Ankit

1657081614

How to Automate Excel with Python | Python Excel Tutorial (OpenPyXL)

How to Automate Excel with Python

In this article, We will show how we can use python to automate Excel . A useful Python library is Openpyxl which we will learn to do Excel Automation

What is OPENPYXL

Openpyxl is a Python library that is used to read from an Excel file or write to an Excel file. Data scientists use Openpyxl for data analysis, data copying, data mining, drawing charts, styling sheets, adding formulas, and more.

Workbook: A spreadsheet is represented as a workbook in openpyxl. A workbook consists of one or more sheets.

Sheet: A sheet is a single page composed of cells for organizing data.

Cell: The intersection of a row and a column is called a cell. Usually represented by A1, B5, etc.

Row: A row is a horizontal line represented by a number (1,2, etc.).

Column: A column is a vertical line represented by a capital letter (A, B, etc.).

Openpyxl can be installed using the pip command and it is recommended to install it in a virtual environment.

pip install openpyxl

CREATE A NEW WORKBOOK

We start by creating a new spreadsheet, which is called a workbook in Openpyxl. We import the workbook module from Openpyxl and use the function Workbook() which creates a new workbook.

from openpyxl
import Workbook
#creates a new workbook
wb = Workbook()
#Gets the first active worksheet
ws = wb.active
#creating new worksheets by using the create_sheet method

ws1 = wb.create_sheet("sheet1", 0) #inserts at first position
ws2 = wb.create_sheet("sheet2") #inserts at last position
ws3 = wb.create_sheet("sheet3", -1) #inserts at penultimate position

#Renaming the sheet
ws.title = "Example"

#save the workbook
wb.save(filename = "example.xlsx")

READING DATA FROM WORKBOOK

We load the file using the function load_Workbook() which takes the filename as an argument. The file must be saved in the same working directory.

#loading a workbook
wb = openpyxl.load_workbook("example.xlsx")

 

GETTING SHEETS FROM THE LOADED WORKBOOK

 

#getting sheet names
wb.sheetnames
result = ['sheet1', 'Sheet', 'sheet3', 'sheet2']

#getting a particular sheet
sheet1 = wb["sheet2"]

#getting sheet title
sheet1.title
result = 'sheet2'

#Getting the active sheet
sheetactive = wb.active
result = 'sheet1'

 

ACCESSING CELLS AND CELL VALUES

 

#get a cell from the sheet
sheet1["A1"] <
  Cell 'Sheet1'.A1 >

  #get the cell value
ws["A1"].value 'Segment'

#accessing cell using row and column and assigning a value
d = ws.cell(row = 4, column = 2, value = 10)
d.value
10

 

ITERATING THROUGH ROWS AND COLUMNS

 

#looping through each row and column
for x in range(1, 5):
  for y in range(1, 5):
  print(x, y, ws.cell(row = x, column = y)
    .value)

#getting the highest row number
ws.max_row
701

#getting the highest column number
ws.max_column
19

There are two functions for iterating through rows and columns.

Iter_rows() => returns the rows
Iter_cols() => returns the columns {
  min_row = 4, max_row = 5, min_col = 2, max_col = 5
} => This can be used to set the boundaries
for any iteration.

Example:

#iterating rows
for row in ws.iter_rows(min_row = 2, max_col = 3, max_row = 3):
  for cell in row:
  print(cell) <
  Cell 'Sheet1'.A2 >
  <
  Cell 'Sheet1'.B2 >
  <
  Cell 'Sheet1'.C2 >
  <
  Cell 'Sheet1'.A3 >
  <
  Cell 'Sheet1'.B3 >
  <
  Cell 'Sheet1'.C3 >

  #iterating columns
for col in ws.iter_cols(min_row = 2, max_col = 3, max_row = 3):
  for cell in col:
  print(cell) <
  Cell 'Sheet1'.A2 >
  <
  Cell 'Sheet1'.A3 >
  <
  Cell 'Sheet1'.B2 >
  <
  Cell 'Sheet1'.B3 >
  <
  Cell 'Sheet1'.C2 >
  <
  Cell 'Sheet1'.C3 >

To get all the rows of the worksheet we use the method worksheet.rows and to get all the columns of the worksheet we use the method worksheet.columns. Similarly, to iterate only through the values we use the method worksheet.values.


Example:

for row in ws.values:
  for value in row:
  print(value)

 

WRITING DATA TO AN EXCEL FILE

Writing to a workbook can be done in many ways such as adding a formula, adding charts, images, updating cell values, inserting rows and columns, etc… We will discuss each of these with an example.

 

CREATING AND SAVING A NEW WORKBOOK

 

#creates a new workbook
wb = openpyxl.Workbook()

#saving the workbook
wb.save("new.xlsx")

 

ADDING AND REMOVING SHEETS

 

#creating a new sheet
ws1 = wb.create_sheet(title = "sheet 2")

#creating a new sheet at index 0
ws2 = wb.create_sheet(index = 0, title = "sheet 0")

#checking the sheet names
wb.sheetnames['sheet 0', 'Sheet', 'sheet 2']

#deleting a sheet
del wb['sheet 0']

#checking sheetnames
wb.sheetnames['Sheet', 'sheet 2']

 

ADDING CELL VALUES

 

#checking the sheet value
ws['B2'].value
null

#adding value to cell
ws['B2'] = 367

#checking value
ws['B2'].value
367

 

ADDING FORMULAS

 

We often require formulas to be included in our Excel datasheet. We can easily add formulas using the Openpyxl module just like you add values to a cell.
 

For example:

import openpyxl
from openpyxl
import Workbook

wb = openpyxl.load_workbook("new1.xlsx")
ws = wb['Sheet']

ws['A9'] = '=SUM(A2:A8)'

wb.save("new2.xlsx")

The above program will add the formula (=SUM(A2:A8)) in cell A9. The result will be as below.

image

 

MERGE/UNMERGE CELLS

Two or more cells can be merged to a rectangular area using the method merge_cells(), and similarly, they can be unmerged using the method unmerge_cells().

For example:
Merge cells

#merge cells B2 to C9
ws.merge_cells('B2:C9')
ws['B2'] = "Merged cells"

Adding the above code to the previous example will merge cells as below.

image

UNMERGE CELLS

 

#unmerge cells B2 to C9
ws.unmerge_cells('B2:C9')

The above code will unmerge cells from B2 to C9.

INSERTING AN IMAGE

To insert an image we import the image function from the module openpyxl.drawing.image. We then load our image and add it to the cell as shown in the below example.

Example:

import openpyxl
from openpyxl
import Workbook
from openpyxl.drawing.image
import Image

wb = openpyxl.load_workbook("new1.xlsx")
ws = wb['Sheet']
#loading the image(should be in same folder)
img = Image('logo.png')
ws['A1'] = "Adding image"
#adjusting size
img.height = 130
img.width = 200
#adding img to cell A3

ws.add_image(img, 'A3')

wb.save("new2.xlsx")

Result:

image

CREATING CHARTS

Charts are essential to show a visualization of data. We can create charts from Excel data using the Openpyxl module chart. Different forms of charts such as line charts, bar charts, 3D line charts, etc., can be created. We need to create a reference that contains the data to be used for the chart, which is nothing but a selection of cells (rows and columns). I am using sample data to create a 3D bar chart in the below example:

Example

import openpyxl
from openpyxl
import Workbook
from openpyxl.chart
import BarChart3D, Reference, series

wb = openpyxl.load_workbook("example.xlsx")
ws = wb.active

values = Reference(ws, min_col = 3, min_row = 2, max_col = 3, max_row = 40)
chart = BarChart3D()
chart.add_data(values)
ws.add_chart(chart, "E3")
wb.save("MyChart.xlsx")

Result
image


How to Automate Excel with Python with Video Tutorial

Welcome to another video! In this video, We will cover how we can use python to automate Excel. I'll be going over everything from creating workbooks to accessing individual cells and stylizing cells. There is a ton of things that you can do with Excel but I'll just be covering the core/base things in OpenPyXl.

⭐️ Timestamps ⭐️
00:00 | Introduction
02:14 | Installing openpyxl
03:19 | Testing Installation
04:25 | Loading an Existing Workbook
06:46 | Accessing Worksheets
07:37 | Accessing Cell Values
08:58 | Saving Workbooks
09:52 | Creating, Listing and Changing Sheets
11:50 | Creating a New Workbook
12:39 | Adding/Appending Rows
14:26 | Accessing Multiple Cells
20:46 | Merging Cells
22:27 | Inserting and Deleting Rows
23:35 | Inserting and Deleting Columns
24:48 | Copying and Moving Cells
26:06 | Practical Example, Formulas & Cell Styling

📄 Resources 📄
OpenPyXL Docs: https://openpyxl.readthedocs.io/en/stable/ 
Code Written in This Tutorial: https://github.com/techwithtim/ExcelPythonTutorial 
Subscribe: https://www.youtube.com/c/TechWithTim/featured 

#python 

Arno  Bradtke

Arno Bradtke

1597944180

Getting wildcard SSL certificate in Kubernetes with cert-manager

In this article, I’ll shortly describe how to get an SSL certificate with HTTP01 validation and a wildcard certificate with DNS01 validation on AWS example.

Image for post

https://letsencrypt.org/


So we already have some ingress and HELM for our k8s cluster, and we want to get some certs for domain dummy.example.com.

Let’s install cert-manager using HELM:

helm install --namespace kube-system -n cert-manager stable/cert-manager

If you prefer to use the latest chart version for cert-manager you can follow the instructions here.

For issuing some certificates we need to have at least one Issuer or ClusterIssuer. The difference between them that Issuer works only inside one namespace, unlike ClusterIssuer which works globally for the cluster.

Let’s create ClusterIssuer:

cat <<EOF | kubectl create -f -
apiVersion: certmanager.k8s.io/v1alpha1
kind: ClusterIssuer
metadata:
  name: le-clusterissuer
  namespace: kube-system
spec:
  acme:
    server: https://acme-v02.api.letsencrypt.org/directory
    email: devops@example.com
    privateKeySecretRef:
      name: le-clusterissuer
    http01: {}
EOF

What’s there:

  • le-clusteissuer — ClusterIssuer name
  • devops@example.com — mailbox for receiving emails from Let’s Encrypt
  • http01: {} — validation method

After creating ClusterIssuer we can check the status:

kubectl describe clusterissuer le-clusterissuer -n kube-system | egrep "Status|Message"
Status:
    Message:    The ACME account was registered with the ACME server
    Status:     True

So now we have ClusterIssuer, and we can create new certificates.

#aws #kubernetes #lets-encrypt #cert-manager #ssl

Monty  Boehm

Monty Boehm

1659453850

Twitter.jl: Julia Package to Access Twitter API

Twitter.jl

A Julia package for interacting with the Twitter API.

Twitter.jl is a Julia package to work with the Twitter API v1.1. Currently, only the REST API methods are supported; streaming API endpoints aren't implemented at this time.

All functions have required arguments for those parameters required by Twitter and an options keyword argument to provide a Dict{String, String} of optional parameters Twitter API documentation. Most function calls will return either a Dict or an Array <: TwitterType. Bad requests will return the response code from the API (403, 404, etc).

DataFrame methods are defined for functions returning composite types: Tweets, Places, Lists, and Users.

Authentication

Before one can make use of this package, you must create an application on the Twitter's Developer Platform.

Once your application is approved, you can access your dashboard/portal to grab your authentication credentials from the "Details" tab of the application.

Note that you will also want to ensure that your App has Read / Write OAuth access in order to post tweets. You can find out more about this on Stack Overflow.

Installation

To install this package, enter ] on the REPL to bring up Julia's package manager. Then add the package:

julia> ]
(v1.7) pkg> add Twitter

Tip: Press Ctrl+C to return to the julia> prompt.

Usage

To run Twitter.jl, enter the following command in your Julia REPL

julia> using Twitter

Then the a global variable has to be declared with the twitterauth function. This function holds the consumer_key(API Key), consumer_secret(API Key Secret), oauth_token(Access Token), and oauth_secret(Access Token Secret) respectively.

twitterauth("6nOtpXmf...", # API Key
            "sES5Zlj096S...", # API Key Secret
            "98689850-Hj...", # Access Token
            "UroqCVpWKIt...") # Access Token Secret
  • Ensure you put your credentials in an env file to avoid pushing your secrets to the public 🙀.

Note: This package does not currently support OAuth authentication.

Code examples

See runtests.jl for example function calls.

using Twitter, Test
using JSON, OAuth

# set debugging
ENV["JULIA_DEBUG"]=Twitter

twitterauth(ENV["CONSUMER_KEY"], ENV["CONSUMER_SECRET"], ENV["ACCESS_TOKEN"], ENV["ACCESS_TOKEN_SECRET"])

#get_mentions_timeline
mentions_timeline_default = get_mentions_timeline()
tw = mentions_timeline_default[1]
tw_df = DataFrame(mentions_timeline_default)
@test 0 <= length(mentions_timeline_default) <= 20
@test typeof(mentions_timeline_default) == Vector{Tweets}
@test typeof(tw) == Tweets
@test size(tw_df)[2] == 30

#get_user_timeline
user_timeline_default = get_user_timeline(screen_name = "randyzwitch")
@test typeof(user_timeline_default) == Vector{Tweets}

#get_home_timeline
home_timeline_default = get_home_timeline()
@test typeof(home_timeline_default) == Vector{Tweets}

#get_single_tweet_id
get_tweet_by_id = get_single_tweet_id(id = "434685122671939584")
@test typeof(get_tweet_by_id) == Tweets

#get_search_tweets
duke_tweets = get_search_tweets(q = "#Duke", count = 200)
@test typeof(duke_tweets) <: Dict

#test sending/deleting direct messages
#commenting out because Twitter API changed. Come back to fix
# send_dm = post_direct_messages_send(text = "Testing from Julia, this might disappear later $(time())", screen_name = "randyzwitch")
# get_single_dm = get_direct_messages_show(id = send_dm.id)
# destroy = post_direct_messages_destroy(id = send_dm.id)
# @test typeof(send_dm) == Tweets
# @test typeof(get_single_dm) == Tweets
# @test typeof(destroy) == Tweets

#creating/destroying friendships
add_friend = post_friendships_create(screen_name = "kyrieirving")

unfollow = post_friendships_destroy(screen_name = "kyrieirving")
unfollow_df = DataFrame(unfollow)
@test typeof(add_friend) == Users
@test typeof(unfollow) == Users
@test size(unfollow_df)[2] == 40

# create a cursor for follower ids
follow_cursor_test = get_followers_ids(screen_name = "twitter", count = 10_000)
@test length(follow_cursor_test["ids"]) == 10_000

# create a cursor for friend ids - use barackobama because he follows a lot of accounts!
friend_cursor_test = get_friends_ids(screen_name = "BarackObama", count = 10_000)
@test length(friend_cursor_test["ids"]) == 10_000

# create a test for home timelines
home_t = get_home_timeline(count = 2)
@test length(home_t) > 1

# TEST of cursoring functionality on user timelines
user_t = get_user_timeline(screen_name = "stefanjwojcik", count = 400)
@test length(user_t) == 400
# get the minimum ID of the tweets returned (the earliest)
minid = minimum(x.id for x in user_t);

# now iterate until you hit that tweet: should return 399
# WARNING: current versions of julia cannot use keywords in macros? read here: https://github.com/JuliaLang/julia/pull/29261
# eventually replace since_id = minid
tweets_since = get_user_timeline(screen_name = "stefanjwojcik", count = 400, since_id = 1001808621053898752, include_rts=1)

@test length(tweets_since)>=399

# testing get_mentions_timeline
mentions = get_mentions_timeline(screen_name = "stefanjwojcik", count = 300) 
@test length(mentions) >= 50 #sometimes API doesn't return number requested (twitter API specifies count is the max returned, may be much lower)
@test Tweets<:typeof(mentions[1])

# testing retweets_of_me
my_rts = get_retweets_of_me(count = 300)
@test Tweets<:typeof(my_rts[1])

Want to contribute?

Contributions are welcome! Kindly refer to the contribution guidelines.

Linux: Build Status 

CodeCov: codecov

Author: Randyzwitch
Source Code: https://github.com/randyzwitch/Twitter.jl 
License: View license

#julia #api #twitter 

Jerod  Durgan

Jerod Durgan

1618345320

Install Certificate Manager Controller in Kubernetes

Automate the process of issuing public key certificates from multiple sources, ensuring they are valid, up to date, and renew before expiration.

· K8s Controller

∘ Prepare

∘ Install

∘ Uninstall

· Self Signed

∘ Issuer

∘ Certificate

· Advanced

∘ Share Secrets between Namespaces

· Summary

Note: This post is a quick start guide for deploying and using cert-manager on a Kubernetes cluster.

Prerequisites

Why do we need to worry about certificates? When declaring a domain name i.e my-website.domain.com and addressing it from either internal network and/or public internet, the devices used to perform the call (web browsers, internal services, containers etc…) would require to check its validity. In order to do that, the domain name should have a certificate that is issued and trusted to operate securely.

Why do we need a certificate manager? Certificate validity has its expiration date, which means certificates have to get renewed. It might be a cumbersome task when there are many certificates to handle. This is the reason cert-manager exists, to help with issuing certificates from a variety of sources, such as Let’s Encrypt, a simple signing key pair, or self-signed. It will ensure certificates are valid, up to date and attempt to renew certificates at a configured time before expiry.

Note: The domain referenced in this post is MY_DOMAIN, please change accordingly. If you interested in a local-only work mode, you don’t have to pay for a new domain, just decide on a name and use it. For example, if your desired domain is homelab.com, replace MY_DOMAIN with homelab.

#cert-manager #kubernetes #certificate #k8s