Savage leaky programs

It’s come to my attention recently that despite a fresh install of Linux Mint, certain programs seem to leak like a basket and hang around after they’re closed too.

I’d noticed my machine freezing intermittently and adding the memory monitor panel item revealed that the system memory was filling up.

The blue mem bar fills up over time when Brave is left open. Disappointing for such an otherwise excellent Web Browser.

xreader and brave seemed to be the main culprits but since rebuilding my desktop machine, I’ve not been using many other programs apart from ledger live to track the value of my crypto currency portfolio while the fed prints money ad infinitum during the coronavirus pandemic. I digress.

Killing processes gets old really quick, so I wrote a quick’n’dirty little shell script to do it for me. Rather than killing individual processes, it savages all processes by the same name.

I shall call it and share it with the world, right here. Not on github.

Killing all running processes for ledger and brave using
# finds all process ID's for the specified program running under your own user account and kills them
# in order to free up system resources.  Some programs have severe memory leaks and consume vast amount of RAM and 
# swap if left running over time.
# Usage: 
# Written by M. D. Bradley during Coronavirus pandemic, March 2020

memfree=`free | grep Mem | awk {'print $4'}`
echo "Program to kill e.g. xreader?: "
read program
pidcount=`ps -fu $user | grep $program | awk {'print$program'} | wc -l`
ps -fu $user | grep $program | awk {'print$2'} | while read eachpid; do 
	kill $eachpid >/dev/null 2>&1
memfree2=`free | grep Mem | awk {'print $4'}`
freedmem=$(( memfree2 - memfree ))
if [ $pidcount -eq 1 ] 
	echo "Found $pidcount process running for $program"
	echo "Killed it.  Freed up $freedmem bytes."
if [ $pidcount -gt 1 ] 
	echo "Found $pidcount processes running for $program"
	echo "Savaged them. Freed up $freedmem bytes."



Python is a simple, easy to learn programming language that bears some resemblance to shell script. It has gained popularity very quickly due to its shallow learning curve. It is supported on all operating systems.


Installers for all operating systems are available here and on linux it tends to be installed by default in most distributions. This is quickly and easily checked by using the python3 -V command.

You may find that the version installed in your distribution lags slightly behind the very latest available from If you want to install the very latest version, then you can either download the source code and compile it, or add the repository and install it using your package management system. Check the version you want isn’t already included in your package management system first using apt-cache search python3.8

INSTALLATION VIA SOURCE CODE (debian based distributions)

Ensure the pre-requisites are installed first from the distro’s default repo’s.

sudo apt-get install build-essential checkinstall

sudo apt-get install libreadline-gplv2-dev libncursesw5-dev libssl-dev libsqlite3-dev tk-dev libgdbm-dev libc6-dev libbz2-dev

Download the source code from here or use wget and unzip using tar -zxvf Python-3.8.2.tgz

Download the python source code from the command line using
sudo wget

Extract the archive using tar xzf Python-3.8.2.tgz
cd into Python-3.8.2 directory
sudo ./configure –enable-optimizations to create makefile
sudo make altinstall to install python without overwriting the version already installed in /usr/bin/python by your distro
Check python version with the python3.8 -V command


Before getting into coding in python, I’ll put this section in here just to satisfy your curiosity about how you actually execute a python script, since python ain’t shell script…

The simplest of all python scripts? The simple “hello world” script
Attempting to execute a python script like you would a shell script doesn’t end well. Python ain’t Shell after all.

The hint was in the use of the python3.8 -V command previously in order to check the version of python i.e. to execute your python script using python 3.8.2, you could use the command python3.8



Comment code or your own comments throughout your python code for readability by placing a # at the front of the line. The python interpreter will ignore any lines beginning with a hash symbol. Alternatively, use a triple quote, e.g. ”’ but hashes are the official method of commenting a line of code/notes.


hello world.

print(“hello world”) -prints the output hello world to the screen

country_name = “England” -create a variable country_name and assign string value of England

number_of_years = 2020 -create a variable number_of_years and assign numeric value of 2020

brexit_event = True -create a boolean variable with a true or false value

print(“hello ” + country_name + ” and welcome to the year ” + str(number_of_years) -Note that you can’t concatenate a string and an integer so you need to convert the integer to a string using the str() function

executing the script comprised of the three lines above

print (“Cyberfella Limited”\n”python tutorial”) -puts a new line between the two strings

print (“Cyberfella\\Limited”) -escape character permits the print of the backslash or other special character that would otherwise cause a syntax error such as a “

phrase = “CYBERFELLA”

print (phrase.lower()) -prints the string phrase in lowercase. There are other functions builtin besides upper and lower to change the case.

print (phrase.islower()) -returns False if the string phrase is not lower case

print (phrase.lower().islower()) -returns True after converting the uppercase string phrase to lowercase.

print (len(phrase)) -returns the length of the string, i.e. 10

print (phrase[0]) -returns the first letter of the string, i.e. C

print (phrase.index(“Y”)) -returns the location of the first matching parameter in the string i.e. 1 Note you can have a string as a parameter e.g. CYB

print (phrase.replace(“FELLA”,”FELLA LTD”)) -replaces matching part of the string (substring) FELLA with FELLA LTD


Python can do basic arithmetic as follows, print (2.5 + 3.2 * 5 / 2)

python performing arithmetic 2.5 + 3.2 * 5 / 2 = 10.5 based on the PEMDAS order of operations. The “operations” are addition, subtraction, multiplication, division, exponentiation, and grouping; the “order” of these operations states which operations take precedence (are taken care of) before which other operations. … Multiplication and Division (from left to right) Addition and Subtraction (from left to right)

To change the order of operations, place the higher priority arithmetic in parenthesis, e.g. print (2 * (3 + 2))

3+2 = 5 and 2 * 5 = 10. The addition is prioritised over the multiplication by placing the addition in () to be evaluated first.

print (10 % 3) is called the Modulus function, i.e. 10 mod 3. This will divide 10 by 3 and give the remainder, i.e. 10 / 3 = 3 remainder 1. So it outputs 1.

How to perform a MOD function, i.e. give the remainder when two numbers are divided. e.g. 10 % 3 (10 mod 3) = 1

The absolute value can be obtained using the abs function, e.g. print (abs(my_num))

The variable my_num had been assigned a value of -98

print (pow(3,2)) prints the outcome of 3 to the power of 2, i.e. 3 squared.

3 squared is 9

print (max(4,6)) prints the larger of the two numbers, i.e. 6 min does the opposite

6 is larger than 4

print (round(3.7)) rounds the number, i.e. 4

3.7 rounded is 4

There are many more math functions but they need to be imported from the external math module. This is done by including the line from math import * in your code

print (floor(3.7)) takes the 3 and chops off the 7 (rounds down) ceil does the opposite (rounds up)

The floor function imported from the math module, returns the whole number but not the fraction

print (sqrt(9)) returns the square root of a number, i.e. 3.

the square root of 9 is 3.0 according to pythons sqrt function


name = input (“Enter your name: “) will create a variable name and assign it the value entered by the user when prompted by the input command.

num1 = input (“Enter a number: “)

num2 = input (“Enter another number: “)

Any input from a user is treated as a string, so in order to perform arithmetic functions on it, you need to use int or float to tell python to convert the string to an integer or floating point number if it contains a decimal point.

result = int(num1) + int(num2) or result = float(num1) + float(num2)

print (result)


Multiple values are stored in square brackets, in quotes separated by commas,

friends = [“Eldred”, “Chris”, “Jules”, “Chris”]

You can store strings, numbers and booleans together in a list,

friend = [“Eldred”, 1, True]

Elements in the list start with an index of zero. So Chris would be index 1.


Note that print (friends[-1]) would return the value on the other end of the list and print (friends[1:]) will print the value at index 1 and everything after it. print (friends[1:3]) will return element at index 1 and everything after it, up to but not including element at index position 3.

To replace the values in a list,

friends[1] = “Benny” would replace Chris with Benny


lucky_numbers = [23, 8, 90, 44, 42, 7, 3]

To extend the list of friends with the values stored in lucky_numbers, effectively joining the two lists together,

friends.extend(lucky_numbers) Note that since Python3 you’d need to use friends.extend(str(lucky_numbers)) to convert the integers to strings before using functions such as sort or you’ll receive an error when attempting to sort a list that is a mix of integers and strings.

To simply add a value to the existing list


To insert a value into a specific index position,

friends.insert(1, “Sandeep”)

To remove a value from the list,


To clear a list, use friends.clear()

To remove the last element of the list, use friends.pop()

To see if a value exists in the list and to return its index value,

print (friends.index(“Julian”))

To count the number of similar elements in the list,

print (friends.count(“Chris”))

To sort a list into alphabetical order,


print (friends)

To sort a list of numbers in numerical order,


print (lucky_numbers)

To reverse a list, lucky_numbers.reverse()

Create a copy of a list with,

friends2 = friends.copy()

WORKING WITH TUPLES (pronounced tupples)

A tuple is a type of data structure that stores multiple values but has a few key differences to a list. A tuple is immutable. You can’t change it, erase elements, add elements or any of the above examples of ways you can manipulate a list. Once set, that’s it.

Create a tuple the same way you would a list, only using parenthesis instead of square brackets,

coordinates = (3, 4)

print (coordinates[0]) returns the first element in the tuple, just as it does in a list.

Generally, if python stores data for any reason whereby it doesn’t stand to get manipulated in any way, it’s stored in a tuple, not a list.


Just as with Shell Scripting, a function is a collection of code that can be called from within the script to execute a sequence of commands. function names should be in all lowercase and underscores are optional if you want to see a space in the function name for better readability, e.g. hello_world or helloworld are both acceptable.

def hello_world ():

print (“Hello World!”)

commands inside the function MUST be indented. To call the function from within the program, just use the name of the function followed by parenthesis, e.g.


You can pass in parameters to a function as follows,

def hello_user (name):

print (“Hello ” + name)

pass the name in from the program with hello_user(“Bob”)

def hello_age (name, age):

print (“Hello ” + name = ” you are ” + str(age))

hello_age (“Matt”, 45)


In the following example, we’ll create a function to cube a number and return a value

def cube (num);

return (num ^3)

Call it with print (cube(3)). Note that without the return statement, the function would return nothing despite performing the math as instructed.

result = cube(4)

print (result)

Note that in a function that has a return statement, you cannot place any more code after the return statement in that function.


Firstly, set a Boolean value to a variable,

is_male = True

If statement in python process the first line of code when the boolean value of the variable in the IF statement is True, i.e.

if is_male:

print (“You are a male”)

This would print “You are a male” to the screen, whereas if is_male = False, it’d do nothing.

if is_male:

print (“You are a male”)


print (“You are not a male”)

Now, what about an IF statement that checks multiple boolean variables? e.g.

is_male = True

is_tall = True

if is_male or is_tall:

print “You’re either male or tall or both”


print “You’re neither male nor tall”

an alternative to using or is to use and e.g.

if is_male and is_tall:

print “You are a tall male”


print “You’re either not male or not tall or both”

Finally, by using the elif statement(s) between the if and else statements, we can execute a command or commands in the event that is_male = True but is_tall is False, i.e.

if is_male and is_tall:

print “You are male and tall”

elif is_male and not(is_tall):

print “You are not a tall male”

elif not(is_male) and is_tall:

print “You are tall but not male”


print “You are neither male nor tall”


The following examples show how you might compare numbers or strings using a function containing if statements and comparison operators.

#Comparison Operators
#Function to return the biggest number of three numbers
def max_num(num1, num2, num3):
if num1 >= num2 and num1 >= num3:
return num1
elif num2 >= num1 and num2 >= num3:
return num2
return num3

print (max_num(3, 4, 5))

#Function to compare three strings
def match(str1, str2, str3):
if str1 == str2 and str1 == str3:
return "All strings match"
elif str1 == str2 and str1 != str3:
return "Only the first two match"
elif str1 != str2 and str2 == str3:
return "Only the second two match"
elif str1 == str3 and str1 != str2
return "Only the first and last match"
return "None of them match"

print (match("Bob", "Alice", "Bob"))

python also supports <> as well as != and can also compare strings and numbers e.g. ’12’ <> 12


This calculator will be able to perform all basic arithmetic, addition, subtraction, multiplication and division.

#A Calculator
num1 = float(input("Enter first number: "))
op = input("Enter operator: ")
num2 = float(input("Enter first number: "))

if op == "+":
print(num1 + num2)
elif op == "-":
print(num1 - num2)
elif op == "/":
print(num1 / num2)
elif op == "*":
print(num1 * num2)
print "Invalid operator"


Key and Value pairs can be stored in python dictionaries. To create a dictionary to store say, three letter months and full month names, you’d use the following structure. Note that in a dictionary the keys must be unique.

monthConversions = {
"Jan": "January",
"Feb": "February",
"Mar": "March",
"Apr": "April",
"May": "May",
"Jun": "June",
"Aug": "August",
"Sep": "September",
"Oct": "October",
"Nov": "November",
"Dec": "December",

To retrieve the value for a given key, use print(monthConversions[Sep]) or print(monthConversions.get(“Sep”) using the get function.

The get function also allows you to specify a default value in the event the key is not found in the dictionary, e.g.

print(monthConversions.get(“Bob”, “Key not in dictionary”)


The following example starts at 1 then loops until 10

i = 1
while i <= 10:
    i = i + 1)  #or use i += 1 to increment by 1
print ("Done with loop")

The while loop will execute the indented code while the condition remains True.


secret_word = "cyberfella"
guess = ""
tries = 0
limit = 3
out_of_guesses = False

while guess != secret_word and not out_of_guesses: #will loop code while conditions are True
if tries < limit:
guess = input("Enter guess: ")
tries += 1
out_of_guesses = True

if out_of_guesses:
#executes if condition/boolean variable is True
print ("Out of guesses, you lose!")
#executes if boolean condition is False
print ("You win")


Here are some examples of for loops

for eachletter in "Cyberfella Ltd":
    print (eachletter)

friends = ["Bob", "Alice", "Matt"]
for eachfriend in friends:

for index in range(10):
    print(index) #prints all numbers starting at 0 excluding 10

for index in range(3,10):
    print(index) #prints all numbers between 3 and 9 but not 10

for index in range (len(friends)):
    print(friends[index]) #prints out all friends at position 0, 1, 2 etc depending on the length of the list or tuple of friends

for index in range (5):
    if index == 0:
         print ("first iteration of loop")
         print ("not first iteration")


print (2**3) #prints 2 to the power of 3

Create a function called raise_to_power to take a number and multiply it by itself a number of times,

def raise_to_power(base_num, pow_num):
result = 1
for index in range (pow_num):
#carry on multiplying the number by itself until you hit the range limit specified by pow_num
result = result * base_num
return result


In python, you can store values in a table, or 2D list, and print the values from certain parts of the table depending on their row and column positions. note that positions start at zero, not 1.

#Create a grid of numbers, that is 4 rows and 3 columns
number_grid = [
#return the value from first row (row 0) first column (position 0)
print number_grid [0][0]
#returns 1

#return the value from third row (row 2) third column (position 2)
print number_grid [0][0]
#returns 9
for eachrow in number_grid:
print (row)

for eachrow in number_grid:
for column in eachrow:
print (column)
#returns the value of each column in each row until it hits the end


This little program is an example of nested if statements that take user input and translate any vowels in the string input to an upper or lowercase x

def translate(phrase):
translation = ""
for letter in phrase:
if letter.lower() in "aeiou":
if letter.isupper():
translation = translation + "X"
translation = translation + "x"
translation = translation + letter
return translation

print(translate(input("Enter a phrase: ")))


Catching errors in your program to prevent the program from being prevented from running. Error handling in python for example, if you prompt the user for numerical input and they provide alphanumerical input, the program would error and stop.

number = int(input(“Enter a number: “))

The variable number is set based upon the numerical, or more specifically the integer value of the users input. In order to handle all the potential pitfalls, we can create a “try except” block, whereby the code that could “go wrong” is indented after a try: and the code to execute in the event of an error, being indented after the except: block, e.g.

number = int(input("Enter a number: "))
print("Invalid input, that number's not an integer")

Specific error types can be caught by specifying the type of error after except. Using an editor like pycharm will display the possible options or errors that can be caught but the specific error will be in the output of the script with it stops.

So if we execute the code outside of a try: block, and enter a letter when asked for an integer, we’d get the following error output that we can then use to create our try: except: block to handle that specific ValueError error type in future.

You can add multiple except: blocks in a try: except: block of code.

If you want to capture a certain type of error and then just display that error, rather than a custom message or execute some alternative code then you can do this…

This can be useful during troubleshooting.


You can “open” a file in different modes, read “r”, write “w”, append “a”, read and write “r+”

employee_file = open(“employees.txt”, “r”) #Opens a file named employees.txt in read mode

It’s worth checking that the file can be read, print(employee_file.readable())

You need to close the file once you’re done with it,


The examples below show different ways you can read from a file

employee_file = open("employees.txt", "r") #opens file read mode
print(employee_file.readable()) #checks file is readable
print( #reads entire file to screen
print(employee_file.readline()) #can be used multiple times to read next line in file
print(employee_file.readlines()) #reads each line into a list
print(employee_file.readlines()[1]) #reads into a list and displays item at position 1 in the list
employee_file.close() #closes file

for employee in employee_file.readlines():
    print (employee)


You can append a a file by opening it in append mode, or overwrite/write a new file by opening it in write mode. You may need to add newline characters in append mode to avoid appending your new line onto the end of the existing last line.

employee_file = open("employees.txt", "a") #opens file append mode
employee_file.write("Toby - HR") #in append mode will append this onto the end of the last line, not after the last line
employee_file.write("\nToby - HR") #in append mode will add a newline char to the end of the last line, then write a new line

employee_file = open("employees.txt", "w") #opens file write mode
employee_file.write("Toby - HR") #in write mode, this will overwrite the file entirely



Besides the builtin modules in python, python comes with some additional modules that can be read in by your python code to increase the functionality available to you. This can reduce time since many things you may want to achieve have already been written in one of these modules. This is really what python is all about – the ability to pull in the modules you need, keep everything light and reduce time.


import useful_tools

feet_in_mile = 5280
metres_in_kilometer = 1000
beatles=["John", "Ringo", "Paul", "George"]
def get_file_ext(filename):
    return filename[filename.index(".") + 1:]
def roll_dice(num):
    return random.randint(1, num)

To use a module in an external file, use print(useful_tools.roll_dice(10)) for example (rolls a 10 sided dice).


Besides the additional internal modules that can be read into your python script, there are also many external modules maintained by a huge community of python programmers. Many of these external modules can be installed using the builtin pip command that comes as part of python. e.g. pip install python-docx will install the external python module that allows you to read and write to Microsoft Word documents.

You can install pip using your package manager

To uninstall a python modules, use pip uninstall python-docx for example.


A class defines a datatype. In the example, we create a datatype or class for a Student.

class Student:
def __init__(self, name, major, gpa, is_on_probation): = name
self.major = major
self.gpa = gpa
self.is_on_probation = is_on_probation

This can be saved in its own class file called and can be imported into your python script using the command from Student import Student i.e. from the Student file, I want to import the Student class.

To create an object that is an instance of a class, or in our case, a student that is an instance of the Student class, we can use student1 = Student(“Bob”, “IT”, 3.7, False)

print ( will print the name attribute of the student1 object.


If you’re using pycharm to create your python code, then Click File, New, Python File and create an external class named This will define the data type for the questions in your main multiple choice quiz code.

class Question:
def __init__(self, prompt, answer):
self.prompt = prompt
self.answer = answer

Now in your main code, read in that class, create some questions in a list called question_prompts, and define the answers to those questions in another list called questions, e.g.

from Question import Question

question_prompts = [
    "What colour are apples?\n(a) Red/Green\n(b) Purple\n(c) Orange\n\n",
    "What colour are Bananas\n(a) Teal\n(b) Magenta\n(c) Yellow\n\n",
    "What colour are Strawberries?\n(a) Yellow\n(b) Red\n(c) Blue\n\n"

questions = [
    Question(question_prompts[0], "a"),
    Question(question_prompts[1], "c"),
    Question(question_prompts[2], "b"),

Now create a function to ask the questions, e.g.

def run_test(questions):
score = 0
for question in questions:
answer = input(question.prompt)
if answer == question.answer:
score +=1
print("You got " + str(score) + "/" + str(len(questions)) + " correct")

and lastly, create one line of code in the main section that runs the test.

run_test (questions)


Consider the following scenario – a python class that defines a Student data type, i.e.

class Student:
def __init__(selfself, name, major, gpa): = name
self.major = major
self.gpa = gpa

and some code as follows,

from Student import Student

student1 = Student("Oscar", "Accounting", 3.1)
student2 = Student("Phyllis", "Business", 3.8)

An object function is a function that exists within a class. In this example, we’ll add a function that determines if the student is on the honours list, based upon their gpa being above 3.5

In the class, we’ll add a on_honours_list function

class Student:
    def __init__(self, name, major, gpa): = name
        self.major = major
        self.gpa = gpa

    def on_honours_list(self):
        if self.gpa >= 3.5:
            return True
            return False

and in our app, we’ll add a line of code to check if a particular student is on the honours list.

from Student import Student

student1 = Student("Oscar", "Accounting", 3.1)
student2 = Student("Phyllis", "Business", 3.8)



Classes can inherit the functions from other classes, this is done as follows. Consider a class that defines a Chef object, e.g.

class Chef:

def make_chicken(self):
print("The chef makes a chicken")

def make_salad(self):
print("The chef makes a salad")

def make_special_dish(self):
print("The chef makes bbq ribs")

Within the main app code, you can instruct the Chef as follows.

from Chef import Chef
myChef = Chef()

But what if there was a Chinese Chef who could do everything that the Chef could do, but also made additional dishes and a different special dish? Creating an additional class for the ChineseChef as follows would facilitate this. e.g. would contain…

from Chef import Chef
class ChineseChef(Chef):
def make_special_dish(self):
print ("The chef makes Orange Chicken")

def make_fried_rice(self):
print ("The chef makes fried rice")

So, the class imports the other class, then the skills unique to the Chinese Chef are added, and also, any of the same skills overridden by re-defining them within the ChineseChef class.


On Windows, Mac or Linux, you can access the python command line interpreter to perform some quick and dirty tests of your commands, Note that python is very particular about it’s tab indented code where applicable – something that was done in say Shell Scripting at the discretion of the programmer for ease of readability – python really enforces it. e.g.

Using the python command will likely open an interpreter for python v2.x whereas the python3 command will open the interpreter for python v3.x. Be sure to add the path to the PATH environment variable if using Windows.

For coding in python, it’s best to use a good text editor, Notepad++ (notepadqq on linux), or a proper coding text editor such as Visual Studio Code (runs on linux as well as Windows and Mac) or Atom or the best dedicated to writing python in particular is PyCharm. The community edition is free, or there is a paid for, Professional Edition.

I found PyCharm be be available via my Software Manager on Linux Mint.


What is DevOps?

DevOps is the key to Continuous Delivery. How is this achieved? First it is useful to consider the evolution of the previous models of project management, namely Waterfall and Agile.


Agile addressed the gap between client requirements and development, but a disconnect remained between the developers and the operations teams, i.e. applications were being developed on different systems to the ones they would ultimately be deployed upon with the assumption that the production infrastrcuture was bigger and more powerful than the development laptop so it would all be fine.

Client + Requirements <—> Developers + Testers <- X -> Operations + Infrastructure


DevOps is a logical evolution of the Agile shift and addresses the link between developers and operations so that continuous delivery and continuous integration can be achieved along with the promise of fast product to market times and quicker return of value to the client. This utopia is further realised since much infrastructure is now hosted in the cloud and is in itself code (infrastructure as code). This doesn’t so much bring the operations and dev teams closer together as blur the divide between them, since they now use many common tools.

Client + Requirements <—> Developers + Testers <—> Operations + Infrastructure

It also facilitates a feedback loop rather than a left-to-right delivery paradigm.

The figure of 8 diagram above shows the sequence of phases in a DevOps environment that facilitate continuous delivery, continuous integration and continous deployment. More on what that means below… First lets have a quick look at each of the phases shown in the diagram, starting with the Planning Phase.

It’s worth noting at this point that many open-source tools are used in each stage of the DevOps process. We’ll cover some of the more commonly used tools as we go along.

It is also worth noting that many of these tools are designed to automate the functions of a build engineer, tester or operator.


To sit down with business teams and understand their goals. Tools used in this phase are Subversion and IntelliJIDEA.


Programmers design code using git to carefully control versioning and branches of code that may be a collaborative effort, ultimately merging the branches into a new build. More on the elementary use of git here. Code may be shell script, python, powershell or any other language and git can maintain version control of developers local repositories of code and the projects main private and public repositories held online at github that collaborating devs keep in sync with.


Build tools such as Maven and Gradle take code from different repositories and combine them to build the complete application.


Testing of code is automated using tools such as Selenium, JUnit to ensure software quality. The testing environment is scripted just as the build environment is.


Jenkins integrates new features once testing is complete, to the already existing codebase. Another tool used in the integration phase is Bamboo.


BMC XebiaLabs can be used to package the application after Jenkins release and is deployed from the Developement Server to the Production Server.


Operations elements such as Servers, VM’s and Containers are deployed using tools such as Puppet, Chef and their configuration managed and maintained using tools such as Ansible and Docker. Like the application hosted on the platform, these tools are used to execute code in the cloud and that code can be maintained using git etc just the same as application code for a consistent, self-healing deployment where the scale of the application may require many identically configured elements to host an application that could also be subjected to attacks.


Monitoring frameworks such as Nagios are used to schedule scripted checks of parts of the solution and the consequences of the results collated by Groundwork and/or Splunk>. A nagios monitoring script should exit with a status of 0, 1 or 2 (OK, Error, Warning) and may be displayed on a board for operators to see, but may also feed back into the development cycle automatically.

So, all these tools, all this code and the utopia of entirely automated, cloud infrastructure is often described as Continuous Integration/ Continuous Delivery/Continous Deployment or “CI/CD” for short. Lets make the distinction between the three…


This is effectively the outcome of the PLAN, CODE, BUILD and TEST phases.



This is effectively the outcome of the CD phases above plus the outcome of the RELEASE phase, i.e.




whereby the outcome of the RELEASE phase (defect or success) is fed back into the Continuous Delivery phases above or moved into the DEPLOY, OPERATE and MONITOR phases or “Continuous Deployment” phases respectively, i.e.


success” outcome from CI –> DEPLOY <–> OPERATE <–> MONITOR

So in summary, the terms Continuous Delivery, Continous Integration and Continuous Deployment is simply a collective term for multiple phases of the DevOps cycle…


Waterfall projects can take weeks, months or years before the first deployment of a working product, only to find bugs when released into the wild on a much larger user base than the developers and testing teams. This is an extremely stressful time if you’re the dev tasked with finding and fixing the root cause of the bugs in the days after go-live, especially when the production system is separate in every sense of the word from the developers working environment, not to mention the potential for poor public image, poor customer PR and spiralling costs after heavy upfront costs.


Agile projects use kanban boards to monitor tasks in the Pending, Active, Complete and Resolved columns. Agreed Sprints lasting 2 weeks or 4 weeks (sprint cadence) ultimately resulting in a new release, drives value back to the customer in a guaranteed schedule, with outstanding tasks and bugs still being worked on during the next sprint.


DevOps in comparison, heavily leverages automation and a diverse toolset to bring the sprint cadence down to days or even a daily release.



As an example, Netflix accounts for a third of all network traffic on the internet, yet it’s DevOps team is just 70 people.

The time taken to create and deliver software is greatly reduced.

The complexity of maintaining an application is reduced via automation and scripting.

Teams aren’t silo’d according to discrete skill sets. They work cohesively at various phases in the loop, their roles assigned during daily scrums.

Value is delivered more readily to the customer and up-front costs reduced.


git Cheat Sheet

My super concise git notes

Developed by Linus Torvalds, git is a…

  1. Distributed Version Control System (VCS) for any type of file
  2. Co-ordinates work between multiple developers
  3. Tracks who made what changes and when
  4. Revert back at any time
  5. Supports local and remote repositories (hosted on github, bitbucket)

It keeps track of code history and takes snapshots of your files
You decide when to take a snapshot by making a commit
You can visit any snapshot at any time
You can stage files before committing

sudo apt-get install git (debian)
sudo yum install git (red hat) (installers for mac and windows)
gitbash is a linux-like command cli for windows

git config –global ‘matt bradley’
git config –global ‘’
touch .gitignore
echo “log.txt” >> .gitignore
Add file to be ignored by git, e.g. log file generated by script
echo “/log” >> .gitignore Add directory to be ignored, e.g. log directory

BASIC COMMANDS (local repository)
git init Initialize a local git repository (creates a hidden .git subdirectory in the directory)
git add Adds file(s) to Index and Staging area ready for commit.
git add . Adds all files in directory to Staging area
git status check status of working tree, show files in Staging area and any untracked files you still need to add
git commit commit changes in index – takes files in staging are and puts them in local repository
git commit -m ‘my comment’ Skips git editing stage adding comment from command.
git rm –cached removes from staging area (untracked/unstaged).

BASIC COMMANDS (remote repo)
git push push files to remote repository
git pull pull latest version from remote repo
git clone clone repo into a local directory

git clone clones my cyberfella repository

git –version shows version of git installed

git branch loginarea creates a branch from master called “loginarea”
git checkout loginarea switches to the “loginarea” branch
git checkout master switches back to the master branch version
git merge ‘loginarea’ merges changes made to ‘loginarea’ files in loginarea branch to master branch

Create a public or private repository
Shows the commands required to create a new repository on the command line or push an existing repository from the command line
A (markdown format) file displays nicely in github.


This is my app

Basically it should look like this in github


This is my app


atom is a very nice, simple text editor for programmers that supports integration with git.


Create Windows 10 bootable USB on Linux

The following commands install the WoeUSB program used to create a bootable USB stick for the installation of Windows 10.

First add the repository (assuming Ubuntu or Linux Mint OS)

sudo add-apt-repository ppa:nilarimogard/webupd8

sudo apt-get update

sudo apt-get install woeusb

The WoeUSB GUI can be found in your Applications Menu but I don’t recommend it. The likelihood is, you’ll run into the problem described here

Using gparted, create a NTFS partition on your USB stick – you may need to install ntfs-tools from your repository to do this.

Create the USB stick using the following command

sudo umount /dev/sdb1

sudo woesub –target-filesystem NTFS –device Win10_1809Oct_EnglishInternational_x64.iso /dev/sdb

Download the Windows 10 ISO from Microsoft here


Make bootable USB from .iso in Linux

The following command will write a downloaded .iso file of your favourite distro to a USB stick.  You can then boot off it and install to hardware.

sudo dd bs=4M if=./manjaro-xfce-18.0-stable-x86_64.iso of=/dev/sdb status=progress

Note that in my example, there was no partition on the usb stick to start with.  I’d removed it using gparted (not necessary though).Facebooktwitterredditpinterestlinkedinmail


One of my first ever posts was about conky and wbar on crunchbang linux.

Crunchbang has since been replaced with a community led fork, Bunsenlabs, and it’s well worth checking out.  I’m so impressed with it that it’s my laptop OS of choice, giving me very little grief installing onto my disappointingly-not-particularly-linux-friendly Dell XPS 15, unlike other popular distros.  Suffice to say, Bunsenlabs has saved my XPS15 from the financial damage limitation exercise known as ebay.

In any case, I thought I’d include a link to my own .conkyrc file.  It’s simple and neat, nothing too fancy.

The download file is called conkyrc.  Once downloaded, just rename it to .conkyrc i.e. put the dot in front (hidden file and the conky default), and copy it to your home directory, remembering to back up any existing .conkyrc file already in your home directory first.

If you want to edit yours to make it your own, the man page for conky is very good, but I find this better.Facebooktwitterredditpinterestlinkedinmail

Linux disk space consumption analysis.

Desktop distro’s have wonderful graphical disk space analysis programs such as Baobab (KDirStat), QDirStat, xdiskusage, duc, JDiskReport and with your desktop distro being connected to the internet, even if you dont already have them installed, installing them from your repositories is easy.   You can quickly drill down using these treemapper programs and find the culprit for filling your disk up.

In the datacentre, things are never so easy.  You have no internet access, and no local repository configured, and even if you did, you have no change control to install it on a live system, and even if you did, no GUI to view it. All you have is a production problem, a stressed out ops manager and a flashing cursor winking at you -oh and native tools.

Sure, you can use the find command to go looking for files over a certain size,

find ./ -type f -size +1000000M -exec ls -al {} \;

removing a zero and re-running as required until it starts finding something, but you’ll fight with the find command syntax for 15 minutes trying to get it to work, only to be unconvinced of the results.  As good as find is, it’s not exactly easy trying to put together a command that does something that should be simple.

Here is a much simpler solution.  Just use du.  In particular…

du -h –max-depth=1

This will summarize the size of the top level sub-directories underneath your present working directory.  You then cd in to the biggest one, run it again and repeat until you basically end up digging down and arriving at the largest file on disk – in my case a 32GB mysql database in /var/lib/mysql/zabbix.

So there you go.  Have a play with it and you’ll see what I mean.  It’s my favourite way of finding out what’s eating all my disk space.

Using QDIRSTAT on headless servers

We live in strange times, where despite the best efforts of the likes of Edward Snowden to open our eyes to the fact that we’re being monitored at any and every opportunity by the intelligence community, we’re still hell bent on moving our enterprise computing into huge corporate cloud data centres that the CIA and NSA have back doors into. If you think “That’s OK, I have nothing to hide.” then great. How ’bout you hand me your phone and let me go and have a good look around it? Oh, that’s not OK? Well make your mind up, will you? You think you’re gonna be as successful as Google and Amazon if you use their cloud services? Whose cloud service do you think they use? That’s right, their own. So your Cloud is their On Prem. I know, I’m such a cynic.

For those who are tasked with monitoring disk space consumption on their cloud servers, containers, headless stuff, you can use a neat little qdirstat cache file writer to generate a cache file that you can then open in qdirstat on your workstation for analysis.

I’ve summarised its use below, assuming you’ll understand what each command is doing.

ssh myserver
sudo cd /usr/local/bin
sudo wget
sudo chmod +x qdirstat-cache-writer
sudo qdirstat-cache-writer / ~/myserver-root.cache.gz
scp "root@myserver:~/*.cache.gz" ~/
sudo chmod 777 ~/*.cache.gz
sudo apt-get install qdirstat
qdirstat --cache ~/myserver-root.cache.gz

I’d like to issue a special thanks to Mike Schlegel in the comments section below for dragging me kicking and screaming into the 21st Century. I guess there’s still some of us out there who are clever enough to be working with Linux but stupid enough that we didn’t buy Bitcoin at 10$ back in 2012 when I started this blog.


Stopping and Disabling Services in Linux

Things are a little different between Centos/RHEL6 and Centos/RHEL7 when it comes to starting and stopping services.

Having grown up on /etc/init.d/ scripts, it’s enough of a challenge using service blah stop instead of /etc/init.d/blah stop, but I guess service blah stop was added to Centos/RHEL6 to simplify things.

And then systemd comes alone they go and change it.  Way to go in terms of keeping things simple – even though it does bring some consistency across redhat and debian based distros going forward tbf…

Now it feels like every time I try to do something as simple as start and stop a service on a redhat based distro, Sod’s Law kicks in and I always get the command wrong, making me feel like a total noob, despite having rocked the command line for over 20 years.

As you can probably gather, I’m not a fan of the landscape changing (which is what drove me away from Windowz and into Linux in the first place – the longevity of the marketable skills set was better).  In my defence, Linus Torvalds isn’t that happy about it either.

Hence this little post.  A quick reminder on which command to use.  Now I’ve written it, I won’t need it of course.  Funny how the brain works, eh?

chkconfig | grep zabbix – lists all services in all runlevels
chkconfig zabbix-agent off – toggle it on/off at startup
service zabbix-agent stop   -stop the service

systemctl status zabbix-agent.service
systemctl disable zabbix-agent
systemctl stop zabbix-agent.service


Retro Terminal

This is just too good.