Multi Availability Zone Auto Scaling Group Deployment with ALB | Tech Arkit

To deploy an Auto Scaling Group (ASG) in AWS with multi-AZ support, you need to follow these steps:

Create a Launch Configuration: A Launch Configuration specifies the AMI (Amazon Machine Image), instance type, security groups, and other configuration details for the instances in your ASG.

Configure Auto Scaling Group: An Auto Scaling Group manages the lifecycle of your instances. It ensures that the desired number of instances are running, replaces unhealthy instances, and scales the group based on defined policies. During the ASG configuration, specify the minimum, desired, and maximum number of instances you want to maintain.

Configure Network Load Balancer: To achieve multi-AZ support, you need to set up a Network Load Balancer (NLB). The NLB distributes incoming traffic across multiple Availability Zones (AZs) to ensure high availability. Configure the NLB to forward traffic to the instances in your ASG.

Configure Scaling Policies: You can define scaling policies for your ASG to automatically scale the number of instances based on various metrics such as CPU utilization, network traffic, or application-level metrics. Configure the scaling policies according to your application's requirements.

Set up Health Checks: Configure health checks to monitor the instances in your ASG. Auto Scaling uses these health checks to determine the health status of instances and replace any unhealthy instances with new ones.

Test and Monitor: Before deploying your application in production, it is crucial to thoroughly test and monitor the ASG. Verify that instances are being launched in multiple AZs, the load balancer is distributing traffic correctly, and scaling policies are working as expected.

Deploy Application: Once your ASG is set up and tested, you can deploy your application onto the instances. You can use various deployment strategies such as blue-green deployments or rolling deployments, depending on your requirements.

Python Comparison Operators | Non-Programmers | Tech Arkit

## Equality (==): Checks if two values are equal. 

## Strings are case sensitive Ravi == Ravi (True) however Ravi == ravi (False).

x = 5

y = 7

print(x == y)  # False

name1 = "Ravi"

name2 = "Ravi"

print(name1 == name2)  # True

## Inequality (!=): Checks if two values are not equal.

a = 10

b = 15

print(a != b)  # True

age1 = 25

age2 = 30

print(age1 != age2)  # True

## Greater than (>): Checks if the left operand is greater than the right operand.

m = 5

n = 3

print(m > n)  # True

score1 = 85

score2 = 90

print(score1 > score2)  # False

## Less than (<): Checks if the left operand is less than the right operand.

p = 7

q = 10

print(p < q)  # True

temperature1 = 25

temperature2 = 30

print(temperature1 < temperature2)  # True

## Greater than or equal to (>=): Checks if the left operand is greater than or equal to the right operand.

c = 5

d = 5

print(c >= d)  # True

marks1 = 80

marks2 = 90

print(marks1 >= marks2)  # False

### Less than or equal to (<=): Checks if the left operand is less than or equal to the right operand.

e = 10

f = 15

print(e <= f)  # True

quantity1 = 5

quantity2 = 5

print(quantity1 <= quantity2)  # True

Python for Non-Programming Background Video 1 | Tech Arkit

Python is a powerful and versatile programming language that is widely used in various fields such as web development, data analysis, artificial intelligence, and automation. If you're new to programming or have no prior programming experience, Python is a great language to start with because of its simplicity and readability.

Here are some basic concepts and resources to help you get started with Python as a non-programmer:

Installation: First, you need to install Python on your computer. Visit the official Python website (python.org) and download the latest version compatible with your operating system. Follow the installation instructions provided.

Python interpreter: Once Python is installed, you can access the Python interpreter, which allows you to interactively run Python code and see the results immediately. You can launch the interpreter by opening the command prompt or terminal and typing "python" or "python3" depending on your installation.

Variables and Data Types: Python uses variables to store and manipulate data. You can assign values to variables and perform operations on them. Python has various built-in data types such as integers, floats, strings, lists, tuples, and dictionaries.

Basic Syntax: Python code is written using a clean and readable syntax. Indentation is crucial in Python and is used to define code blocks. Statements are typically terminated by a newline, and you can use comments to add explanations or notes to your code.

Control Flow: Python provides constructs for controlling the flow of execution in your program. This includes if-else statements for conditional execution, loops (such as for and while loops) for repetition, and logical operators like "and," "or," and "not."

Functions: Functions allow you to group code into reusable blocks and perform specific tasks. You can define your own functions and call them whenever needed. Python also comes with a rich set of built-in functions that you can use.

Libraries and Modules: Python has a vast ecosystem of libraries and modules that extend its capabilities. These libraries provide additional functionality for tasks such as scientific computing (NumPy), data analysis (Pandas), web development (Django), and machine learning (scikit-learn).

Learning Resources: There are numerous resources available to help you learn Python as a non-programmer. Some recommended resources include:

"Python Crash Course" by Eric Matthes: A beginner-friendly book that covers Python fundamentals and projects.

Codecademy: An online learning platform that offers interactive Python courses for beginners.

Python.org: The official Python website provides comprehensive documentation and tutorials.

YouTube tutorials: There are many Python tutorials available on YouTube that cater to beginners.

Remember, practice is key when learning to program. Start with small coding exercises and gradually work on more complex projects. Don't be afraid to make mistakes, as they are part of the learning process. With time and effort, you'll become comfortable with Python and be able to tackle a wide range of programming tasks.