Solution:

Open Azure DevOps project portal --> Project settings --> Service connections (under Pipelines category) --> New service connection --> Azure Resource Manager Service connection

Enter the details

 Enter Azure credential

Note: Operators in the same row are evaluate left to right except ** (Exponentiation) which is right to left binding

Requirement:
To format the below numbers
From
1
2
3
...
To
1,2,3,...

Solution:

• Press Ctrl+H
• Select Search mode Extended(\n, \r, \t, \o, \x...)
• Enter Find what: \r\n
• Enter Replace with: ,
• Replace_All

output:

Install commands:

Generic update:
sudo apt update

mySQL client install:
sudo apt install mysql-client

** mySQL login command **
mysql -h <RDS endpoint> -u <user name> -p <password>

apache server install:
sudo apt install apache2

python essentials install:
sudo apt install python3

** Refer here for pip install **

sudo apt-get purge python-pip
wget https://bootstrap.pypa.io/get-pip.py
sudo python get-pip.py

sudo apt install python-pip
sudo pip install mysql-connector-python
sudo pip install pymysql

sudo pip install boto3

** Boto3 is the Amazon Web Services (AWS) Software Development Kit (SDK) for Python, which allows Python developers to write software that makes use of services like Amazon S3 and Amazon EC2. You can find the latest, most up to date, documentation at our doc site, including a list of services that are supported. **

Exception:

File "/usr/bin/pip", line 9, in <module> from pip import main ImportError: cannot import name main

Explanation:

The exception appears after installing python-pip in the environment. looks like, the get-pip.py script from github is outdated which may be the reason for the exception.

Quick Fix:

Reinstalling python-pip from https://bootstrap.pypa.io website fixed the exception.

sudo apt-get purge python-pip
wget https://bootstrap.pypa.io/get-pip.py
sudo python get-pip.py

Explanation:

Fan-out is a messaging pattern where messages are broadcast in a one-to-many arrangement.One of the very common architectural patterns is fan-out where an event is sent to multiple subscribers by a broker. An event can be like placing an order, which can then be handled by inventory service, record-keeping, as well as shipping service concurrently. These events can also be very frequent - like clickstreams, or search strings on a website. AWS allows for fan-out architecture with SNS topics, and SQS queues. SQS queue(s) can subscribe to SNS topics and receive any message sent to the SNS topic(s)

* SNS - Amazon Simple Notification Service (SNS) is a highly available, durable, secure, fully managed pub/sub messaging service that enables you to decouple microservices, distributed systems, and serverless applications. Additionally, SNS can be used to fan out notifications to end users using mobile push, SMS, and email.

* SQS - Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications.

Explanation:

Python object serialization and deserialization is an important aspect of any non-trivial program. If in Python you save something to a file, if you read a configuration file, or if you respond to an HTTP request, you do object serialization and deserialization.

Serialization refers to the translation of object state into bytes to send it over the network or store it in hard disk. We need serialization because the hard disk or network infrastructure are hardware component and we cannot send objects because it understands just bytes and not objects

Pickling and Unpickling in Python.

Pickling in python refers to the process of serializing objects into binary streams, while unpickling is the inverse of that. It’s called that because of the pickle module in Python which implements the methods to do this.Pickling is useful when you want to save the state of your objects and reuse them at another time without losing any instance specific data. If you are using large files, CPickle is recommended. CPickle is implemented in C, making it much faster.

Amazon CloudFront is a web service that speeds up distribution of your static and dynamic web content, such as .html, .css, .js, and image files, to your users. CloudFront delivers your content through a worldwide network of data centers called edge locations.

Elastic Load Balancing automatically distributes incoming application traffic across multiple Amazon EC2 instances. It enables you to achieve greater levels of fault tolerance in your applications, seamlessly providing the required amount of load balancing capacity needed to distribute application traffic.

Amazon Route 53 effectively connects user requests to infrastructure running inAWS – such as Amazon EC2 instances, Elastic Load Balancing load balancers, or Amazon S3 buckets – and can also be used to route users to infrastructure outside of AWS.

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Explanation:

Blue-green deployment is a technique that reduces downtime and risk by running two identical production environments called Blue and Green.

At any time, only one of the environments is live, with the live environment serving all production traffic. For this example, Blue is currently live and Green is idle.

As you prepare a new version of your software, deployment and the final stage of testing takes place in the environment that is not live: in this example, Green. Once you have deployed and fully tested the software in Green, you switch the router so all incoming requests now go to Green instead of Blue. Green is now live, and Blue is idle.

This technique can eliminate downtime due to app deployment. In addition, blue-green deployment reduces risk: if something unexpected happens with your new version on Green, you can immediately roll back to the last version by switching back to Blue.