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Step-by-Step Guide to Creating an AWS RDS Database Instance

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 Amazon Relational Database Service (AWS RDS) makes it easy to set up, operate, and scale a relational database in the cloud. Instead of managing servers, patching OS, and handling backups manually, AWS RDS takes care of the heavy lifting so you can focus on building applications and data pipelines. In this blog, we’ll walk through how to create an AWS RDS instance , key configuration choices, and best practices you should follow in real-world projects. What is AWS RDS? AWS RDS is a managed database service that supports popular relational engines such as: Amazon Aurora (MySQL / PostgreSQL compatible) MySQL PostgreSQL MariaDB Oracle SQL Server With RDS, AWS manages: Database provisioning Automated backups Software patching High availability (Multi-AZ) Monitoring and scaling Prerequisites Before creating an RDS instance, make sure you have: An active AWS account Proper IAM permissions (RDS, EC2, VPC) A basic understanding of: ...
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How to Access Dictionary Key-Value Data in Python

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Use for-loop to read dictionary data in python. Here's an example of reading dictionary data. It's helpful to use in real projects.


Sample Program to Read Dictionary


Python program to read dictionary data

yearly_revenue = {

   2017 : 1000000,

   2018 : 1200000,

   2019 : 1250000,

   2020 : 1100000,

   2021 : 1300000,

 }

total_income = 0

for year_id in yearly_revenue.keys():

  total_income+=yearly_revenue[year_id]

  print(year_id, yearly_revenue[year_id])


print(total_income)

print(total_income/len(yearly_revenue))


Output


2017 1000000

2018 1200000

2019 1250000

2020 1100000

2021 1300000

5850000

1170000.0



** Process exited - Return Code: 0 **

Press Enter to exit the terminal


Explanation

The input is dictionary data. The total revenue sums up for each year. Notably, the critical point is using the dictionary keys method.


References

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