Skip to main content

Cloud Resources for Python Application Development

  • AWS:

- AWS Lambda:

  - Serverless computing for executing backend code in response to events.

- Amazon RDS:

  - Managed relational database service for handling SQL databases.

- Amazon S3:

  - Object storage for scalable and secure storage of data.

- AWS API Gateway:

  - Service to create, publish, and manage APIs, facilitating API integration.

- AWS Step Functions:

  - Coordination of multiple AWS services into serverless workflows.

- Amazon DynamoDB:

  - NoSQL database for building high-performance applications.

- AWS CloudFormation:

  - Infrastructure as Code (IaC) service for defining and deploying AWS infrastructure.

- AWS Elastic Beanstalk:

  - Platform-as-a-Service (PaaS) for deploying and managing applications.

- AWS SDK for Python (Boto3):

  - Official AWS SDK for Python to interact with AWS services programmatically.


  • Azure:

- Azure Functions:

  - Serverless computing for building and deploying event-driven functions.

- Azure SQL Database:

  - Fully managed relational database service for SQL databases.

- Azure Blob Storage:

  - Object storage service for scalable and secure storage.

- Azure API Management:

  - Full lifecycle API management to create, publish, and consume APIs.

- Azure Logic Apps:

  - Visual workflow automation to integrate with various services.

- Azure Cosmos DB:

  - Globally distributed, multi-model database service for highly responsive applications.

- Azure Resource Manager (ARM):

  - IaC service for defining and deploying Azure infrastructure.

- Azure App Service:

  - PaaS offering for building, deploying, and scaling web apps.

- Azure SDK for Python (azure-sdk-for-python):

  - Official Azure SDK for Python to interact with Azure services programmatically.


  • Cloud Networking, API Gateway, Load Balancer, and Security for AWS and Azure:


AWS:

- Amazon VPC (Virtual Private Cloud):

  - Enables you to launch AWS resources into a virtual network, providing control over the network configuration.

- AWS Direct Connect:

  - Dedicated network connection from on-premises to AWS, ensuring reliable and secure data transfer.

- Amazon API Gateway:

  - Fully managed service for creating, publishing, and securing APIs.

- AWS Elastic Load Balancer (ELB):

  - Distributes incoming application traffic across multiple targets to ensure high availability.

- AWS WAF (Web Application Firewall):

  - Protects web applications from common web exploits by filtering and monitoring HTTP traffic.

- AWS Shield:

  - Managed Distributed Denial of Service (DDoS) protection service for safeguarding applications running on AWS.

- Amazon Inspector:

  - Automated security assessment service for applications running on AWS.


Azure:


- Azure Virtual Network:

  - Connects Azure resources to each other and to on-premises networks, providing isolation and customization.

- Azure ExpressRoute:

  - Dedicated private connection from on-premises to Azure, ensuring predictable and secure data transfer.

- Azure API Management:

  - Full lifecycle API management with features for security, scalability, and analytics.

- Azure Load Balancer:

  - Distributes network traffic across multiple servers to ensure application availability.

- Azure Application Gateway:

  - Web traffic load balancer that enables you to manage traffic to your web applications.

- Azure Firewall:

  - Managed, cloud-based network security service to protect your Azure Virtual Network resources.

- Azure Security Center:

  - Unified security management system that strengthens the security posture of your data centers.

- Azure DDoS Protection:

  - Safeguards against DDoS attacks on Azure applications.

 

Comments

Popular posts from this blog

Financial Engineering

Financial Engineering: Key Concepts Financial engineering is a multidisciplinary field that combines financial theory, mathematics, and computer science to design and develop innovative financial products and solutions. Here's an in-depth look at the key concepts you mentioned: 1. Statistical Analysis Statistical analysis is a crucial component of financial engineering. It involves using statistical techniques to analyze and interpret financial data, such as: Hypothesis testing : to validate assumptions about financial data Regression analysis : to model relationships between variables Time series analysis : to forecast future values based on historical data Probability distributions : to model and analyze risk Statistical analysis helps financial engineers to identify trends, patterns, and correlations in financial data, which informs decision-making and risk management. 2. Machine Learning Machine learning is a subset of artificial intelligence that involves training algorithms t...

Wholesale Customer Solution with Magento Commerce

The client want to have a shop where regular customers to be able to see products with their retail price, while Wholesale partners to see the prices with ? discount. The extra condition: retail and wholesale prices hasn’t mathematical dependency. So, a product could be $100 for retail and $50 for whole sale and another one could be $60 retail and $50 wholesale. And of course retail users should not be able to see wholesale prices at all. Basically, I will explain what I did step-by-step, but in order to understand what I mean, you should be familiar with the basics of Magento. 1. Creating two magento websites, stores and views (Magento meaning of website of course) It’s done from from System->Manage Stores. The result is: Website | Store | View ———————————————— Retail->Retail->Default Wholesale->Wholesale->Default Both sites using the same category/product tree 2. Setting the price scope in System->Configuration->Catalog->Catalog->Price set drop-down to...

How to Prepare for AI Driven Career

  Introduction We are all living in our "ChatGPT moment" now. It happened when I asked ChatGPT to plan a 10-day holiday in rural India. Within seconds, I had a detailed list of activities and places to explore. The speed and usefulness of the response left me stunned, and I realized instantly that life would never be the same again. ChatGPT felt like a bombshell—years of hype about Artificial Intelligence had finally materialized into something tangible and accessible. Suddenly, AI wasn’t just theoretical; it was writing limericks, crafting decent marketing content, and even generating code. The world is still adjusting to this rapid shift. We’re in the middle of a technological revolution—one so fast and transformative that it’s hard to fully comprehend. This revolution brings both exciting opportunities and inevitable challenges. On the one hand, AI is enabling remarkable breakthroughs. It can detect anomalies in MRI scans that even seasoned doctors might miss. It can trans...