Application Modernization: A complete guide

Scenario: Migrating 50 servers (20 middleware, 10 application A, 20 application B, and 5 DB) from APAC to EMEA and North America. This move is driven by the need to consolidate infrastructure, reduce latency, and improve service delivery to customers in these regions.
Traditional Approach (Time Consuming): Creating new setups and installing MQ in new locations. This involves manual configuration, potential inconsistencies, and significant downtime.
Modernization Focus:
- Replicating setups with automation and infrastructure-as-code to ensure consistency and reduce manual effort.
- Migrating applications using modern tools and techniques to minimize downtime and ensure data integrity.
- Deploying applications faster through CI/CD pipelines and automated testing.
- Modernizing applications with microservices to improve scalability, resilience, and maintainability. This includes breaking down monolithic applications into smaller, independent services.
- Building new application versions using cloud-native technologies and DevOps practices.

Application Types: Java, Python, .NET, COBOL. Each application type requires a specific modernization approach.
COBOL Modernization:
- Modernizing COBOL applications to .NET or other languages to leverage modern frameworks and improve maintainability.
- Changing COBOL to Python for increased flexibility and access to a wider range of libraries and tools.
- Segregating functions to create reusable components and improve code organization.
- Identifying main functions for calling as APIs to enable integration with other applications.
- Processing functions/datasets/global variables to ensure compatibility with new languages and platforms.
- Integrating languages to create hybrid applications that combine the strengths of different technologies.
C/CPP Modernization:
- Changing C code with CPP integration to improve code structure and add object-oriented capabilities.
- Modernizing with Python or Java for better portability and access to modern development tools.
- Framework selection based on application requirements and performance considerations.
- Security considerations for integration to protect against vulnerabilities and ensure data privacy.

Understanding application functionality to identify modernization opportunities and ensure successful migration.
Application segregation techniques to break down monolithic applications into smaller, manageable components.

Application modernization projects can yield significant income (e.g., $10,000$ , which is equivalent to 840,000 in some currency). This reflects the high demand for skilled professionals in this field.

Understanding business requirements and models to align modernization efforts with business goals.
Aligning with new models and Google setups (Google IO services) to leverage cloud technologies and improve business agility.
Attending business events to shape skills and stay updated with industry trends.

Deploying applications in virtual missions to gain hands-on experience with different modernization technologies.
Learning IAB (likely referring to a framework or standard) to ensure compliance and best practices.
Data analysis using Power BI to gain insights into application performance and identify areas for improvement.
Procuring and analyzing data from sources like Flipkart to understand user behavior and optimize application features.

Analyzing Netflix raw data to identify underutilized content and optimize content delivery.
Reporting underperforming movies to improve content curation and reduce costs.
Potential earnings by identifying and reporting such movies (e.g., $15$ reward). This incentivizes users to contribute to data analysis efforts.
Netflix actions: Issuing red notices to producers, removing movies, or selling them to optimize content portfolio.

Participating in bug bounty programs (e.g., Microsoft) to identify and report security vulnerabilities.
Earning rewards through programs and redeeming vouchers, providing financial incentives for security research.

Earning Flipkart/Amazon vouchers using Microsoft Copilot and Bing on Edge. This is a user engagement strategy to promote Edge usage.
Purpose: Promoting Edge usage over Chrome by offering tangible rewards.
Rewards for consistent Edge usage to encourage long-term adoption.
Potential rewards: 500 Rupees Flipkart voucher, free PUBG game. These rewards are tailored to specific user interests.
Rewards vary by location (e.g., travel kits in Japan) to cater to regional preferences.

Microsoft's strategy to increase Edge market share by offering rewards and integrating AI-powered features.

Looking for application examples with request/response on Github and Kafka (probably for queue processing) to understand real-world implementations and best practices.