Modernizing Legacy Systems & Building New Ones with AI, Cloud & Mobile

Modern Tech Architecture provides practical, expert‑driven insights for organizations upgrading legacy systems and building modern digital platforms. Through deep experience in AI integration, cloud architecture, API‑led modernization, enterprise solutions, and mobile system design, this blog delivers proven strategies to reduce technical risk, accelerate transformation, improve system reliability, and support long‑term scalability. Whether you’re exploring cloud migration, AI adoption, application modernization, or enterprise integration, you’ll find actionable guidance to help you architect systems built for the future.


LATEST POSTS


  • An Architect’s Take: Azure Cloud Architecture Done Right (and All the Ways Teams Get It Wrong)

    An Architect’s Take: Azure Cloud Architecture Done Right (and All the Ways Teams Get It Wrong)

    Most cloud architectures fail not because Azure is too complex, but because teams treat the cloud like a hosting provider instead of a platform. After a decade of building distributed systems, the pattern is impossible to miss: teams over‑engineer Kubernetes clusters they can’t maintain, sprinkle services everywhere without governance, and then blame Azure for their…

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  • Modernizing Your Website with Generative AI: A Practical Guide Using Google Cloud

    Modernizing Your Website with Generative AI: A Practical Guide Using Google Cloud

    In today’s digital landscape, a website serves as a crucial element throughout the customer journey, necessitating modernization through Generative AI (Gen AI) for enhanced user experiences. This blog outlines how to upgrade websites using Google Cloud’s Gen AI tools like Vertex AI Search, Agent Builder, and BigQuery. Key transformation areas include streamlining content generation for…

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  • BigQuery Data Types: STRUCT vs JSON Performance Insights

    BigQuery Data Types: STRUCT vs JSON Performance Insights

    As data architectures evolve to handle increasingly complex and semi-structured data, choosing the right data type in BigQuery becomes critical. Two popular options for nested or hierarchical data are the STRUCT and JSON data types. While both serve similar purposes, they differ significantly in performance, flexibility, and use cases.  In this post, we’ll explore the…

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  • BigQuery JSON vs STRUCT: Schema Flexibility Explained

    BigQuery JSON vs STRUCT: Schema Flexibility Explained

    In designing the data schema for a project on Google Cloud Platform (GCP), we need to make a choice. We must decide between using the BigQuery JSON data type and the STRUCT data type. These types are for storing semi-structured or nested data. This decision impacts data ingestion, transformation, querying flexibility, and downstream integration. Advantages…

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  • Mastering the BizTalk Technical Interview

    Mastering the BizTalk Technical Interview

    200 BizTalk Technical Questions with Answers Introduction General Not being prepared is preparing to Failure! Ironic but true. Interviewing is just like any other skill that you have acquired; the more that you practice it the better you will get at it. The art of interviewing is as important as other skills that you bring…

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  • Key Architectural Concerns for AWS App Development – (3 – WeightMan.ca)

    Key Architectural Concerns for AWS App Development – (3 – WeightMan.ca)

    In this series of posts, I will go through the architectural concerns when building a new application. I will also discuss design and development considerations. This series will focus specifically on the AWS Platform. In earlier posts (Blogs) we decided the App we would design and build is for public consumers. It would be built…

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