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Category: Design

  • Microservices Design Patterns

    Microservices Design Patterns Microservices are a popular architectural style for building scalable and maintainable applications. They involve breaking down a monolithic application into a collection of small, independent services that communicate over a network. Designing a robust microservices architecture requires careful consideration of various patterns to address common challenges. 1. Decomposition Patterns: Decompose by Business… Read more

  • Multi-Threaded Programming in Java

    Multi-Threaded Programming in Java (2025) Java has robust built-in support for multi-threaded programming, allowing developers to execute multiple parts of a program concurrently. This is crucial for building responsive, scalable, and efficient applications that can leverage multi-core processors effectively in 2025. Understanding Threads in Java Threads: In Java, a thread is a lightweight sub-process, a… Read more

  • Caching in Multi-Cloud Applications

    Caching in Multi-Cloud Applications Caching is a crucial technique for improving the performance and scalability of applications, especially in distributed environments like multi-cloud deployments in 2025. By storing frequently accessed data closer to the point of use, caching reduces latency, decreases network traffic, and lowers the load on underlying data stores. Benefits of Caching in… Read more

  • Building Agentic AI applications Using n8n

    Building Agentic AI Using n8n n8n, a powerful open-source workflow automation platform, can be effectively leveraged to build various components and orchestrate the functionalities of agentic AI systems in 2025. While n8n itself isn’t a machine learning framework for training AI models, its ability to connect different services, handle data transformations, and manage complex workflows… Read more

  • Leveraging Data Lakehouse for Agentic AI

    Leveraging Data Lakehouse for Agentic AI In 2025, the data lakehouse architecture is proving to be a powerful foundation for developing and deploying sophisticated agentic AI systems. Agentic AI, characterized by its autonomy, proactivity, reasoning capabilities, and ability to interact with the environment, requires a robust and versatile data infrastructure. The data lakehouse, which combines… Read more

  • Making Money with AI Tech

    Making Money with AI Tech (2025) There are numerous ways to leverage AI technology to generate income in 2025. Here are some prominent methods and ideas: 1. AI-Powered Content Creation and Editing AI Writing Tools: Utilize AI writing assistants like Jasper AI or Writesonic to generate various forms of content. Offer writing services or create… Read more

  • Top 50 Websites in AI Technology (April 2025)

    Top 50 Websites in AI Technology (April 2025) The field of Artificial Intelligence is vast and rapidly expanding. Here is an extended list of 50 prominent websites covering various aspects of AI technology, including news, research, tools, education, and communities, as of April 2025: OpenAI (openai.com) Organization behind ChatGPT, DALL-E, and leading AI research. Google… Read more

  • The Cost Implications of Monolithic Architectures

    Whether a monolithic architecture is a cost saver is a nuanced question with no definitive yes or no answer. It largely depends on the specific context, the size and complexity of the application, the development team’s expertise, and the application’s long-term evolution. Potential Initial Cost Savings of Monoliths: Potential Long-Term Cost Increases of Monoliths: Conclusion:… Read more

  • Building Agentic AI Applications on Microsoft Azure

    Microsoft Azure offers a rich set of services and tools for building agentic AI applications – intelligent systems capable of autonomous action, planning, memory, and interaction with their environment. This detailed guide outlines key Azure services, their functionalities, and relevant links to help you get started, formatted for your WordPress site. Core Foundation Models Agent… Read more

  • Building Agentic AI Applications on AWS: Detailed Tools and Resources

    Amazon Web Services (AWS) provides a robust and evolving ecosystem for building sophisticated agentic AI applications. These intelligent systems can operate autonomously, plan actions, retain memory, and interact with their environment to achieve specific goals. This detailed guide outlines key AWS services, their functionalities, and relevant links to help you get started, formatted for your… Read more

  • GPU vs. XPU vs. CPU: A Comparative Analysis

    In the world of computing, the terms CPU (Central Processing Unit) and GPU (Graphics Processing Unit) are commonly understood. However, the term XPU is emerging, representing a broader category of processing units. This analysis compares these three types of processors. 1. Central Processing Unit (CPU) The CPU is the brain of the computer, responsible for… Read more

  • Developing Aptitude and Skills for an AI-Focused Tech Career

    A career in Artificial Intelligence is dynamic and rewarding, but requires a specific blend of aptitude and learned skills. This guide outlines key areas to focus on to develop the necessary foundation for success in the AI-driven tech landscape. 1. Strengthen Your Foundational Aptitude While skills can be learned, certain inherent aptitudes can significantly accelerate… Read more

  • Top 21 Spring Boot Interview Questions and Answers

    Spring Boot has become the de-facto standard for building modern, production-ready Java applications quickly and easily. Preparing for a Spring Boot interview requires a solid understanding of its core concepts and features. Here are 21 important interview questions with detailed answers to help you ace your interview: 1. What is Spring Boot? Answer: Spring Boot… Read more

  • Autonomous Scientific Research Assistant using Agentic AI

    Let’s explore another agentic AI use case, this time focusing on a different domain: Autonomous Scientific Research Assistant. Use Case: A research laboratory wants to accelerate the pace of scientific discovery by automating certain aspects of the research process. Instead of researchers spending significant time on literature reviews, hypothesis generation, experimental design, and data analysis,… Read more

  • Building a Personalized Banking Chat Agent with React.js, RAG, LLM, and Redis with sample code

    Here we outline a more detailed structure with conceptual sample code snippets for each layer of a conceptual personalized bank FAQ chat agent. Keep in mind that this is a simplified illustration, and a production-ready system would involve more robust error handling, security measures, and integration logic. I. Knowledge Base Preparation: Step 1: Data Collection… Read more

  • The Monolith to Microservices Journey: Empowered by AI

    The transition from a monolithic application architecture to a microservices architecture, offers significant advantages. However, it can also be a complex and resource-intensive undertaking. The integration of Artificial Intelligence (AI) and Machine Learning (ML) offers powerful tools and techniques to streamline, automate, and optimize various stages of this journey, making it more efficient, less risky,… Read more

  • The Monolith to Microservices Journey: A Phased Approach to Architectural Evolution

    The transition from a monolithic application architecture to a microservices architecture is a significant undertaking, often driven by the desire for increased agility, scalability, resilience, and maintainability. A monolith, with its tightly coupled components, can become a bottleneck to innovation and growth. Microservices, on the other hand, offer a decentralized approach where independent services communicate… Read more

  • Navigating the Currents of Change: A Comprehensive Guide to Application Modernization

    In today’s rapidly evolving digital landscape, businesses face a constant imperative to adapt and innovate. At the heart of this transformation lies the need to modernize their core software applications. These applications, often the backbone of operations, can become impediments to growth and agility if left to stagnate. Application modernization is not merely about updating… Read more

  • Data Lake vs. Data Lakehouse: Understanding Modern Data Architectures

    Organizations today grapple with ever-increasing volumes and varieties of data. To effectively store, manage, and analyze this data, different architectural approaches have emerged. Two prominent concepts in this landscape are the data lake and the data lakehouse. While both aim to provide a centralized data repository, they differ significantly in their design principles and capabilities.… Read more

  • Spring AI and Langchain Comparison

    A Comparative Look for AI Application DevelopmentThe landscape of building applications powered by Large Language Models (LLMs) is rapidly evolving. Two prominent frameworks that have emerged to simplify this process are Spring AI and Langchain. While both aim to make LLM integration more accessible to developers, they approach the problem from different ecosystems and with… Read more

  • gRPC vs HTTP

    gRPC (gRPC Remote Procedure Calls) and HTTP (Hypertext Transfer Protocol) are both fundamental protocols used for communication between applications, but they differ significantly in their design, features, and typical use cases. Here’s a comprehensive comparison: gRPC HTTP Key Differences Summarized: Feature gRPC HTTP Protocol RPC framework over HTTP/2 Application protocol (various versions) Data Format Primarily… Read more

  • Databricks scalability

    Databricks is designed with scalability as a core tenet, allowing users to handle massive amounts of data and complex analytical workloads. Its scalability stems from several key architectural components and features: 1. Apache Spark as the Underlying Engine: 2. Decoupled Storage and Compute: 3. Elastic Compute Clusters: 4. Auto Scaling: 5. Serverless Options: 6. Optimized… Read more