News Aggregator

A Pulse on Generative AI Today: Navigating the Landscape of Innovation and Challenges

Aggregated on: 2025-03-21 11:28:11

Editor's Note: The following is an article written for and published in DZone's 2025 Trend Report, Generative AI: The Democratization of Intelligent Systems. Generative AI (GenAI) has become a transformative force, redefining how machines generate, retrieve, and process information across industries. This article explores its rapid evolution, highlighting key breakthroughs, industry applications, and emerging trends. From the rise of large language models (LLMs) and retrieval-augmented generation (RAG) to the growing role of agentic AI, the analysis delves into innovations driving AI's transformation and the challenges shaping its responsible adoption. Early breakthroughs like GPT-3 and DALL-E paved the way for GPT-4o, Claude 3.5, and Gemini Ultra, enabling real-time memory-augmented reasoning and cross-modal capabilities. Figure 1 shares the key developments across the timeline.

Serverless Kubernetes: The Rise of Zero-Management Container Orchestration

Aggregated on: 2025-03-20 21:43:11

I still remember the day our CTO walked into the engineering huddle and declared, "We're moving everything to Kubernetes." It was 2017, and like many teams caught in the container hype cycle, we dove in headfirst with more excitement than wisdom. What followed was a sobering 18-month journey of steep learning curves, 3 AM incident calls, and the gradual realization that we'd traded one set of operational headaches for another. Fast forward to today, I'm deploying containerized applications without managing a single node. No upgrades. No capacity planning. No security patching. Yet, I still have the full power of Kubernetes' declarative API at my fingertips. The serverless Kubernetes revolution is here, and it's changing everything about how we approach container orchestration.

[Part-1] Text to Action: Build a Smart Calendar AI Assistant

Aggregated on: 2025-03-20 21:13:11

Welcome to the “Text to Action” series, where we build intelligent systems that transform natural language into real-world actionable outcomes using AI. To understand the concept better, let’s start simple by building a Smart Calendar AI Assistant. Soon, we’ll tackle more complex challenges — from smart home control to document automation — as we master the art of turning words into actions.

Grounding Gemini With Google Search and Other Data Sources

Aggregated on: 2025-03-20 20:43:11

When you only have a few data sources (e.g., PDFs, JSON) that are required in your generative AI application, building RAG might not be worth the time and effort. In this article, I'll show how you can use Google Gemini to retrieve context from three data sources. I'll also show how you can combine the context and ground results using Google search. This enables the end user to combine real-time information from Google Search with their internal data sources.

Multimodal AI: Beyond Single Modalities

Aggregated on: 2025-03-20 19:58:11

Artificial intelligence (AI) has progressed significantly from the time of unimodal systems to the more advanced multimodal systems, incorporating information from many different sources. Although unimodal AI has done a good job-solving problems such as language processing or image recognition, issues related to more complex situations in the real world will always comprise a larger data type than one. Since more than one data type must often interplay for a proper conclusion, multimodal AI has come up to the front. It blends text, visual, and audio types of data to provide richer insights with contextual awareness.

Mistakes That Django Developers Make and How To Avoid Them

Aggregated on: 2025-03-20 19:13:11

There is no doubt that Python is one of the most popular programming languages. Furthermore, it offers frameworks like Django and Flask. But Django is the most famous among Python developers as it helps them with a rapid development process and pragmatic design. For example, the Object Relational Mapping tool (ORM), routing, and templating features make things easier for developers. But despite these powerful features, there are many mistakes, such as bad application structure and incorrect resource placement, as well as writing fat views and skinny models, etc. These types of problems are not just faced by newbie Python developers, but they are also difficult ones for experienced Python developers as well.

Migrating from React Router v5 to v6: A Comprehensive Guide

Aggregated on: 2025-03-20 18:43:11

React Router remains a foundational library for routing in React applications, facilitating navigation between different components and handling URL changes elegantly. With the release of React Router v6, several significant changes have been introduced that improve the library’s performance, flexibility, and developer experience.

Build Multimodal RAG Apps With Amazon Bedrock and OpenSearch

Aggregated on: 2025-03-20 18:43:11

Scenario Customer support tickets with screenshots, technical documentation with diagrams, and a mountain of legacy PDFs — all containing valuable information, but impossible to query efficiently. "There has to be a better way," I thought. That's when I dove headfirst into the world of multimodal retrieval-augmented generation (RAG).

Playwright Fixtures vs POM: Which One Should You Choose?

Aggregated on: 2025-03-20 17:28:11

Playwright fixtures and traditional Page Object Models (POM) are both used in test automation, but they serve different purposes and can be integrated for better results. Playwright fixtures help set up and manage test environments, while POM organizes page interactions. In Playwright, you can use fixtures to handle POM instances, making tests cleaner and more maintainable.

Patch Management in the Age of IoT: Challenges and Solutions

Aggregated on: 2025-03-20 14:58:11

In a closely connected world, the Internet of Things (IoT) is already a familiar brand for people. However, the use of such many devices is likely to increase the risk of attack. This is why good patch management is so important. It implies the execution of a set of procedures for acquiring, installing, and supporting operating systems and other software. In this blog, the issues and opportunities concerning patch management in the IoT are considered. It is illustrated how such a possibility of patch management can minimize risks.

Tackling Multidomain Integration in Software Development

Aggregated on: 2025-03-20 13:43:11

Multidomain integration is becoming a cornerstone of modern software development, bridging technologies like blockchain, biotech, and consumer applications. These cross-domain projects are no longer optional — they are the future of innovation. However, combining such diverse systems presents unique challenges. Let me share practical strategies to help you approach cross-domain integration with confidence. In this article, I will explore the technical hurdles of multidomain integration using the example of blockchain and biotech and uncover actionable insights to ensure your projects succeed in this demanding landscape.

Personalized Product Recommendations in E-Commerce Using ML

Aggregated on: 2025-03-20 11:28:11

As a multidisciplinary field, data mining focuses on uncovering hidden patterns within data sets, with machine learning serving as a key approach in this exploration. Machine learning, a branch of data science, is devoted to creating algorithms that can learn from data and make accurate predictions. The growth of e-commerce has led to an overwhelming amount of information for users, often making it difficult to locate content that matches their preferences. To address this challenge, a system has been developed that uses user’s purchase histories to recommend similar food products, taking into account their daily health conditions. Machine learning algorithms, such as Support Vector Machine (SVM) and Random Forest, were utilized and compared in this context. The analysis revealed that SVM outperforms Random Forest in terms of effectiveness, highlighting its superior performance for this application.

Memory Management in Couchbase’s Query Service

Aggregated on: 2025-03-19 22:58:11

In Couchbase, memory management in the Query Service is key to keeping the service efficient and responsive, especially as the service handles an increasing number of queries simultaneously. Without proper memory management, things can go awry — greedy queries can hog memory, and the combined memory usage of multiple concurrent queries can overwhelm the service, leading to degraded performance. Fortunately, the Query Service has several features that allow users to manage the memory usage of queries and the overall service.

Serverless Sign-In Solution Based on Next.js on CloudFare

Aggregated on: 2025-03-19 22:13:11

If you would like to run your own solution without any costs and get familiar with serverless architecture, I'd encourage you to look at CloudFare. Recently, I tried to assemble all the pieces together to make the Next.js application authorization work on Cloudflare and faced a lot of issues. Provided examples on the official site and demos on other sources were working only partially. After some digging and combining the pieces together, it finally started working.

AI-Powered Observability With OpenTelemetry and Prometheus

Aggregated on: 2025-03-19 18:13:11

When it comes to customer satisfaction, providing excellent service isn’t optional anymore — it’s essential for success. With this, traditional monitoring tools are struggling to keep up as IT systems grow more complex with microservices, dynamic setups, and distributed networks. At the next level, the concept of observability is introduced, whereby people become aware of it as a solution. Besides, as AI technology advances and artificial intelligence is introduced, the public no longer sees observability merely as a measure of root cause analysis but also as an issue prediction, system optimization, and the overall keeping of the business the best.

Building an Agentic RAG System from Scratch

Aggregated on: 2025-03-19 17:13:10

In this post, we’ll explore the concept of Agentic RAG, its architecture, and why this powerful combination is reshaping the future of AI systems. Plus, we’ll walk through implementing a basic version of an Agentic RAG system from scratch! What Is RAG and Agentic RAG? To start, let's clarify what RAG is. Retrieval-augmented generation (RAG) is a technique that enhances LLMs by connecting them to external data sources, enabling more accurate and reliable responses. With RAG, the system first retrieves relevant information from a database and then uses it to generate an answer.

Stream Gatherers: Intro to Intermediate Operations Modeler

Aggregated on: 2025-03-19 16:28:10

Java is a programming language with many language features, specifications, and APIs. Even among experienced Java developers, being aware of all of these is quite rare. If a study were conducted, we might come across Java developers who have never worked with Threads, never used JPA, or never developed custom annotations. However, is there a Java developer who has worked with Java 8 or later but has never used the Stream API? I highly doubt it. Gatherers is a powerful extension of the Stream API that introduces support for customized intermediate operations. Initially introduced as a preview feature in JDK 22, it became a standard feature in JDK 24.

OpenAI vs Ollama Using LangChain's SQLDatabaseToolkit

Aggregated on: 2025-03-19 15:58:10

Disclaimer The stock data used in this article is entirely fictitious. It is purely for demo purposes. Please do not use this data for making any financial decisions. In a previous article, we saw the benefits of using Ollama locally for a RAG application. In this article, we'll extend our evaluation of Ollama by testing natural language (NL) queries against a database system, using LangChain's SQLDatabaseToolkit. SQL will serve as the baseline system for comparison as we explore the quality of results provided by OpenAI and Ollama.

Designing and Maintaining Event-Driven Architectures

Aggregated on: 2025-03-19 15:13:10

Event-driven architecture (EDA) gives your system the ability to receive and respond to changes in real time, making it easier to scale. Decoupling components is the core theme of EDA, which makes it flexible, allowing it to scale asynchronously based on events. This approach makes systems reactive, scalable, and resilient to failures. Designing and maintaining, like any other large-scale framework, requires deep thinking and constant monitoring. Understanding EDA At its core, EDA is primarily about reacting to events. A moment that signals a significant change, such as a user signing up or a sensor detecting temperature changes. Events are generated by producers, routed by intermediaries like message brokers or event buses, and consumed by services that act on them. This design keeps the components independent of each other, making the system easier to scale and maintain.

Unlocking Oracle 23 AI's JSON Relational Duality

Aggregated on: 2025-03-19 14:43:11

Oracle 23ai's JSON Relational Duality bridges the gap between JSON and relational data, which allows seamless querying and updating of data in both formats. This feature allows developers to efficiently manage hybrid data models, simplify application workflows, and reduce data transformation overhead. It also allows them to query and update data in JSON and relational formats seamlessly, simplifying data handling for modern applications.

AI-Driven Kubernetes Troubleshooting With DeepSeek and k8sgpt

Aggregated on: 2025-03-19 12:13:10

Kubernetes Site Reliability Engineers (SREs) frequently encounter complex scenarios demanding swift and effective troubleshooting to maintain the stability and reliability of clusters. Traditional debugging methods, including manual inspection of logs, event streams, configurations, and system metrics, can be painstakingly slow and prone to human error, particularly under pressure. This manual approach often leads to extended downtimes, delayed issue resolution, and increased operational overhead, significantly impacting both the user experience and organizational productivity.

Comparing DuckDB, Snowflake, and Databricks

Aggregated on: 2025-03-19 11:13:10

The exponential growth of data in recent years has improved how businesses operate and make decisions. From small start-ups to large enterprises, organizations across industries are leveraging data to gain competitive advantages, optimize operations, and drive innovation. However, with this data surge comes the challenge of efficiently storing, processing, and retrieving vast amounts of information. While traditional solutions like SQLite and MySQL have their place, modern data platforms like DuckDB, Snowflake, and Databricks are reshaping the landscape of data processing.

Building a Distributed Multi-Language Data Science System

Aggregated on: 2025-03-18 22:28:10

How can we, software developers of the 2020s, stay competitive in the world of automation? Would LLM-based code-generating AI (GAI), like OpenAI services, take over our jobs? Would template-based code generators/software robots (TSR), like UiPath, Blue Prism, Strapi, etc., make developers irrelevant? The short answer is no! We should embrace automation whenever reasonable and focus on "business valuable" hard-to-automate skills. To be specific, consider a common distributed microservice information system (IS) in Fig. 1. There are domain microservices, data science (DS)/operations research (OR) microservices, and a composer service to aggregate data from the microservices (See Appendix A for the terminology).

Dynamically Scaling Containers With KEDA and IBM App Connect

Aggregated on: 2025-03-18 20:43:10

Planning for highly variable workloads has always been a difficult art, with the attendant risks of over-provisioning (leading to waste) or under-provisioning (leading to poor performance) of computing resources, but container-based solutions can handle the challenge in ways that would have been difficult in a static VM world. To address this in some common cases, KEDA (Kubernetes Event-Driven Autoscaling) provides a way to automatically scale containers based on metrics such as IBM MQ queue depths, allowing scaling up as needed and then down to zero when the load dies away.

Financial Data and RAG Usage in LLMs

Aggregated on: 2025-03-18 20:43:10

The importance of integrating artificial intelligence in finance stems from its ability to process vast amounts of data at unprecedented speeds, enabling financial institutions to make more informed decisions and improve operational efficiencies. To understand what AI brings to the table, let's first delve into the basics of AI as per recent trends. Let's start with the basic use case the language models were designed to solve and predict the next word in a sequence based on probability learned from trained data. This training grew to a scale of processing billions of parameters using massive datasets. There comes the true potential realization of the models, allowing models to capture more complex relations in language.

Role of Data Annotation Services in AI-Powered Manufacturing

Aggregated on: 2025-03-18 18:13:10

Before diving deep into how AI/ML is a boon for manufacturers, let’s explore how the industry has evolved. Steam and water-powered mechanics disrupted manual processes, thus filling the demand versus supply gap. The introduction of assembly lines followed, allowing manufacturers to increase output while reducing product prices. Partial automation further empowered the manufacturers with mass production capability. Finally, the next big breakthrough came with AI and ML, adding intelligence to the automation formula. In other words, AI is at the forefront of industrial revolution 4.0. Not only this, but a strategic combination of AI with new-age technologies such as cloud computing, IoT, robotics, etc., spearheads the manufacturing industry to new heights, making the processes more accurate, efficient, and scalable.

Frugal AI: How Efficiency is Reshaping the Future of Tech

Aggregated on: 2025-03-18 17:43:10

As the energy and climate footprint of digital technologies keeps accelerating, frugal AI emerges as an alternative that seeks to reconcile innovation with environmental responsibility. What is this approach? Can it truly establish itself against current ultra-powerful yet energy-intensive models? What are the challenges and opportunities associated with its adoption? Let's break it down. At a global scale, digital technology today accounts for nearly 4% of greenhouse gas emissions, a figure that is steadily increasing, with an annual growth rate of 6%. This footprint is now comparable to that of the civil aviation sector. Around the world, digital energy consumption is following an exponential trajectory. But how can we balance technological innovation with environmental responsibility? And could frugal AI be a viable solution?

Bridging Cloud and On-Premises Log Processing

Aggregated on: 2025-03-18 16:43:10

Modern cloud-native architectures require robust, scalable, and secure log processing solutions to monitor distributed applications. This study presents a hybrid solution for log collection, aggregation, and analysis using Azure Kubernetes Service (AKS) for log generation, Fluent Bit for log collection, Azure EventHub for intermediary aggregation, and Splunk deployed on an on-premises Apache CloudStack cluster for comprehensive log indexing and visualization. We detail the system’s design, implementation, and evaluation, demonstrating how this architecture supports reliable and scalable log processing for cloud-native workloads while retaining control over data on-premises.

Exploring Playwright’s Feature “Copy Prompt”

Aggregated on: 2025-03-18 14:28:10

Web automation testing demands both efficient processes and precise outcomes. Microsoft developed Playwright as an open-source framework, which gained recognition for its powerful browser automation across Chromium, Firefox, and WebKit. Playwright consistently releases new features through ongoing updates that optimize workflows for both developers and testers. The new “Copy prompt” feature introduced in version 1.51 enhances debugging processes through the capabilities of large language models (LLMs). This blog will explain this feature’s functionality and workings before demonstrating its practical application through an example.

Bringing Security to Digital Product Design

Aggregated on: 2025-03-18 13:58:10

One of the biggest problems in digital product development today is the failure to collaborate with InfoSec or DevSecOps teams. Unfortunately, threats are ubiquitous and increasingly sophisticated. But did you know that there is a way to reduce the time spent remediating security issues by up to 50%? In 2016, the State of DevOps Report published its research indicating that high-performing teams spent less than half the time fixing security issues compared to low-performing teams. And the solution to this is to move left.

SAP HANA Triggers: Enhancing Database Logic and Automation

Aggregated on: 2025-03-18 12:13:10

SAP HANA is a powerful in-memory database platform that offers advanced features to manage and analyze data efficiently. Among these features, triggers play a crucial role in automating database operations and enforcing business logic at the database level. In this article, we will discuss SAP HANA triggers, their types, and practical use cases to demonstrate how they can be leveraged effectively.

Secure File Transfer as a Critical Component for AI Success

Aggregated on: 2025-03-18 11:43:10

Secure file transfer (SFT) has become one of the most crucial technologies in the modern Information technology (IT) landscape for ensuring data security and confidentiality. SFT is a hot topic in today’s world, especially when decisions are being made based on data. It is used to transfer data between systems in a secure manner to avoid the tempering of data or loss of data integrity. SFT helps in keeping track of data for audit trial purposes to ensure accountability and support compliance. This is even more so for AI projects, which rely on such data to be timely transferred, stored, and processed safely and accurately.

Navigating Innovations and Challenges of Conversational AI

Aggregated on: 2025-03-17 21:13:10

Large language models (LLMs) are sophisticated AI models with the ability to understand, generate, and process natural language. They employ deep neural networks, more precisely transformer models, which enable them to perform many language tasks like answering questions and text generation, language translation, and summarization of content. Conversational AI is a type of artificial intelligence that is committed to facilitating natural human-to-human-like dialogue through voice or text-based interfaces. It works on the principles of natural language processing and machine learning technologies and has been further enhanced by the development of LLMs.

Building Security into the Feature During the Design Phase

Aggregated on: 2025-03-17 20:13:10

It is exciting how different disciplines can be merged to make the processes more efficient. In 2009, DevOps was coined to address the friction between the Development and Operations teams. As a result, the industry moved towards clubbing both teams together so that the development team was responsible for the entire cycle, from writing code to production deployment. Of course, who would better understand intricacies than the people who developed them? After this shift, we have seen features being shipped rapidly and the time to market for new features coming down rapidly. DevOps also served as the foundation for many other practices like MLOps, DataOps, GitOps, and undoubtedly many more have emerged.

The Agile Prompt Engineering Framework

Aggregated on: 2025-03-17 19:28:10

TL; DR: Bridging Agile and AI With Proper Prompt Engineering Agile teams have always sought ways to work smarter without compromising their principles. Many have begun experimenting with new technologies, frameworks, or practices to enhance their way of working. Still, they often struggle to get relevant, actionable results that address their specific challenges. Regarding generative AI, there is a better way for agile practitioners than reinventing the wheel team by team — the Agile Prompt Engineering Framework. Learn why it solves the challenge: a structured approach to prompting AI models designed specifically for agile practitioners who want to leverage this technology as a powerful ally in their journey.

Migrating From SQLite to MySQL

Aggregated on: 2025-03-17 18:28:10

Introducing SQLite SQLite is a kind of open-source RDBMS that is distinguished from most other database management systems built on a client-server model since it is a server-less embedded database. This means that the SQLite database runs within the software that accesses the data, eliminating the need for a separate server. Due to such architecture, SQLite is a highly reliable, efficient system that works perfectly in low-memory environments. One of the major benefits of SQLite is its cross-platform compatibility, allowing it to run on various modern OS. As an RDBMS contained within a C library, SQLite can be utilized by applications written in any programming language that can connect to external libraries written in C. For example, it is ideal for developing embedded software in digital devices, such as mobile phones, game consoles, cameras, and set-top boxes. Additionally, SQLite can serve as a temporary dataset for applications to process data.

All About GPU Threads, Warps, and Wavefronts

Aggregated on: 2025-03-17 17:13:09

On a GPU, the threads are always run as a group of threads called warps. In that sense, the granularity of thread execution is always 32 (or 64, as explained later) on GPU. If a user requests for one thread, that one thread in the warp acts as an active thread while the rest of the threads are inactive. It is not conventional to request a single thread in GPU programming. The threads inside the warp run in parallel (and not concurrent) and execute the instructions in a SIMD (Single Instruction Multiple Data) fashion.

Attribute-Level Governance Using Apache Iceberg Tables

Aggregated on: 2025-03-17 16:28:10

Large organizations where the number of users accessing crucial data is pretty high have to face a lot of challenges in managing fine-grained access. A variety of AWS services like IAM, Lake Formation, and S3 ACL can help in fine-grained access control. But there are scenarios where a single entity containing the global data needs to be accessed by multiple user groups across the system with restrictive access. Also, organizations with a global presence might be working in different environments and with different toolsets, so data movement and cataloging become very tedious.

Best Practices for Data Warehouses in Microsoft Fabric

Aggregated on: 2025-03-17 15:28:09

To succeed, companies must transform raw data into actionable insights that support their operational growth. Users maintain separate tools for data lakes, ETL pipelines, and analytical tasks under traditional data warehousing, which results in complex conditions. Users can operate every aspect of their data analytics work via one platform when they use Microsoft Fabric for ingestion, storage, transformation, and analysis. Overview of Microsoft Fabric Data Warehouse Microsoft Fabric combines data lake and warehouse functions into one simplified analytics platform. The platform integrates data engineering with data warehouse, data science, real-time analytics, and Power BI into a single operational space.

Top Terraform and OpenTofu Tools to Use in 2025

Aggregated on: 2025-03-17 14:28:09

Infrastructure-as-Code (IaC) has become a trusted approach for managing and provisioning infrastructure. As the field evolves, the number of IaC tools continues to grow, with frequent updates, new features, and improvements being introduced. One of the most popular tools in this space is Terraform, a leader in the IaC ecosystem. There is a wide range of smaller tools that work alongside Terraform, adding extra features and making it even more powerful.

Rebalancing Agile: Bringing People Back into Focus

Aggregated on: 2025-03-17 13:43:09

Agile methodologies were introduced to enhance collaboration, foster continuous improvement, and promote the growth of both software and people. The intent was to create a framework that not only improved delivery but also empowered teams to innovate, learn, and contribute beyond their immediate tasks. However, what started as a noble idea has, in many cases, devolved into a system focused purely on delivery. Teams are increasingly confined to ticking checkboxes in user stories, following rigid processes, and participating in endless meetings, leaving little room for creativity, autonomy, or professional growth.

Leveraging LLMs for Software Testing

Aggregated on: 2025-03-17 12:13:09

As software systems become more complex, traditional testing methods often fall short in keeping up with the fast-paced development cycles and changing user needs. Fortunately, advancements in machine learning and generative AI are bringing intelligent and adaptive testing strategies that improve test coverage and decrease maintenance efforts to speed up the entire testing process. This article details using large language models (LLMs) to test a Python codebase project.

Top Security Automation Tools for Auto-Remediation

Aggregated on: 2025-03-17 11:28:09

Speed matters in cybersecurity. Responding to a potential threat in seconds rather than minutes can be the difference between a thwarted attack and a realized one. The problem is that human analysts — however capable they may be — often can’t remediate threats in time. Investigating an alert and executing response actions can be a slow process — and that’s if security teams remediate them at all. Disturbing research from 2023 found that organizations only remediate 13% of vulnerabilities and take an average of 271 days to address the ones they do. So, how can organizations help analysts overcome their — albeit understandable — limitations and remediate issues as soon as they arise? With auto-remediation tools.

Accelerating Deep Learning on AWS EC2

Aggregated on: 2025-03-14 21:13:08

One common approach to significantly speed up training times and efficiently scale model inference workloads is to deploy GPU-accelerated deep learning microservices to the cloud, enabling flexible, on-demand compute for training and inference tasks. This article provides a comprehensive guide covering the setup and optimization of such a microservice architecture. We’ll explore installing CUDA, choosing the right Amazon EC2 instances, and architecting a scalable, GPU-enabled deep learning platform on AWS.

Automate and Standardize IBM ACE Installation With PowerShell

Aggregated on: 2025-03-14 20:13:08

Tackling the Repetition If you've worked with IBM App Connect Enterprise (ACE) for any length of time, you’re probably familiar with the repetitive nature of installations. Each setup involves the same predictable steps: unpacking the release files, configuring directories, updating scripts, adjusting ODBC entries, setting up the runtime environment, and verifying that everything runs smoothly. While these steps might seem routine, the manual process is inherently prone to human error. A missed step, such as skipping a configuration file or mistyping a path, can cause inconsistencies that lead to operational issues — problems that sometimes take a long time to diagnose and resolve.

Build a Scalable E-commerce Platform: System Design Overview

Aggregated on: 2025-03-14 19:28:08

Topic: High-level design of an e-commerce platform like Amazon, Walmart, etc. Objective: Big picture, challenges, options to overcome those

Event Sourcing 101: When to Use and How to Avoid Pitfalls

Aggregated on: 2025-03-14 18:28:08

Recently, I delivered a lecture to my colleagues on event sourcing, and I realized that this introductory information could be valuable to a broader audience. This article is useful for those interested in the concept of event sourcing and who want to decide if it's a good fit for their projects while avoiding common pitfalls. So, let's dive in.

Queries for Optimizing and Debugging PostgreSQL Replication

Aggregated on: 2025-03-14 17:28:08

PostgreSQL logical replication provides the power and organization behind a pgEdge replication cluster, allowing you to replicate tables selectively and, on a more granular level, the changes in those tables. Whether you're using pgEdge Distributed PostgreSQL replication for real-time analytics, low latency, or high availability, optimizing replication configuration and query use allows you to optimize for performance, consistency, and reliability. Postgres replication is a powerful tool for replicating data between databases; unlike physical replication, logical replication gives you more control and flexibility over what data is replicated and how it's used.

Smart Cities With Multi-Modal Retrieval-Augmented Generation

Aggregated on: 2025-03-14 16:58:08

Why Smart Cities Need Advanced AI Managing cities today is an increasingly complex task. Urban centers face challenges like: Traffic congestion, which affects daily commutes and the economy. Infrastructure maintenance, where damaged roads or broken utilities need quick attention. Air quality and environmental monitoring, critical for public health and safety. City planners, traffic managers, and environmental regulators rely on data to make decisions, but often, this data is siloed or outdated. For example, when a city planner asks, “Which roads need repairs and how should traffic be rerouted?” the answer requires:

Building a Real-Time AI-Powered Workplace Safety System

Aggregated on: 2025-03-14 16:28:08

Workplace injuries from poor posture cost industries billions annually. While traditional ergonomic assessments are manual and periodic, we developed an AI-powered solution that provides real-time monitoring and feedback. Here's how we built it using Python, MediaPipe, and OpenCV.