News Aggregator

WebAssembly (Wasm) and AI at the Edge: The New Frontier for Real-Time Applications

Aggregated on: 2025-07-04 20:26:43

In the fast-moving digital world, users demand instant responses and smarter technology on every device they use. This demand is pushing for advancement to faster, secure, and efficient computing techniques. Two technologies are coming to the fore as powerful solutions — WebAssembly (Wasm) and artificial intelligence at the edge (Edge AI) — redefining the ways real-time applications are built and deployed. WebAssembly and Edge AI together form a powerful duo that bridges performance and intelligence at the device level. By enabling high-speed execution and local decision-making, they reduce latency, enhance privacy, and deliver seamless user experience, marking a major shift in how real-time applications are developed for today’s diverse and demanding digital environments.

Modernizing Apache Spark Applications With GenAI: Migrating From Java to Scala

Aggregated on: 2025-07-04 19:26:43

If you're working on big data projects using Spark, you've likely come across discussions within your team about Java vs. Scala vs. Python, along with comparisons in terms of implementation, API support, and feasibility. These technologies are typically chosen on a case-by-case basis depending on the specific use case. For example, data engineering teams often prefer to use Scala over Java because of:

Are Traditional Data Warehouses Being Devoured by Agentic AI?

Aggregated on: 2025-07-04 18:26:43

From a technical architecture perspective, I believe this wave of AI will profoundly reshape the entire software ecosystem. DSS systems are designed around the logic of human decision-making as the ultimate consumer. However, with the advent of the Agentic AI era, the final "consumer" is more likely to be an agent. This will lead to a complete redesign—or even elimination—of traditional data warehouses and complex ETL pipelines. Conventional data warehouses emphasize structure and query patterns, but they will be replaced by Agentic Data Stack architectures that focus on semantics and response patterns. Introduction: The Signal Behind Snowflake’s CEO Change In the spring of 2024, Snowflake, a star in the cloud data warehouse space, announced a change in leadership: Sridhar Ramaswamy, former head of Google’s advertising business, succeeded the legendary CEO Frank Slootman, who had helped Snowflake reach a $60 billion valuation.

Event Storming Workshops: A Closer Look at Different Approaches

Aggregated on: 2025-07-04 17:26:43

Event Storming serves as a strategic approach to gain a comprehensive understanding of the business domain, aiming to unveil as many uncertainties and complexities as possible prior to initiating design and implementation. Each phase of this process demands varying degrees of detail and breadth of information. At times, a broad overview suffices, while certain scenarios necessitate an in-depth exploration of the intricate aspects of specific requirements. Preparing for Your Event Storming Workshop Who to Invite? A successful workshop hinges on three participant groups:

The Shift to Open Industrial IoT Architectures With Data Streaming

Aggregated on: 2025-07-04 16:26:43

Operational Technology (OT) has traditionally relied on legacy middleware to connect industrial systems, manage data flows, and integrate with enterprise IT. However, these monolithic, proprietary, and expensive middleware solutions struggle to keep up with real-time, scalable, and cloud-native architectures. Just as mainframe offloading modernized enterprise IT, offloading and replacing legacy OT middleware is the next wave of digital transformation. Companies are shifting from vendor-locked, heavyweight OT middleware to real-time, event-driven architectures using Apache Kafka and Apache Flink, enabling cost efficiency, agility, and seamless edge-to-cloud integration.

Leveraging AI: A Path to Senior Engineering Positions

Aggregated on: 2025-07-04 15:26:43

As I sit here, reflecting on my past experiences as a software engineer, I am reminded of the countless hours spent trying to streamline the development processes and improve productivity for the team. It's an issue that plagues many of us, but one that I believe can be addressed with the help of AI agents. I clearly remember when I first encountered AI agents - I was skeptical, to say the least. But as I delved into the world of machine learning and automation together, I began to see the possibilities for these tools to transform the business. After months of experimenting with a variety of AI-powered tools, I am excited to share my findings with the community.

How Predictive Analytics Became a Key Enabler for the Future of QA

Aggregated on: 2025-07-04 14:26:43

In recent years, software development has experienced significant growth and increased emphasis on quality. For instance, conventional software testing has primarily been mechanical, where defects are detected and corrected during testing. Although this method has been used for some time and has been somewhat helpful, it has been considered unsuitable in the current context of derivation, integration, and frequent updates. This is where predictive analytics comes in—a new approach that turns the model from one of post facto testing and design to one of pre-testing. Real-time analytics is a process that identifies potential defects and failures by analyzing historical data, leveraging machine learning, and applying statistical models to predict future occurrences. This enables development teams to take preventive measures to prevent system failures, reducing downtimes and enhancing software quality. This is not just a change in the tools employed in developing these software systems; it is a change mandated to enable software development in a new way.

The Evolution of Software Integration: How MCP Is Reshaping AI Development Beyond Traditional APIs

Aggregated on: 2025-07-04 13:26:43

As software engineers, we've spent years mastering the art of API integration. We've wrestled with REST endpoints, debugged authentication flows, and built countless adapters to make disparate systems talk to each other. But as artificial intelligence transforms from experimental technology to production necessity, we're witnessing a fundamental shift in how software systems need to communicate. The API Foundation: A Double-Edged Success Story We need to acknowledge what APIs have helped us accomplish; they helped revolutionize software development by providing standardized ways for systems to interact. For example, the Stripe payment API enabled developers across the world to add complex financial transactions through simple HTTP calls, and GitHub's REST API enabled an entire ecosystem of development tools. These successes shaped how we think about system integration.

How to Troubleshoot Common Linux VPS Issues: CPU, Memory, Disk Usage

Aggregated on: 2025-07-04 12:26:43

Linux, for its reputation of stability, security, and efficiency, several of the internet is hosted on Linux-based cloud servers, web hosts, and enterprise applications. This reliability positions it ideal for Virtual Private Servers (VPS), where even during high-demand workloads, it remains operational. Linux has native tools that are very powerful for diagnosing and solving your issues in no time. The commands such as top, htop, vmstat, and sar are used to monitor the system resources in real-time so that the performance bottleneck can be identified and corrective action can be taken before your VPS starts to freeze.

One Checkbox to Cloud: Migrating from Tosca DEX Agents to E2G

Aggregated on: 2025-07-04 11:26:43

If you read my recent article on the Elastic Execution Grid (E2G), you’ll know I’ve been exploring some of the newer additions to the Tosca ecosystem. It’s been an interesting learning curve and raised a few thoughts about how we approach execution infrastructure. That said, I realize many teams are still working smoothly with their existing DEX testing setups, and for good reason. If your workflows are stable and reliable, it can be hard to justify changing what already works. The effort to switch can feel like more hassle than it’s worth.

How to Use AI to Understand Gaps in Your Resume and Job Descriptions

Aggregated on: 2025-07-03 20:11:43

At the beginning of my career, when I applied for jobs, I felt there was always a gap between what my resume had and what the job description said. I used to spend many hours staring at my resume, second-guessing whether it reflected my skills correctly or aligned with the Job Description and what recruiters were looking for. Not knowing if my resume would surpass the Applicant Tracking Systems (ATS) drove me to understand what might work in today's job search game. That's when I realized that there might be many of those who are struggling with such issues. However, people who are constantly up-leveling their skills in software engineering and have gained might find it easier to at least get through the ATS filtering with their experience, specific job requirements, or domain knowledge needed to crack the job. But for someone who's new to software engineering or who knows how to use AI but needs a head start with building an AI (LLM-based) tool for themselves, this solution might help.

Self-Supervised Learning Techniques

Aggregated on: 2025-07-03 19:26:43

Visual tracking systems are essential for applications ranging from surveillance to autonomous navigation. However, these systems have a significant Achilles' heel: they rely heavily on large, labeled datasets for training. This reliance makes it challenging to deploy them in real-world situations where labeled data is scarce or expensive to obtain. In this article, we will learn about self-supervised learning (SSL) and how it leverages unlabeled data to train models. What Is the Problem? Visual tracking involves identifying and following an object across frames in a video. Traditional methods depend on vast amounts of labeled data to learn how to recognize and track objects accurately. This dependence poses several problems:

Real-Time Market Data Processing: Designing Systems for Low Latency and High Throughput

Aggregated on: 2025-07-03 18:26:43

In financial markets, real-time data processing is critical for trading, risk management, and decision-making. Market data systems must ingest and process millions of updates per second while ensuring ultra-low latency. During my time at Bloomberg and Two Sigma, I worked on optimizing such systems for speed and reliability. By the means of this article, I’d like to explore key challenges in real-time market data processing, design strategies, and optimizations—with code snippets where applicable. I’ll try my best to keep things succinct without going into too much details!

The OWASP Top 10 for LLM Applications: An Overview of AI Security Risks

Aggregated on: 2025-07-03 17:26:43

The world of AI, especially with Large Language Models (LLMs) and Generative AI, is changing the game. It's like we've unlocked a superpower for creating content, automating tasks, and solving tricky problems. But, as with any new superpower, there are new ways things can go wrong. Open Worldwide Application Security Project (OWASP) experts have put together a list of the top 10 security risks specifically for these new AI applications in 2025. Think of it as a field guide to help everyone from developers to CISO’s, spot and fix these new kinds of digital vulnerabilities. Let's break down these top 10 AI security risks, with simple explanations and everyday examples:

Designing Microservices Architecture With a Custom Spring Boot Starter and Auto-Configuration Framework

Aggregated on: 2025-07-03 16:11:43

Spring Boot has Java development with its embedded servers, auto-configuration, and convention-over-configuration philosophy. Among its many features, one of the most powerful — but often underused — is the ability to create custom Spring Boot starters. These components enable development teams to package and reuse common configuration and boilerplate logic, making microservices more modular, maintainable, and consistent across a large-scale enterprise platform. This article explores how to build and use custom Spring Boot starters with auto-configuration to centralize concerns such as database access, authentication, and WebSocket communication, especially valuable in environments like loan servicing and trading platforms that operate with numerous microservices.

Seata the Deal: No More Distributed Transaction Nightmares Across (Spring Boot) Microservices

Aggregated on: 2025-07-03 15:11:43

In a time when nostalgia may have gone a little too far, the software development world has been swept by a heated debate: has the massive adoption of the microservices pattern truly delivered the expected benefits, or is its balance sheet more uncertain? Many teams are starting to wonder whether it’s time for a “homecoming” to the good old, reliable monolith — or if the answer lies somewhere in between, in the form of the modular monolith. A distracted architect distributed transactions

Building V1 Gen-AI Products at Scale: Technical Product Patterns That Work

Aggregated on: 2025-07-03 14:11:43

Shipping the first version of the Gen-AI product is not only a technical problem but a systems-level event. Coordinating the product, infra, security, design, and executive layers when doing it in the enterprise or a consumer-grade setting is necessary. This is especially true when the product interacts with real users and serves in a business-critical environment. This is not a testbed prompt with an open-source LLM. This is a real-world deployment; at this scale, every minute of latency and every hallucination incurred ceases to be some model parameter and becomes a business liability.

Advanced gRPC in Microservices: Hard-Won Insights and Best Practices

Aggregated on: 2025-07-03 13:11:43

Building microservices at scale often means pushing beyond the basics of gRPC. Many teams adopt gRPC for its high performance and cross-language support, only to discover subtle complexities when running it in production. In this article, we delve into advanced gRPC concepts — streaming, deadlines, interceptors, load balancing — and share practical “dos and don’ts” learned from real-world systems. We’ll also examine how industry leaders like Netflix have leveraged gRPC to boost productivity and solve tough issues in their microservice architectures. The goal is a leadership-level view of gRPC: not just how to write a service, but how to build and scale a gRPC-based microservice ecosystem effectively. Let’s explore the key concepts and hard-won lessons for making the most of gRPC in production.

How We Broke the Monolith (and Kept Our Sanity): Lessons From Moving to Microservices

Aggregated on: 2025-07-03 12:11:43

If you’ve ever been nervous about deploying code on a Friday, trust me — you’re not alone. A few years ago, I was leading a team at a major e-commerce company, wrangling a monolithic beast that could break in a hundred creative ways. The idea of microservices was everywhere, but nobody really tells you about the messy parts. Here’s what we learned the hard way — warts and all — while moving from monolith to microservices.

Why Traditional CI/CD Falls Short for Cloud Infrastructure

Aggregated on: 2025-07-03 11:56:43

For years, CI/CD pipelines have been the gold standard for software delivery—fast, repeatable, and reliable. But when it comes to cloud infrastructure, the model breaks down. It’s not that CI/CD is broken. It’s that infrastructure isn’t software. It has different constraints, different risks, and very different failure modes. And treating it like software introduces risk, drift, friction, and operational overhead—right when teams need speed and stability most. The more your cloud estate grows, the more these problems compound—until visibility, control, and velocity start to erode.

Top Tools for Front-End Developers

Aggregated on: 2025-07-03 11:11:42

My Favorite Tools for Writing High-Quality Code With Maximum Fun and Minimal Effort As a developer, having the right tools can transform your workflow from tedious to enjoyable, while ensuring your code is top-notch. Over time, I’ve discovered a set of tools that strike the perfect balance between power, ease of use, and even a bit of fun! Whether you’re a seasoned coder or just diving in, these tools can make your development life easier and more productive. Quick List IDE WebStorm API tools Mockoon Postman Debuging Chrome Developer Tools React Developer Tools Redux DevTools Accessibility Chrome Accessibility Inspector Lighthouse ANDI (Accessible Name & Description Inspector) WAVE (Web Accessibility Evaluation Tool) 1. WebStorm: The All-in-One IDE WebStorm is an amazing Integrated Development Environment (IDE) that now comes with free — yes, you heard that right!

Stabilizing ETL Pipelines With Airflow, Presto, and Metadata Contracts

Aggregated on: 2025-07-02 20:26:42

Wednesday. 10:04 AM. The dashboard says conversions dropped 18%. Product’s panicking. Marketing’s quiet-slacking you. But nothing’s failed—Airflow’s green, Hive tables are updating, and your pipeline logs look squeaky clean. That’s when it hits you: this isn’t a failure. It’s something worse. It’s silent data drift.

Parallel Data Conflict Resolution in Enterprise Workflows: Pessimistic vs. Optimistic Locking at Scale

Aggregated on: 2025-07-02 19:11:42

Data conflict resolution is not a simple backend detail in modern enterprise systems, particularly when supporting complex concurrent operations. It is a full-stack architectural matter that affects consistency, UX, observability, and trust in the system. We experienced this firsthand while building a government system that handled claims adjudication. Multiple case workers accessed and edited the shared records in parallel, and the premise that all system parts could be operated separately started to break down. Locking was no longer a database concern; it became a product at that scale.

Deploying LLMs Across Hybrid Cloud-Fog Topologies Using Progressive Model Pruning

Aggregated on: 2025-07-02 18:26:42

Large Language Models (LLMs) have become backbone for conversational AI, code generation, summarization, and many more scenarios. However, their deployment poses significant challenges in environments where compute resources are limited mostly in hybrid cloud-fog architectures, where real-time inference may need to run closer to the edge. In these instances, progressive model pruning plays a pivotal role offering solution to reduce model size and computation cost without impacting accuracy. In this article, we will discuss how to efficiently deploy LLMs across cloud-fog topologies using layer-aware, resource-adaptive pruning techniques.

Top NoSQL Databases and Use Cases

Aggregated on: 2025-07-02 17:26:42

Traditional relational databases (SQL), while robust and reliable, are not always the ideal solution. The demand for high-performance, scalable, and schema-flexible data storage systems has driven the adoption of NoSQL databases, which offer alternatives to the rigid structure of relational systems. NoSQL (short for “Not Only SQL”) databases are designed to handle large volumes of unstructured, semi-structured, or structured data, with a focus on flexibility, horizontal scalability, and real-time performance. They are increasingly used in modern architectures, especially where speed, flexibility, and high throughput are essential, such as mobile applications, real-time analytics, and IoT systems.

MCP and The Spin-Off CoT Pattern: How AI Agents Really Use Tools

Aggregated on: 2025-07-02 16:11:42

Why MCP Is the Missing Piece in the AI Tool Integration Puzzle I’ve read many articles explaining what MCP is, but none explore how AI actually handles these server interactions under the hood. Here’s my take, using what I call the ‘Spin-off CoT’ concept. Picture this: You’re having a conversation with an AI assistant about the weather in San Francisco. Behind the scenes, something fascinating happens. The AI doesn’t just “know” the current temperature — it spawns what I call a “spin-off Chain of Thought” (CoT) to handle tool interactions. This pattern, which emerged naturally from our exploration of the Model Context Protocol (MCP), reveals something profound about how AI systems should integrate with external tools.

Why API-First Frontends Make Better Apps

Aggregated on: 2025-07-02 15:11:42

In today’s software landscape, building a frontend that simply looks good isn’t enough. The real power lies in how well it interacts with APIs because that’s where the data lives, the business logic resides, and the real-time user experience gets delivered. If your frontend is still structured as a UI-first project where data integration is a postscript, it’s time to flip that approach. This guide walks through what it means to design API-centric frontends from the ground up, how to avoid common pitfalls, and how to build interfaces that are both dynamic and maintainable.

Vibe Coding: Conversational Software Development — Part 1 Introduction

Aggregated on: 2025-07-02 14:11:42

Since I started coding, I have seen developer communities strive to make programming more human-readable, almost like writing in English or a preferred language. Many modern languages introduced syntactic sugar to make code more intuitive and conversational. These efforts have made significant advancements, but now, we are witnessing something far more transformative. Natural language can now be translated directly into functional software. The concept is trending and is widely referred to as vibe coding. It is an AI-first approach for rapid software development. Let me try to explain the idea with the help of a step-by-step diagram that I have added below. As the picture shows, you put down your thoughts or overall idea as a prompt. You direct what step you want to achieve or what is your end goal. The chat-based AI works on your prompt and comes up with a generated code. You preview the output of the code and can fine-tune it further. Once you are happy, you put that code into your server.

Microservice Madness: Debunking Myths and Exposing Pitfalls

Aggregated on: 2025-07-02 13:11:42

Microservice is the false belief that adding a message broker to your app will somehow magically make it faster and more scalable. Ignoring the fact that this is, in itself, an oxymoron—and that your app quite literally becomes two billion times slower—the absolute dumbest argument I've ever heard in favor of microservices is:

Reducing Hallucinations Using Prompt Engineering and RAG

Aggregated on: 2025-07-02 12:26:42

Overview Large language models (LLMs) are a powerful tool to generate content. The generative capabilities of these LLMs come with various pros and cons. One of the major issues we often encounter is the factual correctness of the generated content. The models have a high tendency to hallucinate and sometimes generate non-existent and incorrect content. These generated contents are so impressive that they look like they are factually correct and viable. As developers, it is our responsibility to ensure the system works perfectly and generates concise content. In this article, I will delve into two of the major methodologies that I employed to lower the hallucinations for applications developed using AWS Bedrock and other AWS tools and technologies.

Docker Model Runner: A Game Changer in Local AI Development (C# Developer Perspective)

Aggregated on: 2025-07-02 11:11:42

Big breakthroughs and advancements in AI, particularly with LLM's (Large Language Models) have made it increasingly common for developers to integrate AI capabilities into their applications in a faster way than ever before. However, developing, running, and testing these models locally can often be challenging due to environment inconsistencies, performance issues, and dependency management. It's a common pattern. To help with this, Docker introduced Docker Model Runner, a new feature in Docker Desktop designed to simplify the process. In this post, we’ll take a closer look at Docker Model Runner, explore its benefits, and walk through an end-to-end project to see it in action. What Is Docker Model Runner (DMR)? Docker Model Runner is a feature integrated into Docker Desktop that aims to streamline local development and testing of LLM models. It helps in solving several pain points often faced by developers working on AI related projects.

Reinforcement Learning in CRM for Personalized Marketing

Aggregated on: 2025-07-02 11:11:42

The modern customer relationship management (CRM) system plays an increasingly strategic role in building effective communication with customers. The competitive environment demands not only quality customer service but also intelligent, personalized engagement that considers both current customer interests and their potential long-term value. In this context, personalized marketing is becoming one of the most critical development areas for CRM platforms. However, traditional machine learning algorithms used in most CRM systems exhibit several limitations. They rely on historical data, are slow to react to dynamic changes in customer behavior, and fail to optimize marketing strategies for long-term outcomes. One of the most promising technologies to overcome these limitations is reinforcement learning (RL).

Replacing Legacy Systems With Data Streaming: The Strangler Fig Approach

Aggregated on: 2025-07-01 20:11:42

Organizations looking to modernize legacy applications often face a high-stakes dilemma: Do they attempt a complete rewrite or find a more gradual, low-risk approach? Enter the Strangler Fig Pattern, a method that systematically replaces legacy components while keeping the existing system running. Unlike the “Big Bang” approach, where companies try to rewrite everything at once, the Strangler Fig Pattern ensures smooth transitions, minimizes disruptions, and allows businesses to modernize at their own pace. Data streaming transforms the Strangler Fig Pattern into a more powerful, scalable, and truly decoupled approach. Let’s explore why this approach is superior to traditional migration strategies. What Is the Strangler Fig Design Pattern? The Strangler Fig Pattern is a gradual modernization approach that allows organizations to replace legacy systems incrementally. The pattern was coined and popularized by Martin Fowler to avoid risky “big bang” system rewrites.

A Keycloak Example: Building My First MCP Server Tools With Quarkus

Aggregated on: 2025-07-01 19:11:42

Recently, I explored how the Model Context Protocol (MCP) is gaining traction in the Java ecosystem, with frameworks like Spring AI, Quarkus, and LangChain4j starting to adopt it for integrating language models via standardized interfaces. It was also time to start experimenting with writing an MCP Server myself (well maybe not the first time). Certainly, I don’t want to be left out of all the cool things being demonstrated by the community. The goal for me is to learn, and creating perhaps a more practical example. In this post I am going to choose Keycloak, and write an experimental MCP server implementation for Keycloak. The post is also to spark interest around this topic: Will it be useful to have an MCP server for Keycloak?

Spring Cloud LoadBalancer vs Netflix Ribbon

Aggregated on: 2025-07-01 18:26:42

The Spring Cloud ecosystem has been evolving significantly over the years. At first, it was mainly based on the Netflix stack, then it started shifting towards its own solutions. One of the components that has been substituted is Netflix Ribbon. Ribbon is a client-side load balancer and has been replaced by Spring Cloud LoadBalancer. Spring Cloud LoadBalancer is a more modern and maintainable solution. In this article, you will learn the differences between the two, their designs, and practical examples in Java.

Ethical AI for Product Owners and Product Managers

Aggregated on: 2025-07-01 17:26:42

TL; DR: Ethical AI or Risk? Without ethical AI, Product Owners and Product Managers (PO/PMs) face a dilemma: balancing AI’s potential with its risks in product discovery and delivery. Unchecked AI can introduce bias, compromise data, and erode empathy. To navigate this, implement four guardrails: ensuring data privacy, preserving human value, validating AI outputs, and transparently attributing AI’s role. This approach transforms PO/PMs into ethical AI leaders, blending AI’s power with indispensable human judgment and empathy.

Squid Game: The Clean Code Trials — A Java Developer's Survival Story

Aggregated on: 2025-07-01 16:11:42

"In the world of code, there are only two outcomes: evolve or perish." Episode 1: The Red Light of Rigid Code Scene: A vast ODC filled with desks, whiteboards, and terminals. The chairs are marked with red and green stickers. Software contestants sitting, trembling, gazing at a giant robot doll that watches them intently.

Zero-Click CRM: The Future of Predictive Customer Management With Autonomous AI

Aggregated on: 2025-07-01 15:11:42

As the digital economy matures and customer expectations evolve, businesses are seeking not only faster, but also smarter ways to manage relationships. Traditional customer relationship management (CRM) systems have undergone a major transformation in recent years, with AI playing a central role in enabling automation, personalization, and predictive insights. However, the next frontier is emerging — Zero-Click CRM — a concept that pushes AI integration even further, aiming to remove the need for manual interaction altogether in many customer-facing tasks. This article explores the core technological, architectural, and ethical aspects of Zero-Click CRM and outlines how it will transform how businesses interact with customers, making these systems not just reactive, but truly proactive and autonomous.

The Death of REST? Why gRPC and GraphQL Are Taking Over

Aggregated on: 2025-07-01 14:26:42

For two decades, REST has been the undisputed monarch of API architecture. Stateless. Cacheable. Universally understood. Yet beneath this seemingly unshakeable foundation, tectonic shifts are occurring — and they're happening fast. Walk into any modern tech company today, and you'll witness a quiet revolution. Engineers are abandoning REST endpoints in favor of something entirely different. gRPC calls zip through internal networks at breakneck speeds. GraphQL queries slice through data with surgical precision. The question isn't whether change is coming — it's whether REST can survive it.

Microservices for Machine Learning

Aggregated on: 2025-07-01 13:11:42

My latest personal project, a personal finance tracker with ML-powered insights, started with a simple feature to categorize expense but quickly got expanded to accommodate multiple features including handling everything from transaction classification to spending predictions (I was greedy to get into ML based investment recommendations but oh boy I don’t think I’m there yet to believe in making ML recommended investments :D). When one model failed, everything failed. So I decided to do what I'd been putting off for months: break the monolith apart. Here's what I learned decomposing my personal ML project into focused microservices, and why, I think, you might want to consider the same approach for your own projects.

CRITICAL_PROCESS_DIED: How to Fix This Windows Blue Screen Error

Aggregated on: 2025-07-01 12:11:42

CRITICAL_PROCESS_DIED is a notorious Windows error that triggers the dreaded Blue Screen of Death (BSOD), often leaving users frustrated and unsure of how to proceed. This error typically indicates that a critical system process has unexpectedly terminated, causing Windows to halt to prevent further damage. Encountering this error can disrupt your workflow and raise concerns about your system's stability. In this comprehensive guide, we'll explore the causes, solutions, and preventive measures for the CRITICAL_PROCESS_DIED error, ensuring you can get your system back on track quickly. Key Takeaways The CRITICAL_PROCESS_DIED error is a BSOD caused by the failure of essential system processes. Common causes include faulty drivers, corrupted system files, hardware issues, or malware. Solutions range from updating drivers and running system scans to performing a system restore or reset. Preventive measures include regular system maintenance, driver updates, and malware protection. Always back up data before attempting advanced troubleshooting to avoid data loss. What Is the CRITICAL_PROCESS_DIED Error? The CRITICAL_PROCESS_DIED error, identified by the stop code 0x000000EF, occurs when a critical Windows process—such as those managing memory, I/O operations, or system services — stops functioning. This forces Windows to crash to protect the system from potential data corruption or hardware damage. The error is most common in Windows 10 and 11 but can also appear in older versions like Windows 7 and 8.

Jakarta EE 11 and the Road Ahead With Jakarta EE 12

Aggregated on: 2025-07-01 11:11:42

Jakarta EE 11 is now available, and it’s more than just a version update. It’s the beginning of a new era in enterprise Java—one that aligns with modern Java standards, simplifies the platform, and positions it for the future of cloud-native development. But it doesn’t stop there. Jakarta EE 12 is already shaping up to push the platform even further. Let’s explore what Jakarta EE 11 delivers and how Jakarta EE 12 is preparing us for a more powerful and modern Java ecosystem.

Docker Model Runner: Running AI Models Locally Made Simple

Aggregated on: 2025-07-01 11:11:42

Docker has released an exciting new beta feature that's set to revolutionize how developers work with generative AI. Docker Model Runner enables you to download, run, and manage AI models directly on your local machine without the complexity of setting up elaborate infrastructure. What Is Docker Model Runner and Why Should You Care? Docker Model Runner is a feature that dramatically simplifies AI model management for local development. Currently in beta testing, it's available in Docker Desktop version 4.40 and above across multiple platforms:

Tableau Dashboard Development Best Practices

Aggregated on: 2025-06-30 20:11:41

Tableau is a great tool for turning data into clear, interactive visuals. But to get the most out of it, it’s important to follow a few best practices. These help keep dashboards clean, fast, and easy to understand. Whether you're building reports for yourself or a wider team, sticking to some core development habits can save time, avoid headaches, and make your work more impactful. Data Sources and Extracts It is the main section of Tableau where you begin the configuration to pull the data from any source from this list.

Streamlining DevOps: How Containers and Kubernetes Deliver

Aggregated on: 2025-06-30 19:11:42

The software development landscape is rapidly evolving, with many organizations embracing containerized applications. Technologies like containers and Kubernetes have revolutionized DevOps and automation services. According to a Red Hat survey, containers assist organizations in fostering innovation, modernizing infrastructure, and enhancing IT support. Teams now develop, deploy, and manage applications differently because of containers in DevOps. These tools provide the consistency and scalability needed for success. Kubernetes leads the charge with faster deployment cycles and zero-downtime updates. The platform also offers automated scaling that responds to live traffic needs. This combination solves the common "it works on my machine" issue and ensures reliable application performance across development, testing, and production environments.

Rust: The Must-Adopt Language for Modern Software Development

Aggregated on: 2025-06-30 18:11:41

Rust brings together safety, speed, and solid support for concurrency, three things that are often hard to get all at once in a programming language. Here's how it stacks up against some of the popular ones: Why Rust Stands Out

DevOps Remediation Architecture for Azure CDN From Edgio

Aggregated on: 2025-06-30 17:26:41

Some ongoing projects are currently leveraging Azure CDN from Edgio (formerly Verizon), which is officially being retired. Notably, the shutdown date has been moved up to January 7, 2025, meaning users must take action sooner than initially planned. To understand the implications of this retirement, we recommend reviewing Microsoft’s official guidance in the article: Azure CDN from Edgio retirement FAQ

Maximizing Productivity: GitHub Copilot With Custom Instructions in VS Code

Aggregated on: 2025-06-30 16:11:41

AI code assistants really shine when they're integrated into an integrated development environment (IDE). Imagine an IDE as the ultimate workspace where everything a developer could want is right at their fingertips, like syntax highlighting that makes code a breeze to read, error detection that spots issues before they escalate, and version control that tracks every little change. In this dynamic setting, AI assistants become incredibly adept at understanding what you're trying to create. They can analyze your existing code, recognize the patterns you're using, and provide suggestions that feel like they're coming from a teammate who truly understands your project. What really makes this partnership between AI and IDEs so effective is how effortlessly they come together to remove the usual hurdles that slow developers down. Instead of constantly bouncing between different tools and losing your focus, you can maintain your coding rhythm while the AI takes care of the repetitive tasks, like generating boilerplate code or suggesting the next logical step in your function. If you hit a snag or need to tidy up a messy section, you can just ask your AI assistant for help without ever stepping out of your development environment. It’s like having a savvy coding buddy right there with you, ready to lend a hand whenever you need it, making the whole software-building process feel more like a team effort and less like a lonely battle against complexity.

Threat Modeling for Developers: Identifying Security Risks in Software Projects

Aggregated on: 2025-06-30 15:11:41

Software projects can have disastrous breaches resulting from security flaws that expose private information and compromise user confidence. Preventive security measures become critical as applications get more sophisticated. One of the best ways to find and reduce possible hazards before they turn into exploitable weaknesses is threat modeling. Structured approaches such as STRIDE and DREAD let developers methodically examine security concerns and create strong programs. Understanding Threat Modeling in Software Development A methodical strategy for spotting and assessing security vulnerabilities in a software system is threat modeling. Developers foresee possible risks and use mitigating techniques during the development procedure rather than reacting to weaknesses following an attack. Good threat modeling improves security by guiding teams toward where their applications might be weak and what steps they might take to reduce risks.

Transform Settlement Process Using AWS Data Pipeline

Aggregated on: 2025-06-30 14:11:41

Data modernization involves simplifying, automating, and orchestrating data pipelines, as well as improving the claim and settlement process using various AWS SaaS services, converting large data settlement files to a new business-required format. The task involves processing settlement files from various sources using AWS data pipelines. These files may be received as zip files, Excel sheets, or database tables. The pipeline applies business logic to transform inputs (often Excel) into outputs (also in Excel). Our inputs typically come from a variety of sources. Utilize inputs from existing AWS tables and external inputs in Excel format. These diverse inputs are ultimately converted to Parquet format. This documentation outlines the process and includes the AWS data pipeline ETL jobs architecture for replication purposes.