News Aggregator

After 9 Years, Microsoft Fulfills This Windows Feature Request

Aggregated on: 2025-05-23 14:43:02

Most of the source code for the Windows Subsystem for Linux (WSL) has now been released on GitHub. Microsoft announced on May 19 that developers and hobbyists can now build WSL from source, explore the code, experiment with modifications, and contribute directly to its development. What is Windows Subsystem for Linux? Windows Subsystem for Linux is a feature that allows users to run a Linux environment inside a Windows machine without requiring a virtual machine or dual boot setup. The first version, WSL, was released in 2016. Shortly after its launch, the first issue raised about WSL on GitHub questioned whether the feature would ever be open sourced; nearly a decade later, Microsoft has answered that request.

Implementing Explainable AI in CRM Using Stream Processing

Aggregated on: 2025-05-23 14:13:02

Modern-day customer relationship management (CRM) systems have become a vital element of the business ecosystem, orchestrating engagement at a personalized level and scale. Transparency becomes necessary in automated systems and machine-learning environments, especially when these systems have an increasing prominence in operations. Thus, explainable AI can be a solution: it makes model decisions interpretable and justifiable. This proved very powerful when combined with stream processing, allowing responsiveness in real time. Hence, together, they may remodel CRM platforms into intelligent systems: automated and yet understandable and controllable.

Event-Driven Microservices: How Kafka and RabbitMQ Power Scalable Systems

Aggregated on: 2025-05-23 13:43:02

Event-driven microservices have revolutionized how modern applications handle data flow and communication. Using message brokers such as Apache Kafka and RabbitMQ, microservices can efficiently process and distribute events in a scalable, fault-tolerant manner. This tutorial will guide you through the fundamentals of event-driven microservices, focusing on how Kafka and RabbitMQ enable scalable architectures.

Distributed Consensus: Paxos vs. Raft and Modern Implementations

Aggregated on: 2025-05-23 13:28:02

Distributed consensus is a fundamental concept in distributed computing that refers to the process by which multiple nodes (servers or computers) in a distributed system agree on a single data value or a sequence of actions, ensuring consistency despite the presence of failures or network partitions. In simpler terms, it's the mechanism that allows independent computers to reach agreement on critical data or operations even when some nodes fail or communication is unreliable. The importance of distributed consensus in today's technology landscape cannot be overstated. It serves as the foundation for:

Optimizing Software Performance for High-Impact Asset Management Systems

Aggregated on: 2025-05-23 12:58:01

My extensive experience building complex software systems has shown that performance optimization is often the deciding factor between operational success and failure, especially in large-scale environments managing millions of interconnected components. Unlike consumer-facing apps, enterprise asset management platforms must meet rigorous demands: high concurrency, guaranteed data integrity, and real-time access to mission-critical information. The Problem With Traditional Systems Conventional enterprise systems typically rely on synchronous APIs and relational databases. While this setup can support simple queries under moderate load, it struggles with the complexity and scale of modern asset management needs. When tens of thousands of users query complex bill of materials (BOMs), multi-level part hierarchies, or conditional attributes at once, latency becomes inevitable.

Scaling Microservices With Docker and Kubernetes on Production

Aggregated on: 2025-05-23 12:28:02

I am building a fleet of Python FastAPI microservices and aiming to scale them efficiently in a production environment. Each service runs inside a Docker container, which keeps it isolated and portable. I’m orchestrating these containers with Kubernetes, specifically using the lightweight K3s distribution on the Azure cloud. In this article, I share my hands-on experience optimizing this setup for high performance and reliability in production.

Apple and Anthropic Partner on AI-Powered Vibe-Coding Tool – Public Release TBD

Aggregated on: 2025-05-23 11:58:02

Apple has quietly partnered with Anthropic to build a new “vibe-coding” software tool that uses AI to write, test, and fix code. According to Bloomberg’s Mark Gurman, the project is essentially a revamped version of Xcode, Apple’s flagship software for building apps. But this new tool is infused with the Claude Sonnet model developed by Anthropic. It includes a chat-based interface where developers can instantly type requests and get code written. The vibe-coding tool can also debug apps and test user interfaces.

Modern Test Automation With AI (LLM) and Playwright MCP

Aggregated on: 2025-05-23 11:28:02

Delivering high-quality applications at scale is a constant challenge. Traditional test automation, while powerful, often struggles with dynamic user interfaces, flaky tests, and time-consuming script maintenance. This blog explores how generative AI (GenAI) and Playwright MCP (Model Context Protocol) work together to streamline QA processes, boost efficiency, and empower testers to focus on strategic tasks.

Power BI Embedded Analytics — Part 3: Power BI Embedded Demo

Aggregated on: 2025-05-22 21:28:01

Note: This article presents the details of a Power BI Embedded Demo application. This is a continuation of the articles Power BI Embedded Analytics — Part 1 and Power BI Embedded Analytics — Part 2, which discuss Power BI Authoring and Power BI Embedded. So, it is recommended that you go through the previous parts of the series. Power BI Embedded Demo Source Code Github: https://github.com/robinrizvi/embedded-analytics-poc

System Coexistence: Bridging Legacy and Modern Architecture

Aggregated on: 2025-05-22 20:28:01

Abstract Organizations are challenged with integrating legacy systems and modern applications in a way that ensures operational harmony and business continuity. This article explores the concept of system coexistence, the ability of diverse software systems built across different eras and architectures to function together within shared environments. It delves into practical strategies for achieving coexistence, such as the Strangler Fig Pattern, adapter-based decoupling, and event-driven communication models. The article also addresses critical supporting aspects like data coexistence, observability, and performance monitoring, emphasizing that coexistence is not merely a transitional phase but a strategic imperative for sustainable growth and innovation. Drawing on real-world examples, such as Netflix’s cloud migration and the HealthCare.gov launch failure, this piece provides a roadmap for organizations to navigate coexistence successfully while preparing for scalable, future-ready systems. Introduction We live in a world where it's easy to assume that all our applications built at different times, using the "best" technologies of their era will seamlessly integrate and continue to function in harmony. Yet, time and again, we’re proven wrong.

The Role of AI in Identity and Access Management for Organizations

Aggregated on: 2025-05-22 19:28:01

Introduction Identity and Access Management (IAM) is a key pillar of any organization. It plays a vital role in enterprise security—securing the resources and the data of an organization by making sure only authorized users have access. As the IT infrastructure of organizations is growing exponentially and increasing cyber threats, rule based IAM solutions are often insufficient. To enhance security, streamline processes, reduce operational costs, and adapt to evolving threats, organizations are integrating their IAM systems with Artificial Intelligence (AI). This article examines the technical aspects of how AI is driving a change in IAM for organizations.

Build a Simple REST API Using Python Flask and SQLite (With Tests)

Aggregated on: 2025-05-22 18:28:01

You can find the complete project and test files for this tutorial on GitHub if you’d like to follow along or extend the code further. In this tutorial we are going to build a REST API using Python Flask. We will create a simple Flask application that serves a single endpoint, GET /items, which returns a list of items from a SQLite database. This guide is written for beginners and will walk you through each step in a straightforward way. By the end, you will have a working API, a basic test file to verify the API, and a project structure that you can zip and upload to GitHub.

How to Create a Successful API Ecosystem

Aggregated on: 2025-05-22 18:28:01

Application programming interfaces (APIs) are essential to a developer’s daily work. They are the reasons why diverse hardware and the internet communicate seamlessly. Here is an accessible look into the world of API ecosystem creation for coders of all skill levels. What Is an API Ecosystem and Its Role for Devs? An API ecosystem is a collection of APIs working together. They function alongside many programs, documents, databases, scripts, and support to make digital spaces functional and easy to use. The network is like an open forum where various stakeholders can request services and information from other experts.

Go 1.24+ Native FIPS Support for Easier Compliance

Aggregated on: 2025-05-22 18:28:01

In February, Go released version 1.24, introducing significant enhancements to its cryptographic libraries, particularly in achieving FIPS (Federal Information Processing Standards) compliance. This update positions Go as a superior choice for developers building applications for U.S. federal government use. By eliminating dependency on third-party libraries and integrating FIPS compliance directly into its core, Go 1.24 simplifies and streamlines development for government-regulated industries. In this article, we’ll explore what FIPS is, why it matters, and how Go 1.24 changes the game for FIPS compliance.

Assessing Bias in AI Chatbot Responses

Aggregated on: 2025-05-22 18:28:01

Abstract AI communication in the form of chatbots has brought about a new paradigm of communication and service delivery through the use of large language models (LLMs) like GPT. However, as these technologies are applied in daily life, questions about the bias of the answers given by chatbots also arise. In this paper, the focus will be on discussing the ethical considerations of AI chatbots, including the detection of bias, fairness, and transparency. Bias detection techniques described in the study include fairness metrics, sensitivity analysis, and bias correction algorithms. It also emphasizes the importance of diverse training data and the integration of ethical protocols to avoid radiating bias. The consequences of bias in AI chatbots are explored in a range of cases and actual-life scenarios in settings including healthcare, recruitment, and customer relations and service. The study draws attention to the fact that more work has to be done to make certain that AI chatbots are designed and utilized in a way that is ethical and not deceptive. Keywords AI Chatbots, Bias Detection, Fairness Metrics, Transparency, Ethical AI, Bias Mitigation, Generative Pretrained Transformers (GPT), Chatbot Development, Ethical Guidelines, Artificial Intelligence

Knowledge Graph Embeddings and NLP Innovations

Aggregated on: 2025-05-22 18:28:01

Knowledge Graph Question Answering (KGQA) systems facilitate the structuring of typical natural language queries and consequently retrieve specific, relevant information from knowledge graphs efficiently. Given new advances in Knowledge Graph Embeddings (KGEs) and the sophistication of Large Language Models (LLMs), significant strides are being made in understanding complex semantic relationships and multi-hop queries. This article provides a comprehensive examination of embedding methodologies, particularly emphasizing advanced negative sampling strategies, and discusses the deployment of cutting-edge NLP architectures, such as RoBERTa, to enhance query representation and retrieval accuracy. Problem Synopsis and Importance Current KGQA frameworks face substantial obstacles in accurately interpreting, extracting, and reasoning over intricate relational data patterns present in multi-hop queries. These questions are notoriously nuanced and call for the ability to draw complex distinctions and conclusions. Unfortunately, conventional embedding techniques can miss the nuances of these relationships across the entire knowledge graph space, limiting the reliability and performance of KGQA systems. Better continual refinement of knowledge graph embeddings using more sophisticated negative sampling methods and more detailed NLP models creates excellent opportunities for enhancing query interpretation and answer precision.

SaaS in an Enterprise - An Implementation Roadmap

Aggregated on: 2025-05-22 15:28:01

With business software changing daily, companies are adopting Software as a Service (SaaS) solutions due to their agility, expandability, and economical nature. Compared to conventional software that must be installed on a local computer, SaaS is more appealing because it makes accessing applications over the internet much simpler. That said, a successful SaaS implementation entails consideration of planning, proper training, engagement of relevant parties, and continuous improvement. In this article, we discuss several approaches that ensure the effectiveness of your SaaS implementation.

Code Reviews: Building an AI-Powered GitHub Integration

Aggregated on: 2025-05-22 14:58:01

One common issue with growing teams with an extensive codebase is maintaining the code quality. It requires tremendous effort to maintain the code base, and manual code reviews often create a bottleneck during the development process. One standard practice is to get the pull request (PR) reviewed by a senior engineer before merging it into the code base. But developers often get overloaded with reviews as they continue to deliver their regular tasks and might overlook some of the minute details that end up in production. I personally had an experience where a simple missing null check created a cascading error during migration, ultimately leading to corrupted data in production. Human beings tend to make such mistakes, and it is a very common issue.

Analyzing Techniques to Provision Access via IDAM Models During Emergency and Disaster Response

Aggregated on: 2025-05-22 14:28:01

Introduction A natural or human-made disaster is a significant concern for populations across the world. It is important that the response to such cases be prompt and effective so that human and financial losses are minimized. In addition, while the response operations to such critical situations are often complex and complicated, a timely response is crucial. Therefore, designing and implementing effective identity and access management (IDAM) systems to respond to such incidents is the need of the hour. This article talks about the need for providing secure access in disaster response and the different techniques to provide access to key stakeholders during an emergency response. The Need for Secure Access in Disaster Response During disaster relief efforts several stakeholders are called upon to action. They include multiple organizations, such as government agencies, non-profits, private sector companies, and many more. Employees or staff of such organizations along with volunteers, many of whom may or may not have any sort of previous experience or affiliations with such agencies, must be onboard rapidly and granted access to mission critical resources.

MCP Servers: The Technical Debt That Is Coming

Aggregated on: 2025-05-22 13:58:01

Over the last decade, we’ve refined how APIs are built, shared, and consumed. REST became a common ground, OpenAPI offered structure, and gRPC brought speed. But now, in the age of AI, something new is surfacing: the rise of MCP servers — Model Context Protocol servers. These systems offer an enticing promise: bring AI into the loop by orchestrating backend calls, shaping flows in natural language, and empowering LLMs to act more independently.

Chat With Your Knowledge Base: A Hands-On Java and LangChain4j Guide

Aggregated on: 2025-05-22 13:28:01

Disclaimer: This article details an experimental project built for learning and demonstration purposes. The implementation described is not intended as a production-grade solution. Some parts of the code were generated using JetBrains’ AI Agent, Junie. Large language models (LLMs) like GPT-4, Llama, and Gemini have revolutionized how we interact with information. However, their knowledge is generally limited to the data they were trained on. What if you need an AI assistant that understands your specific domain knowledge — your company’s internal documentation, product specs, or operational data from a complex system?

GitHub Copilot's New AI Coding Agent Saves Developers Time – And Requires Their Oversight

Aggregated on: 2025-05-22 12:58:01

At Microsoft’s Build developer conference, GitHub announced the rollout of a new AI coding agent built directly into GitHub Copilot. This upgraded assistant can now handle development tasks like fixing bugs, writing features, refactoring code, and improving documentation. Developers can assign issues to Copilot through GitHub.com, GitHub Mobile, or the GitHub command-line interface, just like assigning them to a human. The agent reacts with an eyes emoji and kicks off its work.

Intro to RAG: Foundations of Retrieval Augmented Generation, Part 2

Aggregated on: 2025-05-22 12:28:01

In the last post, we discussed the basics of retrieval-augmented generation (RAG) and how it enhances the capabilities of large language models (LLMs) by integrating them with external knowledge sources. We also introduced the concept of vector embeddings and their role in semantic search. In this post, we'll dive deeper into the different layers of RAG, including vector RAG, graph RAG, and agents. We'll explore how these layers can be combined to create more powerful and effective AI systems.

Monolith: The Good, The Bad and The Ugly

Aggregated on: 2025-05-22 11:58:01

After an initial very warm welcome and a wave of hype, microservices are no longer considered a silver bullet for all software pitfalls. We, as a community of engineers, started to notice the significant complexity they introduced. The plain old monolith approach started to get mainstream attention once again. That is why, today, I would like to bring it and its different subtypes to your attention in more detail.

AI Speaks for the World... But Whose Humanity Does It Learn From?

Aggregated on: 2025-05-22 11:28:01

Generative AI models are widely celebrated for performing tasks that seem “close to human” — from answering complex questions to making moral judgments or simulating natural conversations. But this raises a critical question that is too often overlooked:

How to Merge HTML Documents in Java

Aggregated on: 2025-05-21 21:13:01

Java developers are often handed the challenge of consolidating documents in efficient file processing workflows. With this prompt, HTML might not be the first document format that comes to mind — we might think of “file processing” as pertaining to robust, “business-y” formats like PDF or Excel first and foremost — but HTML’s importance in many modern enterprise environments can’t be understated. Whether it's a question of processing data pulled together from multiple online sources, piecing scraped web pages together, or consolidating custom web-based reports, programmatically combining and packaging HTML content is often highly relevant. In this article, we’ll take a closer look at what it means to merge HTML content programmatically, and we’ll point out some of the specific challenges Java developers can expect to encounter in this endeavor. Towards the end, we’ll touch on some open-source libraries and third-party APIs we can use to build HTML merging capabilities into a file processing workflow, carefully weighing the benefits of each approach.

Enforcing Architecture With ArchUnit in Java

Aggregated on: 2025-05-21 20:28:01

You create a well-defined architecture, but how do you enforce this architecture in your code? Code reviews can be used, but wouldn't it be better to verify your architecture automatically? With ArchUnit you can define rules for your architecture by means of unit tests. Introduction The architecture of an application is described in the documentation. This can be a Word document, a PlantUML diagram, a DrawIO diagram, or whatever you like to use. The developers should follow this architecture when building the application.

Creating a Web Project: Caching for Performance Optimization

Aggregated on: 2025-05-21 19:28:01

In one of the previous articles on identifying issues in your project, “Creating a Web Project: Key Steps to Identify Issues,” we discussed how to analyze application performance and how collecting metrics can assist in this task. However, identifying a problem is only the first step; action must be taken to resolve it. Caching is arguably one of the most effective and widely used methods for accelerating your application. The principle behind it is that instead of performing complex operations each time, we temporarily save the result of those operations and return it for subsequent similar requests if the inputs have not changed. This way, the application can be sped up, load reduced, and overall stability improved.

Exploring Intercooler.js: Simplify AJAX With HTML Attributes

Aggregated on: 2025-05-21 18:28:01

Intercooler.js is a lightweight JavaScript library that enables developers to add AJAX functionality to their web applications with minimal effort. Inspired by HTML's simplicity, it allows the use of HTML attributes to handle dynamic updates instead of writing extensive JavaScript code. This library is ideal for developers who want the power of AJAX without diving into complex frameworks like React or Angular. Note: While Intercooler.js is still supported, its successor, htmx, offers additional features and enhanced browser capabilities.

Agile’s Quarter-Century Crisis

Aggregated on: 2025-05-21 17:28:44

TL; DR: Agile Failure at Corporate Level The data couldn’t be more supportive: Despite 25 years of the Agile Manifesto, countless books, a certification industry, conferences, and armies of consultants, we’re collectively struggling to make Agile work. My recent survey, although not targeting Agile failure, still reveals systemic dysfunctions that persist across organizations attempting to implement Agile practices:

How To Introduce a New API Quickly Using Quarkus and ChatGPT

Aggregated on: 2025-05-21 16:28:44

My last two articles (part 1 and part 2) focused on getting to market quickly using Java. The only difference was the build automation tool that I used for each example. This time, I want to step outside of my comfort zone and try something a little different. I read about how Quarkus is a Kubernetes-native Java framework designed for building fast, lightweight microservices. What’s even better is that it is optimized for cloud environments, including features like fast startup times, low memory footprints, and support for both imperative and reactive programming models.

The Future of Java and AI: Coding in 2025

Aggregated on: 2025-05-21 15:28:44

Expanding on the findings of "The State of Coding the Future with Java and AI" survey, this article focuses more on the unique perspective and potential for developers leveraging Quarkus for Java AI. Software development is evolving rapidly, and Java remains a cornerstone for enterprise applications, especially as Artificial Intelligence (AI) reshapes the coding landscape. In 2025, Java developers are at the forefront of this transformation, harnessing AI tools and frameworks like Quarkus to build scalable, cloud-native, and intelligent applications.

IoT and Cybersecurity: Addressing Data Privacy and Security Challenges

Aggregated on: 2025-05-21 14:28:44

The Internet of Things has shaken up our lives, connecting everything from smart homes to massive industrial systems in a pretty smooth way. Sure, these tech upgrades make our day-to-day so much easier, but they have also brought some real concerns about security and privacy. With billions of IoT devices out there, are we really ready for the growing cybersecurity threats?

Securing the Future: Best Practices for Privacy and Data Governance in LLMOps

Aggregated on: 2025-05-21 13:13:44

Over the last few years, they have rapidly developed in the field of large language models (LLMs) since these models can now underpin anything, from a customer service chatbot to an enterprise-grade solution. Now that such models are more woven into the fabric of daily operations, the definition of importance will extend beyond privacy to strong data governance. The operational infrastructure around LLMs is changing rapidly, focusing on security, compliance, and data protection as their rapid adoption across sectors makes such things poignant.

Prioritizing Cloud Security Risks: A Developer's Guide to Tackling Security Debt

Aggregated on: 2025-05-21 12:28:44

In this era of ever-growing digital footprint, decreasing security debt has become so critical for organizations operating in the cloud. The myriads of unresolved security findings expose services vulnerable to emerging threats as well as pose risk to compliance and governance. The solution requires organizations to develop an efficient method for prioritizing security risks based on severity levels across different teams to tackle this problem at scale. A forward-thinking solution involves creating a centralized security graph that merges various risk and compliance signals into one unified view. Such platforms enable engineering teams and security teams to discover and manage their most critical security risks by assessing their real business impact and risk severity rather than their age or backlog size.

Can You Run a MariaDB Cluster on a $150 Kubernetes Lab? I Gave It a Shot

Aggregated on: 2025-05-21 11:58:44

If you're like me, learning how to run databases inside Kubernetes sounds better when it's hands-on, physical, and brutally honest. So instead of spinning up cloud VMs or using Kind or minikube on a laptop, I went small and real: four Orange Pi 3 LTS boards (a Raspberry Pi alternative), each with just 2GB RAM. My goal? Get MariaDB — and eventually Galera replication — running on Kubernetes using the official MariaDB Kubernetes Operator.

Driving DevOps With Smart, Scalable Testing

Aggregated on: 2025-05-21 11:28:44

DevOps practices can require software to be released fast, sometimes with multiple deployments throughout the day. This is critical to DevOps, and to accomplish it, developers must test in minutes to determine if software will move forward, be sent back to the drawing board or canned altogether. Identifying and correcting bugs prior to production is essential to the Software Development Life Cycle (SDLC) and testing should play a part in all processes. During the test phase, integrating automated testing when possible is critical, with the choice of approach tailored to the specific application’s structure. This could involve focusing on public methods for APIs, verifying code and components or implementing comprehensive end-to-end (E2E) assessments. Emphasizing a thorough testing process ensures all aspects, such as units or methods, and integration between internal system components and frontend and backend parts.

Orchestrating Microservices with Dapr: A Unified Approach

Aggregated on: 2025-05-20 22:58:44

Introduction Modern software architectures are increasingly embracing microservices to improve scalability, flexibility, and resilience. However, as the number of systems expands, managing inter-service communication, data persistence, event-driven messaging, and security becomes more complex. Additionally, as a product scales, organizations often inadvertently develop strong dependencies on specific database providers, messaging middleware, or cloud vendors. This tight coupling makes future changes challenging, often requiring extensive refactoring. Dapr (Distributed Application Runtime) offers a unified abstraction for handling these concerns, allowing microservices to interact with databases, message queues, APIs, and secrets stores in a cloud-agnostic and infrastructure-independent manner.

Next-Gen IoT Performance Depends on Advanced Power Management ICs

Aggregated on: 2025-05-20 21:13:44

The rise of Internet of Things (IoT) applications is a key integrated circuit (IC) market driver. As these internet-connected technologies become increasingly smaller, complex, and energy-intensive, advanced power management ICs are exponentially important. Factoring in potential energy reliability issues due to heightened demand emphasizes this situation’s urgency. Thanks to its convenience and affordability, the IoT is quickly becoming a staple in industrial, medical, and technology spaces. Since demand is so high, research and development are flourishing. However, progress may soon stall unless professionals leverage advanced power management integrated circuit (PMIC) design to handle variable input and regulate voltage.

Kullback–Leibler Divergence: Theory, Applications, and Implications

Aggregated on: 2025-05-20 20:13:44

Kullback–Leibler divergence (KL divergence), also known as relative entropy, is a fundamental concept in statistics and information theory. It measures how one probability distribution diverges from a second, reference probability distribution. This article delves into the mathematical foundations of KL divergence, its interpretation, properties, applications across various fields, and practical considerations for its implementation. 1. Introduction

Manual Sharding in PostgreSQL: A Step-by-Step Implementation Guide

Aggregated on: 2025-05-20 20:13:44

Learn how to implement manual sharding in native PostgreSQL using Foreign Data Wrappers. This tutorial walks through creating distributed tables without additional extensions like Citus. The Challenge With Database Scaling As applications grow, single-node databases face several challenges:

Next Evolution in Integration: Architecting With Intent Using Model Context Protocol

Aggregated on: 2025-05-20 19:28:44

Integration has moved beyond system connectivity. In todays distributed digital first environments the focus has shifted from building statics connections to intelligent context aware interactions. The next phase of integration is to build the integration with intent using Model Context Protocol (MCP) design pattern. In this article, I will explain how integration evolved over the period from traditional middleware to cloud native approach to a design centric approach that aligns integration with meaning and intent. We will examine the architecture of MCP and how it's going to play a pivotal role in driving next-generation integration strategies. Integration in Middleware Era: Reliable, but Rigid Early integration strategies relied on centralized middleware and formal contracts like SOAP and XML. Systems were prioritized for consistency and reliability. The rigid contract definition and static service definition made them slow to adapt and very expensive to evolve. Development were often done in tools which required deep expertise and managing this has become huge overhead for organizations.

Building Reliable LLM-Powered Microservices With Kubernetes on AWS

Aggregated on: 2025-05-20 18:28:44

Software development environments have evolved due to large language models (LLMs), which offer advanced natural language processing capabilities that were previously unimaginable. To improve user experiences through conversational interfaces, content creation, data analysis, and other features, organizations are progressively integrating these models into their systems. However, implementing LLMs in production settings, especially as microservices, presents special difficulties that conventional application deployment techniques are not designed to handle.

Building an AI/ML Data Lake With Apache Iceberg

Aggregated on: 2025-05-20 17:28:44

As companies collect massive amounts of data to fuel their artificial intelligence and machine learning initiatives, finding the right data architecture for storing, managing, and accessing such data is crucial. Traditional data storage practices are likely to fall short to meet the scale, variety, and velocity required by modern AI/ML workflows. Apache Iceberg steps in as a strong open-source table format to build solid and efficient data lakes for AI and ML. What Is Apache Iceberg? Apache Iceberg is an open table format for big analytical datasets, initially built at Netflix. It solves many of the limitations of data lakes, especially when handling the needs of AI/ML workloads. Iceberg offers a table layer over file systems or object stores, introducing database-like functionality into data lakes. The most important aspects that make Iceberg valuable for Artificial Intelligence and machine learning workloads are:

Tired of Spring Overhead? Try Dropwizard for Your Next Java Microservice

Aggregated on: 2025-05-20 16:28:44

Instead of a monolith, build your first Java microservice with Dropwizard. Hello, my fellow programmers! I’m positive you do not want to read another complex article on how to build Java microservices. We are going to take a look at Dropwizard today. It is fairly convenient as it has everything loaded in it, i.e., Jetty, Jersey, Jackson, etc., and also provides you with the ability to set your business logic without the boilerplates.

Parameters to Measure in Chaos Engineering Experiments

Aggregated on: 2025-05-20 15:28:44

Keywords: Chaos Engineering, System Resilience, Failure Injection, Performance Metrics, Fault Tolerance Abstract Chaos Engineering is an essential practice for testing system resilience by intentionally injecting failures and analyzing the system’s response. This journal explores key parameters to measure in Chaos Engineering experiments, including system performance, availability, fault tolerance, and user experience metrics. By systematically monitoring these parameters, organizations can proactively identify weaknesses, enhance failover mechanisms, and optimize recovery strategies. The study also provides a structured experiment template to help teams document and analyze chaos experiments effectively. The ultimate goal is to build confidence in a system’s ability to withstand turbulent operational conditions and ensure reliable service delivery.

Secrets Sprawl and AI: Why Your Non-Human Identities Need Attention Before You Deploy That LLM

Aggregated on: 2025-05-20 14:28:44

It seems every company today is excited about AI. Whether they are rolling out GitHub Copilot to help teams write boilerplate code in seconds or creating internal chatbots to answer support tickets faster than ever, large language models (LLMs) have driven us into a new frontier of productivity very rapidly. Advancements like retrieval-augmented generation (RAG) have let teams plug LLMs into internal knowledge bases, making them context-aware and therefore much more helpful to the end user. However, if you haven’t gotten your secrets under control, especially those tied to your growing fleet of non-human identities (NHIs), AI might speed up your security incident rate, not just your team's output. Before you deploy a new LLM or connect Jira, Confluence, or your internal API docs to your internal chat-based agent, let’s talk about the real risk hiding in plain sight: secrets sprawl and the world of ungoverned non-human identities.

How to Build Real-Time BI Systems: Architecture, Code, and Best Practices

Aggregated on: 2025-05-20 13:43:44

In today’s fast-paced digital economy, real-time data is no longer a luxury—it’s a necessity. Traditional Business Intelligence (BI) systems, which rely on batch processing, introduce significant latency that can hinder timely decisions. Whether it's detecting fraud in banking or optimizing ICU bed allocation in hospitals, delay equals lost opportunity or even risk. Real-time BI turns this around by enabling systems to ingest, process, and visualize data within seconds or even milliseconds of generation. In this article, we’ll walk through the architecture, tools, and practical implementation steps required to build a real-time BI system, from ingestion and processing to analytics storage and dashboarding.

How Kubernetes Cluster Sizing Affects Performance and Cost Efficiency in Cloud Deployments

Aggregated on: 2025-05-20 12:13:44

Kubernetes has become the de facto solution for container orchestration when deploying applications in the cloud. It enables developers to scale applications easily and provides reliable management. However, cluster sizing is one crucial factor in determining the performance and cost efficiency of your Kubernetes deployment. In this article, we will examine how Kubernetes cluster sizing affects these two crucial factors and give actionable insights on how to improve your cloud environment.

Cloud Security and Privacy: Best Practices to Mitigate the Risks

Aggregated on: 2025-05-20 11:13:44

Cloud security refers to technologies, best practices, and safety guidelines that help to protect your data from human errors, insider and security threats. Therefore, it naturally covers a wide range of procedures, which are aimed at securing systems from data breaches, data loss, unauthorized access, and other cybersecurity-related risks that are growing from year to year. According to GitProtect's State of DevOps Threats report, the number of incidents in GitHub grew by over 20%, and around 32% of events in GitLab had an impact on service performance and customers. Moreover, it’s worth mentioning that the cost of failures is growing as well. Thus, the average cost of recovering from a ransomware attack is around $2.73 million, the average cost of a data breach is $4.88 million, and every minute of downtime can cost up to $ 9 K.