News Aggregator

ANTLR-Powered Query Engine and Floorplan Parser for Real Estate Data

Aggregated on: 2025-11-13 13:11:04

Some time ago, my colleagues published two deep-dive technical articles that walk through a real challenge we faced: turning chaotic, inconsistent real estate data into something machines and users can actually work with. If you’ve ever tried to make sense of MLS feeds, build a custom property search, or generate layouts from encoded property plans, you know the pain. This wasn’t a matter of plugging in a library or buying an API. We had to build the underlying parsers ourselves.

Building Fault-Tolerant Applications with Temporal Workflow Engine

Aggregated on: 2025-11-13 12:11:04

Workflows and orchestration are critical to most software systems. In fact, at a fundamental level, every piece of software is essentially a workflow: you write functions and execute them in a specific order. These functions retain state (variables), pass state along, discard state, and renew state. There are dependencies and relationships between these functions. Broadly speaking, any software system can be divided into two parts, orchestration and atomic actions. Orchestration handles retries, state management between methods, resource management, and error or crash handling. Now, imagine a system that handles all the orchestration aspects of software development, allowing you to focus solely on the atomic steps. Enter Temporal, a workflow engine that does exactly that. Temporal manages workflow orchestration for you, allowing you to focus on developing core business logic. From this perspective, Temporal is a truly powerful tool in my opinion.

Facilitate AI-Human Architectural Thinking

Aggregated on: 2025-11-12 20:11:04

Architectural thinking or modeling will only be effective when it involves a landscape, decisional, and structural view. People talk a lot about systems thinking, but to ensure a viable architectural model, systems thinking must approach it from the three pillars of thinking. AI-powered architectural thinking or modeling also requires these three pillars of thinking. Let’s briefly look at each of these from a perspective of enterprise solution architecture (ESA), which falls somewhere between enterprise architecture (EA) and solution architecture (SA).

The Terraform State Locking Migration You Need to Know About: Moving Beyond DynamoDB

Aggregated on: 2025-11-12 19:11:03

If you've been working with Terraform for a while, you probably have backend configurations that look something like this scattered across your infrastructure repositories. I know I did. And if you're like me, you might have missed a pretty significant announcement from HashiCorp that's going to affect how we handle state locking going forward. Let me save you some future headaches: DynamoDB-based state locking is being deprecated.

Compose Architecture, Done Right: MVI’s Unidirectional State vs. MVVM

Aggregated on: 2025-11-12 18:11:03

Why MVVM Feels Clunky With Compose MVVM grew up with XML and two-way data binding. Compose flipped the model: the UI is a function of state. That mismatch shows up in common pain points: Scattered state. Multiple LiveData/Flows (loading, items, error, searchQuery, pagination…) mutate independently. Compose recomposes at odd times, and you start sprinkling remember { mutableStateOf(...) } to “patch” glitches. The “SingleLiveEvent” saga. One-off actions (toasts, navigation, snackbars) don’t belong in your steady UI state, so teams hack in special event wrappers that break on configuration change or process death. Implicit writes. With two-way binding (or eager observers), it’s not obvious who changed what. You hunt bugs by grepping for setters. Brittle tests. It’s hard to reproduce a bug when the state can be mutated from multiple pathways and observer races. What MVI Brings to the Table Model-View-Intent (MVI) is just a strict recipe for unidirectional data flow:

How to Map PostgreSQL JSON Data Types in Java Using asentinel-orm

Aggregated on: 2025-11-12 17:11:04

It isn’t seldom when software products need to easily and efficiently manage the direct storage and handling of JSON content directly into the underlying database. The purpose of this article is to exemplify how such tasks can be conveniently accomplished via the asentinel-orm, a lightweight ORM tool built on top of Spring JDBC, which possesses most of the features one would expect from such a project. We will start by defining a simple entity that contains a JSONB column. Then, we will configure a sample application that uses the asentinel-orm to handle its data access towards a PostgreSQL database that stores such entities. Lastly, we will exemplify and emphasize how the actual JSON data can be queried and stored properly.

From Developer to AI Teammate: Building an Agentic Automation Prototype

Aggregated on: 2025-11-12 16:11:03

The Problem: Developer Workflows Are Still Too Manual Despite CI/CD, containerization, and mature DevOps practices, developers still spend hours on repetitive, low-value tasks — restarting services, parsing logs, or cross-checking configurations. Common examples include:

A Developer's Guide to Mastering Docker Networking Concepts

Aggregated on: 2025-11-12 15:11:04

As developers, our first success with Docker is typically running a single container and accessing it through localhost. While this is a solid beginning, the true strength of containers emerges when you start running multi-container applications. This is also where most developers face challenges. You have a web application in one container and a database in another. How do they communicate?

GitLab CI/CD for Tenant-Specific ML Governance: Automating Model Registries in Databricks Unity Catalog on AWS

Aggregated on: 2025-11-12 14:11:03

To bring automation to machine learning operations (MLOps) in the Databricks Unity Catalog, linking up GitLab CI/CD pipelines is revolutionizing the way we govern our data. As of September 2025, the community-driven examples and updates from Databricks show that companies can use GitLab to create isolated model registries for individual tenants, run compliance checks, and deploy ML workflows in a declarative style. By bridging gaps in traditional data platform operations, this setup brings us one step closer to scalable, secure ML deployments with much less manual intervention.

AI Code Refactoring: Principles, Techniques, and Benefits

Aggregated on: 2025-11-12 13:11:03

Coders will tell you that dealing with messy code is a pain. But starting over is even more of a headache. Luckily, AI can help clean up your code, making it easier to read, faster, and ready for updates. It utilizes machine learning to identify errors, remove unnecessary code, and update your code to the latest standards. This saves time and helps you avoid errors. So, whether you're fixing old systems or just dealing with tech debt, AI can help. Let's explore how AI refactors code, the primary methods the employ, and the benefits they offers to coders and companies.

The DSPM Paradox: Perceived Controls for an Uncontrollable Data Landscape

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

Data is always on the move. Data flows across multiple interconnected systems, creating an expanded attack surface that spans Slack messages, browser-based AI tools, cache folders, and distributed cloud workloads. Security teams have long tried to keep up. While traditional tools, such as firewalls, SIEMs, and DLPs, have evolved to address dynamic data flows, they face challenges in environments where data constantly moves across platforms. These tools look at networks. They watch for strange logins. They inspect files as they are being sent in and out of a system. However, the core challenge remains: effectively monitoring and protecting data that is distributed across numerous touchpoints.

A Growing Security Concern: Prompt Injection Vulnerabilities in Model Context Protocol Systems

Aggregated on: 2025-11-11 20:26:03

Most companies set up their AI document assistant the same way: give it access to the repository, then rely on it to filter results based on user permissions. When someone asks: "For the security audit, list all documents containing 'confidential' in the title."

Debugging Performance Regressions in High-Scale Java Web Services: A Systematic Approach

Aggregated on: 2025-11-11 19:26:03

High-scale, real-time services live under unforgiving economics. Ad tech and similar platforms push millions of requests through Java web services, where a handful of milliseconds either unlock profitable throughput or sink margins under excess compute. Regressions in latency and resource usage rarely arrive with sirens; they slip in alongside routine refactors, dependency upgrades, or subtle shifts in traffic shape. What looks like a harmless tweak in a unit test can magnify into elevated CPU, long garbage collection pauses, or thread starvation once it meets production load. The work of debugging these regressions is less about isolated heroics and more about following a disciplined trail from symptoms to causes, correlating signals across the JVM, and validating fixes under real heat. Industry-wide, the cost of performance regressions is notoriously high, though rarely measured with public precision. In environments like ad tech, where margins are directly tied to throughput and latency, even a minor, sustained performance degradation can translate to significant operational expense and lost revenue. Teams that adopt systematic debugging and profiling practices don't just resolve incidents faster; they build a culture of performance awareness that prevents regressions from being deployed in the first place. The resulting efficiency gains, often manifesting as reduced cloud spend or the ability to handle more traffic on the same hardware, directly improve the bottom line. This article examines how that discipline works in practice for Java services running on Tomcat.

Formae and PKL: Revolutionizing Infrastructure Automation

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

As an automation engineer and architect, I have been using IaC tools like Terraform for years. Recently, I started exploring and learning Pulumi, an Infrastructure as Code platform that lets developers and teams create, deploy, and manage cloud resources using familiar programming languages. As part of my weekend reading, I came across a new announcement about an open-source platform called Formae. In this article, let's learn about Formae and how it uses PKL, a configuration-as-code language. Infrastructure-as-code has transformed how we manage cloud resources, yet fundamental challenges persist: state file corruption, drift detection complexity, and the painful process of codifying existing infrastructure. Enter Formae, an open-source platform launched in October 2025 by Platform Engineering Labs, that challenges these conventions by leveraging Apple's PKL configuration language and introducing a stateless, auto-discovering approach to infrastructure management.

Gatherers in Java: What They Are and Why They Matter

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

Java 8, released more than a decade ago, is a major milestone. With this version, Java brought a fundamental shift from only being an object-oriented programming (OOP) to a combination of OOP and functional programming (FP) as well. To achieve this, Java 8 came in with support of lambdas, stream APIs, etc., as core language features. Stream API is influenced and modeled after the collection pipeline. A typical stream has three stages, viz., source, intermediate operations, and terminal operations.

Why Agility Matters

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

TL; DR: Why Agility Matters What if your organization’s “Agility” dysfunction isn’t an implementation problem but a missing-conditions problem that switching to, say, a product operating model cannot solve? This article identifies the success factors for agility that are absent in your organization. It gives you concrete Monday-morning actions to test what’s actually possible within your sphere of influence to drive change, because agility matters. Does Agility in Your Organization Feel Like This? Let me guess: You have sat through the training. You know the “ceremonies.” Your organization proudly calls itself “agile,” while every meaningful decision gets made three levels above you. Your Retrospectives generate action items that vanish into management theater. Your Daily Scrums are status reports for people who never show up. The product roadmap was decided before your team existed.

Creating an MCP Server With Spring AI

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

In this blog, you will learn how to create a Model Context Protocol (MCP) server using Spring AI. You will see how little effort it takes to create your own MCP server. Enjoy! Introduction Model Context Protocol provides a standardized way to connect large language models (LLMs) to different kinds of data sources and tools. The word standardized is very important in this sentence. This means that integration with data sources and tools becomes much easier than before. Besides that, MCP servers enhance your LLM with extra knowledge or extra functionality, making it an even more powerful assistant. Imagine you can ask an LLM to book a holiday for you.

Decentralized Identity Management: The Future of Privacy and Security

Aggregated on: 2025-11-11 14:41:03

The average person juggles accounts with varying levels of security. Login fatigue may lead us to recycle passwords or trust personal information to dubious companies. There is also the ever-looming threat of data breaches, social engineering attacks, and brute force takeovers. Traditional authentication models force users to give their information to a vulnerable centralized storage. Users surrender control, trusting third-party organizations to shoulder the security risks and liability for our data.

WebRTC at Scale: Docker, GPU Nodes, Prometheus, and Latency-Based Autoscaling on GKE

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

Real-time apps are now part of daily life. We use them for video calls, live classes, online games, and health checkups. These apps need to respond fast. Even a small delay in sound or video makes them hard to use. WebRTC is the open standard that powers most of these apps. It runs in browsers and on mobile devices, allowing direct audio, video, and data connections. But scaling WebRTC apps in the cloud is tricky.

Kubernetes Guardrail Extension: Bringing Compliance-as-Code to Your Browser

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

Why Developers Needed This Every DevOps engineer knows how fragile Kubernetes manifests can be. A single missing resourceLimit, an unpinned container image, or an accidental privileged: true can create serious performance, security, or compliance issues. The problem isn’t awareness — it’s timing. Most existing tools surface feedback only after commit, once CI/CD scans or admission controllers run. By that point, the feedback loop has stretched into hours.

Docker Security: 6 Practical Labs From Audit to AI Protection

Aggregated on: 2025-11-10 20:11:02

Docker containers share the host kernel. A single misconfigured container can expose sensitive data, provide root access to the host, or compromise the entire infrastructure. This guide provides six practical labs that work on Linux, macOS, and Windows. The examples use open source tools and demonstrate both vulnerable and secure configurations. Each lab is hands-on and runnable. All code and detailed instructions are available on GitHub: https://github.com/opscart/docker-security-practical-guide

How Tool-Call Observability Enables You to Support Reliable and Secure AI Agents

Aggregated on: 2025-11-10 19:11:02

Companies are rapidly deploying AI agents to support internal processes and their products. But as these agents gain autonomy, how do you monitor systems that make decisions on their own? Traditional application monitoring wasn't designed for AI agents. You can track API latency and error rates, but that tells you nothing about whether an agent called the right tool, passed valid parameters, or accessed data it shouldn't have.

Event-Driven Architecture Patterns: Real-World Lessons From IoT Development

Aggregated on: 2025-11-10 18:11:02

Why This Matters for Back-End Developers I spent six years working with microservices before I truly understood event-driven architecture. Building a real-time IoT system with more than 50 distributed nodes, using asynchronous messaging and meeting latency goals under 100 milliseconds, made it all click for me. In this article, I’ll share practical patterns from real production experience that you can use for microservices, stream processing, and distributed systems. These ideas are useful whether you’re building IoT solutions, APIs, or data pipelines.

GitOps-Backed Agentic Operator for Kubernetes: Safe Auto-Remediation With LLMs and Policy Guardrails

Aggregated on: 2025-11-10 17:11:02

Kubernetes is already the master of reconciliation: if a pod dies, the scheduler restarts it; if a node disappears, workloads reschedule. But what happens when the failure is due to misconfiguration, resource limits, or novel runtime errors? Traditional controllers keep retrying without real problem-solving. This is where Agentic AI Operators step in. Instead of blindly retrying, they analyze logs, propose a fix, run it through policies, and deliver it safely via GitOps.

Hudi vs. Delta vs. Iceberg: How to Choose the Right Lakehouse Table Format

Aggregated on: 2025-11-10 16:26:02

Why This Matters A few years ago, data teams had to make a tough choice: the flexibility of a data lake or the reliability of a data warehouse. Now, the lakehouse architecture bridges that gap, combining cheap object storage with transactional guarantees, schema management, and even time travel. But here’s the catch — none of this works without a table format to organize the chaos of raw files. If you’ve ever tried to manage updates, deletes, or schema changes in a plain S3 bucket, you know the pain. Table formats like Apache Hudi, Delta Lake, and Apache Iceberg solve this by adding a metadata layer that turns files into structured, queryable tables. They all promise ACID transactions, schema evolution, and scalability, but they’re not interchangeable. The right choice depends on your workload, team, and long-term goals.

Regression Analysis for Time Series Data: Models and Applications

Aggregated on: 2025-11-10 15:26:02

The global big data and business analytics market is projected to grow to $961 billion by 2032. A substantial portion comprises analytics software, most of which supports time series regression analysis. This analytics method is widely used across business domains and is helpful in most forms of planning, forecasting, monitoring, and modeling. That’s exactly why it’s useful to be well-versed in forms of regression analytics and know how it can be used in your business area. In this blog post, you’ll find out about regression analysis of time series and its difference from standard regression analysis. Moreover, you’ll learn how to conduct a regression analysis in clear steps. You’ll also review business use cases of using data regression analysis, explore challenges and limitations, and find out whether this analysis method can work for your business.

AI-Driven Generative Design: Automating Architectural Layouts

Aggregated on: 2025-11-10 14:26:02

Architectural design historically has been a human-centric, iterative process: sketch, evaluate, refine. But as computational power and AI algorithms evolve, a new paradigm is emerging — generative design — where software assists in producing (or even automating) layout decisions. In an AI-driven generative design system, one does not just “draw” rooms or corridors; instead, one defines constraints (e.g., adjacency, circulation, lighting, structural rules), and the system proposes multiple candidate layouts, often optimizing for multiple objectives (area utilization, daylight access, egress paths, energy efficiency).

There’s No API for Operational Chaos: Lessons from Scaling Acquired SaaS

Aggregated on: 2025-11-10 13:26:02

The deal closed on Friday. By Monday, the acquired company’s CI/CD pipeline had triggered an outage during onboarding. No one knew where the deployment scripts were, and half the infrastructure was still named after an ex-employee’s dog. This is not edge case material — it is standard operating procedure in the world of permanent capital SaaS.

The Exponential Price of Neglecting Modern Web Application Testing

Aggregated on: 2025-11-10 12:26:02

The True Challenge of Modern Web App QA The complexity of today's web applications has fundamentally changed the nature of software quality assurance. We've moved far beyond the simple, static pages of the past. Today's applications are vast, intricate ecosystems defined by: Microservices and distributed architectures running in the cloud Components deployed at the edge Real-time data feeds and APIs from third parties User interfaces built with multiple, deeply nested layers Each of these interconnected components introduces unique quirks, hidden dependencies, and potential failure points. Despite this exponential increase in complexity, testing often remains an under-resourced afterthought — a simple box to tick just before a major release.

Kubernetes v1.34: Enabling Smarter Traffic Routing With PreferSameNode and PreferSameZone

Aggregated on: 2025-11-07 20:26:01

Kubernetes has steadily evolved into an industry standard for container orchestration, powering platforms from small developer clusters to hyperscale AI and data infrastructures. Every new release introduces features that not only make workloads easier to manage but also improve performance, cost efficiency, and resilience. With the v1.34 release, one of the standout enhancements is the introduction of traffic distribution preferences for Kubernetes Services. Specifically:

Beyond Dashboards: How Autonomous AI Agents Are Redefining Enterprise Analytics

Aggregated on: 2025-11-07 19:26:01

The field of data analytics is going through the biggest change since business intelligence platforms were first introduced. Agentic AI — "intelligent systems that perceive, reason, plan, and act on their own" — is changing the way businesses get information and make choices. Generative AI only responds to prompts, but agentic systems work on their own, going after complex goals with little human oversight. They also have persistent memory and can adapt to new situations. This change marks a shift from reactive analytics to proactive intelligence. Companies are moving away from static dashboards and manual analysis cycles in favor of self-driving systems that monitor data, find insights, and make decisions. The market is expected to be worth $196.6 billion by 2034, and 62% of executives expect a return on investment of more than 100%. This change is transitioning from small-scale tests to large-scale deployments, which significantly impact how businesses operate.

Prompt Engineering vs Context Engineering

Aggregated on: 2025-11-07 18:11:01

As AI integration becomes standard in modern applications, developers face a very critical decision: How do we effectively communicate with large language models (LLMs) to get reliable and accurate results? The answer lies in understanding two distinct but often confused approaches: prompt engineering and context engineering. While these terms are frequently used interchangeably, they represent fundamentally different strategies for working with AI systems. Understanding their differences is important for building robust and production-ready applications that leverage LLMs effectively.

Understanding Proxies and the Importance of Japanese Proxies in Modern Networking

Aggregated on: 2025-11-07 17:11:01

In the current digital age, which largely revolves around the use of the internet, privacy and security, as well as access to the whole world, are some of the main concerns for individuals and businesses. One of the most effective methods to achieve these objectives is the use of proxy servers. Proxy servers essentially change your IP address and reroute your online traffic. Many types of proxies are available, but Japanese proxies are considered to be the best because they are not only stable but also have very low latency and offer you excellent regional access.

How Does a Scrum Master Improve the Productivity of the Development Team?

Aggregated on: 2025-11-07 17:11:01

The role of a Scrum Master is to establish Scrum, and the Scrum Master is accountable for the Scrum Team’s effectiveness. Thus, it is quite tempting to ask how a Scrum Master can help improve the productivity of the development team. But, in a complex working environment like software development, productivity is often not the right measure to showcase all the complexities of software developers’ knowledge work. In simple working environments, productivity means a ratio of output to input. The traditional idea is to know how much is achieved (output) with a given amount of resources (inputs), largely in numbers, and the focus is on maximizing the output. That’s why, in traditional project management of software development projects, stakeholders evaluate the development team’s productivity based on the lines of code. Or, even today in Agile project management, stakeholders with a traditional mindset ask for the number of story points per iteration, known as Sprint Velocity.

Production-Grade React Project Structure: From Setup to Scale

Aggregated on: 2025-11-07 15:26:01

Do you struggle to organize your React project folder structures? The right folder organization does more than just keep things tidy. The development efficiency and team collaboration of your project depend on it. A solid folder structure makes the project look clean and speeds up scalability, collaboration, and debugging. The way developers organize files and components is vital to the long-term success of any React project. React applications are easier to scale, debug, and onboard new team members through a clean folder structure and clear system design. The best folder structure practices help developers find files and components quickly, which reduces the time spent searching through the code. The consistent folder structure of your application prevents chaos and confusion as it grows. Team members work together more smoothly, with fewer merge conflicts and improved productivity.

Laravel + Next.js Integration Guide (Real-World Setup, 2025)

Aggregated on: 2025-11-07 14:26:01

The goal is simple: build a secure app that uses SSR or SSG for SEO, CSRF-safe session cookies, clear CORS rules, and a smooth deploy to Vercel plus Forge or Vapour. By the end, readers will know how to wire Laravel routes and controllers, fetch from Next.js with credentials, handle CSRF and sessions, and deploy with confidence. A short troubleshooting list covers common 401, 419, and CORS issues so teams do not get stuck.

Understanding the Idle-Timer

Aggregated on: 2025-11-07 13:26:01

What is an Idle Timer? An idle timer is a software component that tracks user inactivity or idleness within an application or website. It measures the duration of time a user remains inactive—no mouse movements, keyboard inputs, or touch events—and triggers specific actions after a predefined idle period, such as logging out the user, showing a warning, or saving work. What Problems Does an Idle Timer Solve? Idle timers are essential in many scenarios, including:

Workload Identities: Bridging Infrastructure and Application Security

Aggregated on: 2025-11-07 12:26:01

Infrastructure security has long been about protecting networks, hosts, and cloud platforms. Application security focuses on securing APIs, data flows, and business logic to protect critical assets. Both approaches are critical, but they can’t provide complete protection on their own. When isolated from each other, there is a higher risk that attackers can exploit the security gaps in either layer, which is why workload identities should be employed to serve as a bridge that unifies both layers. The Two Security Worlds: Infrastructure vs. Application Infrastructure security is about protecting the foundation, including measures such as network segmentation, least-privilege identity and access management (IAM) roles, container isolation, and applying zero-trust principles at the infrastructure level. Application security works higher up in the stack, closer to data and user interactions. It deals with authentication, authorization, token management, session handling, and API protection.

A Beginner's Guide to Docker Compose

Aggregated on: 2025-11-06 20:11:00

The constant need to run docker run in multiple terminals for managing multi-container setups. If you’re new to Docker, you’ve likely already discovered the docker run command that makes it easy to run a single container. However, what happens if your app requires a database? A cache? Before you know it, you’re dealing with a terminal tab nightmare:

Unlocking Modernization: SUSE Virtualization on Arm64 With Harvester

Aggregated on: 2025-11-06 19:11:00

As the number of data centers and their size grow worldwide, requiring increased efficiency, scalability, and agility from IT infrastructure, the convergence of virtual machines (VMs) and cloud-native technologies is crucial for success. A recent conversation between Dave Neary of Ampere Computing and Alexandra Settle, Product Manager for SUSE Virtualization, highlights a significant step forward: the general availability of SUSE Virtualization for Arm64 architecture, and Harvester’s pivotal role within SUSE’s ecosystem. This white paper summarizes their discussion, highlighting how SUSE is empowering organizations to modernize infrastructure with energy-efficient, high-performance solutions.

A Developer's Guide to Sentiment Analysis With Naive Bayes and Python

Aggregated on: 2025-11-06 18:11:00

Sentiment analysis is a powerful tool for understanding customer feedback, social media comments, and product reviews. It allows us to programmatically determine whether a piece of text is positive, negative, or neutral. While complex models like Transformers (e.g., BERT) often grab the headlines, the classic Multinomial Naive Bayes classifier remains a surprisingly effective, efficient, and interpretable baseline, especially for text-based tasks. In this guide, we'll walk through a complete sentiment analysis project using Python and Scikit-learn. We'll cover:

A Beginner's Guide to Essential Commands to Fix Container Setup Issues

Aggregated on: 2025-11-06 17:11:00

You followed the tutorial. You ran Docker Run. And... nothing. The container exited immediately. Or maybe it is running, but localhost just shows “This site can’t be reached.” We’ve all been there. When you’re new to Docker, a failing container can feel like a sealed black box. You know something is wrong inside, but you have no idea how to look. In this quick guide, I’ll show you the five essential commands to open that box, see what’s happening, and fix your broken containers.

A Practical Guide to Modernizing Data Serving Architectures Using DBSQL

Aggregated on: 2025-11-06 16:11:00

If you’ve ever built analytical dashboards, chances are you’ve worked with the old “batch-load-to-RDS” pattern, where we load the data into RDS from a batch process and read from that operational data store, such as AWS RDS or other databases. We certainly did in our case — and for a while, it served us well. Our applications pulled data from a lakehouse like Snowflake or Delta Lake, transformed it in AWS Glue, and loaded it into Amazon RDS. The RDS database powered Lambda APIs that fed dashboards and front-end apps.

Optimizing Write-Heavy Database Workloads for Low Latency

Aggregated on: 2025-11-06 15:11:00

Write-heavy database workloads bring a distinctly different set of challenges than read-heavy ones. For example: Scaling writes can be costly, especially if you pay per operation, and writes are 5X more costly than reads Locking can add delays and reduce throughput I/O bottlenecks can lead to write amplification and complicate crash recovery Database backpressure can throttle the incoming load While cost matters quite a lot, in many cases, it’s not a topic we want to cover here. Rather, let’s focus on the performance-related complexities that teams commonly face and discuss your options for tackling them.

Tactical Domain-Driven Design: Bringing Strategy to Code

Aggregated on: 2025-11-06 14:11:00

In the previous article, I discussed the most often overlooked aspect of Domain-Driven Design: the strategic side. When it comes to software development, teams tend to rush toward code, believing that implementation will clarify the domain. History shows the opposite — building without understanding the underlying reason or direction often leads to systems that are technically correct but conceptually wrong. As the old Latin root of strategy (strategos, “the art of the general”) suggests, the plan must precede the movement. Now that we’ve explored the “why” and “what,” it’s time to turn to the “how.” Tactical DDD represents this next step — the process of transforming a well-understood domain into expressive, maintainable code. While strategic design defines boundaries and fosters a shared understanding, tactical design brings those ideas to life within each bounded context.

The JVM Pause That Wasn't: A War Story

Aggregated on: 2025-11-06 13:11:00

In high-performance computing, we are trained to hunt for bottlenecks in our code, our algorithms, or our infrastructure. But my favorite bug was not in any of those. It was an invisible interaction between the JVM's garbage collector and the server's disk, resulting in 15+ second, stop-the-world (STW) pauses on a service handling millions of requests per second. The Mystery: The 503 Spikes I was working on a large-scale Java service handling millions of user requests per second. The system was designed for extreme throughput, but we were plagued by intermittent spikes in load balancer timeouts, causing 503 responses to be returned to the users.

Master Production-Ready Big Data, Apache Spark Jobs in Databricks and Beyond: An Expert Guide

Aggregated on: 2025-11-06 12:11:00

This iteration is based on existing experience scaling big data with Apache Spark workloads and uses more refinements by still preserving the eight most important strategies but moving high-value but less important strategies — such as preferring narrow transformations, applying code-level best practices, leveraging Databricks Runtime features, and optimizing cluster configuration — to a Miscellaneous section, thereby not losing focus on impactful areas such as shuffles and memory, but still addressing them thoroughly. Diagrams for in-phased insights and example code can be completely executed in Databricks or vanilla Spark sessions, and for all of these to be worth your time, the application will yield unbelievable performance benefits, often in the range of 5–20x in real-world pipelines.

Bridging the Divide: Tactical Security Approaches for Vendor Integration in Hybrid Architectures

Aggregated on: 2025-11-05 20:11:00

Security architecture in hybrid environments has traditionally focused on well-known concepts such as OWASP vulnerabilities, identity and access management, role-based access control, network security, and the principle of least privilege. Best practices like secure coding and incorporating SAST/DAST testing into CI/CD pipelines are also widely discussed. However, when organizations operate in a hybrid model — running workloads both on-premises and in the cloud — while also integrating with vendor-managed cloud solutions, a different set of security design considerations comes into play. These scenarios are not uncommon, yet they are rarely highlighted in the context of secure solution implementation involving vendor software in hybrid environments.

Build a LangGraph Multi-Agent system in 20 Minutes with LaunchDarkly AI Configs

Aggregated on: 2025-11-05 19:11:00

Overview Build a working multi-agent system with dynamic configuration in 20 minutes using LangGraph multi-agent workflows, RAG search, and LaunchDarkly AI Configs. Part 1 of 3 of the series: Chaos to Clarity: Defensible AI Systems That Deliver on Your Goals

JPlus: A Modern Java Superset Language

Aggregated on: 2025-11-05 18:11:00

JPlus is a Java superset language running on the JVM that enhances developer productivity while staying fully compatible with the Java ecosystem. Why Support JPlus? JPlus fills a unique gap in the Java ecosystem: