News Aggregator

Building a Modern Data Platform That Delivers Real Business Value

Aggregated on: 2025-07-23 20:14:25

Data modernization is a strategic endeavor that transforms the way organizations harness data for value creation. It involves adopting innovative approaches in terms of accessibility, governance, operations, and technology, typically centered around modern cloud architectures. This transformation is not limited to technology alone but extends to rethinking people and processes within an organization. At its core, data modernization aims to facilitate easier and more effective use of data through enhanced governance structures, operational practices, and technological frameworks. The objective is to ensure that data ecosystems evolve to support the growing demand for timely, accurate, and actionable insights. The strategic importance of this transformation lies in its ability to unlock new business opportunities, improve decision-making, and strengthen competitive positioning by making data an accessible and valuable asset across all levels of the enterprise.

Configuring Model Context Protocol (MCP) With Amazon Q CLI

Aggregated on: 2025-07-23 19:14:25

Amazon Q CLI is a next-generation developer tool that brings IDE-style autocomplete and agentic capabilities to your terminal. I’ve spent a lot of time writing about this powerful tool, so I was especially excited when v1.9.x was released in May—it introduced support for the Model Context Protocol (MCP) for tools use. What is Model Context Protocol (MCP)? If you have not heard about MCP (where have you been?) then check out my colleague's post on this, Standardizing AI Tooling with Model Context Protocol (MCP)

Undocumented Java 16 Feature: The End-of-File Comment

Aggregated on: 2025-07-23 18:29:25

While working on some code where I wanted to obscure parts of it using Unicode escapes instead of the actual source, I accidentally stumbled upon an undocumented feature that’s been around since Java 16: what I call the end-of-file comment. In Java, we typically have three types of comments:

The Golden Signals of Monitoring

Aggregated on: 2025-07-23 17:29:25

This article describes "Golden Signals," how they can provide a high-level health overview and performance of your service. These signals are very useful to understand the state of any service and can help identify potential issues. They can be used as a good starting point to implement monitoring strategies specific to your workload. If any of these signals are out of the norm, it is a strong indicator that something needs attention. Here's a breakdown of each signal and how it can be used as a starting point for monitoring your services:

Beyond the Handoff: How Product and Engineering Teams Are Redefining Collaboration

Aggregated on: 2025-07-23 16:14:25

The modern digital product team gathers in a glass-walled conference room at a Seattle technology firm. Sitting around the table are the product manager, three engineers, a UX designer, and a data analyst. They're not debating a completed feature or fighting about a product roadmap. Instead, they're engaged in what increasingly organizations call "product discovery"—a collaborative exploration of user problems before a line of code is written. This moment, all too familiar to top tech organizations, marks a sea change in the way that product and engineering teams interact. The old model of handoffs—product folks defining requirements, engineers building out—has its days numbered.

[Part-3] Text to Action: Adding Voice Control to Your Smart Calendar

Aggregated on: 2025-07-23 15:14:25

Welcome to the third installment of our “Text to Action” series, where we’re building intelligent systems that transform natural language into real-world actions using AI. In "[Part-1] Text to Action: Build a Smart Calendar AI Assistant," we established our foundation by creating an Express.js backend that connects to Google Calendar’s API. This gave us the ability to programmatically create calendar events through exposed API endpoint.

Building Resilient Event-Driven Applications Using Temporal

Aggregated on: 2025-07-23 14:14:25

Temporal is an open-source durable workflow engine that allows developers to write fault-tolerant, long-running, and stateful applications using simple code. This guide walks you through setting up Temporal locally, writing your first workflow, and running it end-to-end using the TypeScript SDK. Problem: Distributed Systems Are Complex to Manage Building modern software systems isn’t getting any easier. As companies move to the cloud and break their applications into microservices, the promise is agility and scalability. But what developers actually end up with is a tangled web of APIs, message queues, retry logic, and fragile cron jobs. A single user action — like placing an order or submitting a loan application — can trigger dozens of interconnected processes that need to happen in the right order, with the right timing, and ideally, never fail. But they do fail. Networks timeout. Services go down. Scheduled jobs disappear silently. And every failure is another patch, another workaround, another sleepless night for engineers. Writing and maintaining the glue code to handle these failures gracefully is frustrating, repetitive, and hard to test. It’s like trying to build a house of cards in the middle of a windstorm — one shaky piece and everything crashes. That’s the harsh reality of distributed systems today.

Designing Retry-Resilient Fare Pipelines With Idempotent Event Handling

Aggregated on: 2025-07-23 13:14:25

In modern flight booking systems, streaming fare updates and reservations through distributed microservices is common. These pipelines must be retry-resilient, ensuring that transient failures or replays don’t cause duplicate bookings or stale pricing. A core strategy is idempotency: each event (e.g., a fare-update or booking command) carries a unique identifier so processing it more than once has no adverse effect. In practice, this means assigning a unique event ID or idempotency key to each fare request. For example, an airline booking API might attach a unique request token so that if a user’s retry comes through, the service recognizes and ignores it. This prevents duplicate bookings if, say, a payment call times out and is retried. Similarly, pricing events should include a unique price-update ID. Downstream consumers (cache updaters, booking services, analytics) record these IDs (in a database or distributed cache) and skip any event with an already-seen ID.

Automating a Web Form With Playwright MCP and MySQL MCP

Aggregated on: 2025-07-23 12:14:25

Combining browser automation with database interactions opens up powerful possibilities. Imagine fetching user data from a database and using it to populate a web form automatically — no manual scripting required. With Playwright MCP (Model Context Protocol) and MySQL MCP, you can achieve this seamlessly. In this blog, I’ll walk you through how to integrate these tools to fetch data from a MySQL database and use it to fill in the checkout in the Web Form. By the end, you’ll have a working automation setup that’s both efficient and scalable.

Software Engineering Trade-Offs: Why We Cannot Build the Perfect

Aggregated on: 2025-07-23 11:14:25

In a couple of my last articles, I emphasized the importance of different software engineering trade-offs, for example, here. I have been trying to point out that focusing on maxing out just one trait can cause problems in others. I believe that the main part of our job as software engineers should be to min-max different software engineering trade-offs and even the trade-offs of different combinations of trade-offs. Software engineering is the art of constantly balancing all these things. Below you can find eight trade-offs, plus their pros and cons. I will also share a very simple framework for navigating software engineering trade-offs.

Implementing ΔE-ITP in Python: Accurate Color Difference Metric for Image Processing

Aggregated on: 2025-07-22 20:29:27

Image difference analysis is essential in computer vision, graphics processing, and media quality assessment. Whether you're evaluating compression artifacts, detecting subtle regressions, or comparing perceptual similarity, various metrics help quantify differences between images. This article discusses popular image difference metrics, their pros and cons, and recommends ΔE-ITP, a modern, perceptually optimized color difference metric. We’ll also look at how to implement DeltaE ITP—including transforming images from SDR, HLG, and PQ into ITP—and interpreting the reported color differences effectively.

More Than Just Buttons: A Frontend Engineer's Exploration of Accessibility Frameworks

Aggregated on: 2025-07-22 19:29:25

Accessibility is often treated as actions that have to be implemented like checkboxes. In this scenario, contrast, alt images, and tagging will create structure. However, in real-world scenarios that involve advanced frontend systems, accessible interfaces are products of architectural decisions. In a practical scenario, as a senior engineer, there are multiple factors of influence apart from the coding aspects. The impact radiates to the workflows of development, component systems, and patterns, which are used or created by others. If there is no strategy incorporated during construction for accessibility, there will be difficulties or bridge gaps that need to be crossed when trying to patch this problem later on, causing multiple regressions.

Implementing Least Privilege in AWS IAM: Principles, Practices, and Automation

Aggregated on: 2025-07-22 18:14:25

The principle of least privilege is fundamental to securing cloud environments by ensuring that identities have only the permissions necessary to perform their tasks. In AWS Identity and Access Management (IAM), sticking to the principle of least privilege is one of the smartest ways to reduce the chances of unauthorized access, data leaks, or someone getting more permissions than they should. This paper dives into how to apply the principle of least privilege in AWS IAM, covering key best practices, common challenges, and ways to automate policy management. It also highlights AWS tools that help with analyzing, validating, and enforcing IAM policies at scale. Introduction As organizations increasingly adopt AWS cloud services, managing access control becomes a critical aspect of maintaining a secure and compliant environment. IAM lets you control exactly who can access which resources in your AWS environment and under what conditions they can do it. However, without careful policy design, users and services may accumulate excessive permissions, thereby violating the principle of least privilege and introducing security risks. This paper outlines approaches for achieving least privilege in AWS IAM and highlights automation techniques that enhance efficiency and accuracy in policy management.

Building a Multi Tenancy Platform Using Camunda

Aggregated on: 2025-07-22 17:14:25

Camunda is an open-source workflow and decision automation platform for the modeling, execution, and monitoring of business processes following BPMN (Business Process Model and Notation), DMN (Decision Model and Notation), and CMMN. It is used for the orchestration of complex workflows among microservices, APIs, human tasks, and external systems. Camunda is embedded by developers into their applications to automate business logic, monitor process state, and bring operational transparency. Camunda enables companies to orchestrate processes across people, systems, and devices to tame complexity continuously and drive efficiency. A common visual language enables business and IT teams to collaborate seamlessly in designing, automating, and optimizing end-to-end processes with the speed, scale, and resilience required to compete.

Agile-Based Fine-Tuning of AI Agents for Domain-Specific User Feedback Loops

Aggregated on: 2025-07-22 16:14:25

Since AI agents are becoming an inseparable part of various applications across financial, healthcare, customer service, and engineering domains, one issue remains at the forefront: how to keep models accurate, relevant, and aligned with the changing demands of users. Powerful standard pre-trained models usually fail to perform well in narrow tasks without a continuous tuning process. This has given impetus to Agile-based fine-tuning—a feedback-driven process in which AI agents are aligned through iterative, short cycles, similar to those used in agile software development (Tupsakhare, 2022). Such a strategy encourages constant change and step-by-step evolution, steered by actual user feedback loops. Agile Meets AI: A Synergistic Framework Agile practices focus on sprints, quick iterations, stakeholder comments, and unceasing delivery. This, together with the AI fine-tuning, becomes a dynamic process: gather user feedback, retrain or adjust the model, roll out the adjustments, repeat. An agile approach to AI systems could reduce time-to-market on model updates by 30% and maintain accuracy through a drift in the data (LinkedIn, 2024).

Why Microservices Teams Struggle to Ship Independently

Aggregated on: 2025-07-22 15:14:25

At a glance, the benefits of microservices seem obvious: independent teams can move faster, deploy more frequently, and scale systems more effectively. In theory, this architecture should unlock agility. But for many teams, that promise hasn’t materialized — not because their systems are flawed, but because their processes haven’t evolved in step. If your team still relies on heavy coordination for a single microservice change, waits days for staging access, or juggles PRs through slow, serialized pipelines, you may have a distributed system — but you’re still operating like a monolith.

Building a Proactive Cloud Environment Using AWS Monitoring

Aggregated on: 2025-07-22 14:29:25

Cloud applications need to run smoothly and reliably more than ever. Building a proactive cloud means monitoring your AWS resources continuously to detect and resolve issues before they hit users. With AWS’s monitoring tools, you can get real-time visibility, automate responses, and achieve optimal performance. This article will show you how to do that, combining strategic best practices with practical tips to help cloud architects, DevOps engineers, and CTOs keep their AWS infrastructure resilient and efficient.

Debugging Distributed Flight Search: What Logs Alone Won’t Tell You

Aggregated on: 2025-07-22 13:29:25

Modern flight-search systems juggle dozens of services — search APIs, fare engines, cache clusters, and partner gateways — all to assemble a single price quote in milliseconds. When something goes wrong (say, a price anomaly or missing fare), sifting through siloed logs can leave engineers blind. True visibility comes from observability: correlating logs with metrics and traces across the architecture. In practice, senior teams have learned that without request tracing and rich metrics, elusive faults in fare pricing often defy diagnosis. Here we describe a typical flight‐search flow, show why plain logging falls short, and share how Datadog-powered observability (metrics, tracing, correlation IDs, alerts) saves the day. We draw on anonymized incidents — intermittent mismatches, provider glitches, race conditions — to underscore practical lessons and concrete debugging strategies.

How to Create Loki Alerts via PrometheusRule Resource

Aggregated on: 2025-07-22 12:29:24

In modern observability stacks, log-based alerts are often more immediate and actionable than those based on metrics, especially when you're tracking down anomalies, security incidents, or sudden application failures. While tools like Loki simplify log aggregation, turning those logs into meaningful, automated alerts remains a challenge. In the world of metrics, many engineers are familiar with Prometheus and its PrometheusRule resource for Kubernetes. But what if you could apply that same flexible, declarative alerting model to Loki logs?

Lock-Free Programming: From Primitives to Working Structures

Aggregated on: 2025-07-22 11:29:24

Working with multiple threads is one of the most complex problems we may encounter in our daily work. When put against the wall of multithreading, most people right away reach out for blocking approaches. In Java, it takes the form of the synchronized keyword, or some other less painful mechanisms, like ReentrantLock. Locks are not the only option: Lock-free programming is also the way. In this text, I will show problems, techniques, and best practices related to Lock-Free Programming. I will also provide a real-life example of how to implement a Lock-Free stack. Besides, I will share common patterns on moving from Lock-Free to Wait-Free.

6 Ways AI-Enhanced Phishing Can Hijack Developer Workflows (and What to Do About It)

Aggregated on: 2025-07-21 19:29:24

Phishing is no longer just an inbox problem – it’s a full-fledged software development supply chain risk. Some 60% of breaches studied in the 2025 Verizon Data Breach Investigations Report involved the “human element,” with phishing and credential abuse topping the list. Phishing volume overall has increased by 4,151% since ChatGPT’s debut, according to SlashNext’s mid-2024 report.

Software Supply Chain Security Regulations From a DevSecOps Perspective

Aggregated on: 2025-07-21 18:29:24

Editor's Note: The following is an article written for and published in DZone's 2025 Trend Report, Software Supply Chain Security: Enhancing Trust and Resilience Across the Software Development Lifecycle. High-profile software supply chain attacks like SolarWinds, Log4j, and MOVEit highlight the urgent need to address the vulnerabilities caused by insecure software supply chains, prompting a decisive regulatory response. In the United States, entities like the Federal Trade Commission (FTC), the Computer Fraud and Abuse Act, and emerging state laws are already being used to penalize companies that contain or distribute vulnerable or malicious code. Meanwhile, Europe's Cyber Resilience Act and new Product Liability Directive impose stricter cybersecurity obligations, heavy fines, and even personal accountability for software-related harm.

Reasoning Models Explained: What They Are, How They Work, and When to Use Them Over Traditional LLMs

Aggregated on: 2025-07-21 17:14:24

If you’ve been closely following the evolution of AI in recent years, you are probably aware of the various significant leaps that have advanced the capabilities of the technology. From the development of LLMs to the generative pre-trained transformer (GPT) that delivered the generative AI offerings that have taken the world by storm, innovation in the field has ramped up significantly in a relatively short space of time. It is an incredible journey that has precipitated the fast realization of AI-led value and potential across industries—and that journey continues. The latest and most significant advancement comes in the form of reasoning models, which are, quite literally, bringing a more considerate element to the technology. Here’s how.

Implementing Data Analytics in Healthcare: A Hands-On Approach

Aggregated on: 2025-07-21 16:14:24

When I first started working with healthcare businesses, one thing struck me right away: there is tons of data, but most of it is a mess. It’s usually stored in separate systems, in different formats, and is hard to aggregate and analyze. Getting this kind of data into shape takes more than just loading it into a database and writing a few queries. In this article, I’ll walk through some of the real challenges in building healthcare data analytics solutions based on my experience and suggest ways to overcome them.

Designing and Operating Single-Tenant Architectures at Scale

Aggregated on: 2025-07-21 15:14:24

Single-tenant architecture plays a very important role when driven by regulatory/compliance needs, workload isolation to improve security posture and improved performance with dedicated resources. At the same time, these architectures are highly complex and hard to manage, specifically at scale. In this post, we’ll explore common deployment patterns for single-tenant resources, walk through architecture examples, and share automation and observability best practices to run such environments at scale. This post is platform-agnostic and applicable across off-premise or on-premise setups.

ArchUnit, Unit Testing The Architecture

Aggregated on: 2025-07-21 14:14:24

Enforcing a specific package structure or architecture is very important. Especially in Java, where some things must be public to work correctly or actually be available outside their package. ArchUnit is an open-source library that will help you whenever the compiler is not enough. All of the code examples from this article are available in my GitHub repo.

Today’s Platform Engineer Needs to Build AI-Ready Infrastructure

Aggregated on: 2025-07-21 13:14:24

The demands on today’s platform engineers are evolving at breakneck speed. What began as a natural evolution from DevOps has transformed into a distinct discipline with expanding responsibilities. Today’s platform engineers find themselves at an inflection point: they must not only manage increasingly complex cloud-native environments but also architect the foundation for Artificial Intelligence (AI) across the enterprise. This mandate requires rethinking infrastructure from the ground up to support the unique demands of AI workloads. It’s undeniable, however, that this role and shift are both necessary. Gartner states that by 2026, 80% of large software engineering organizations will establish platform engineering teams as internal providers of reusable services, components and tools for application delivery — up from 45% in 2022. By 2027, its adoption is expected to significantly impact how infrastructure and operations teams make technology choices, influencing more than half of their decisions.

1-Line IO in Java

Aggregated on: 2025-07-21 12:14:24

Here is a quick coding challenge for all Java developers: How many lines of code do you need to implement the following tasks, using the JDK and any library of your choice? (Rules of the game: Lines of code are counted using standard formatting, you need to close any opened resources, the code may throw IOExceptions, except if stated otherwise):

Log Spikes? No Sweat: How Top DevOps Teams Tame Bursty Workloads

Aggregated on: 2025-07-21 11:29:24

Taylor Swift ticket sales brought the entire platform to its knees… a crypto exchange saw 10x its regular traffic during a price swing… holiday deals dropped at midnight, and retail sites scrambled to keep up. These weren’t just high-traffic moments. They were log storms. For DevOps teams in bursty verticals like media, fintech, gaming, and retail, moments like these are make-or-break. Whether the spike is planned (like a product drop) or unpredictable (like an influencer mention), what happens behind the scenes is intense: logging pipelines can flood, ingestion costs can surge, and dashboards often freeze when you need them the most.

How to Expose IBM FS Cloud Container App to Public

Aggregated on: 2025-07-18 20:29:23

Are you looking for a way to expose your containerized applications to the internet without breaking compliance with IBM Cloud for Financial Services? This guide walks through how to do just that. It shows how to securely expose your apps using the IBM Cloud Framework for Financial Services, with a focus on the IBM Cloud Private Path Service. This service helps you route external traffic to private clusters over secure, compliant VPC-to-VPC connections.

Automation of IT Incident Reports Using Observability API and GenAI

Aggregated on: 2025-07-18 19:14:22

Recently, I was involved in automating the preparation of IT incident reports by integrating monitoring solutions and generative AI. This post is to share my observations during this ongoing exercise. It outlines how to leverage the power of the AI service to interpret alerts generated by an observability solution (in this case, eG Enterprise Suite). It utilized the Gemma AI model, running locally via Ollama for on-premise users, and the Llama-3.1 AI model with OpenAI for those with internet connectivity. The outcome of this exercise resulted in faster understanding of system issues and potential remediation steps. It automates the incident report creation by a Level 1 engineer.

AI-Driven Threat Hunting: Catching Zero Day Exploits Before They Strike

Aggregated on: 2025-07-18 18:14:22

Picture this: you're a cybersecurity pro up against an invisible enemy. Hidden in your network are zero-day exploits, which represent unknown vulnerabilities that await their moment to strike. The time you spend examining logs becomes pointless because the attack might already be causing harm. AI-driven threat hunting emerges as your most valuable new ally. Your network receives a real-time protection system through AI, which functions like a super-intelligent guard dog that detects threats. The following article explains how AI detects hard-to-find threats while demonstrating its real-world impact and providing Python-based instructions to create your own threat-hunting tool. Buckle up, let’s go! Why AI Matters in the Fight Against Zero Days Cybersecurity has come a long way from the days of simple virus scanners and static firewalls. Signature-based defenses were sufficient to detect known malware during the past era. Zero-day exploits operate as unpredictable threats that traditional security tools fail to detect. The technology sector saw Microsoft and Google rush to fix more than dozens of zero day vulnerabilities which attackers used in the wild during 2023. The consequences reach extreme levels because a single security breach results in major financial losses and immediate destruction of corporate reputation.

Burn that List: Smarter Use of Allowlists and Denylists in Multi-Tenant Systems

Aggregated on: 2025-07-18 17:14:22

In multi-tenant systems—whether you're managing an API gateway, identity platform, or SaaS product—access control is essential. Two of the most widely used tools for managing that access are allowlists and denylists. These mechanisms define who or what is permitted or rejected, helping isolate tenants, control risk, and enforce trust boundaries. But despite their simplicity, both lists can easily become operational liabilities if not carefully managed. This article explores real-world examples of allowlists and denylists, how to store and govern them, and why every list needs a plan to die. What Are Allowlists and Denylists? An allowlist is a list of explicitly approved entities—users, IPs, tenants, apps, or domains—that are permitted to access a resource. Everything else is denied by default. A denylist is the opposite: a list of explicitly blocked entities; everything else is allowed. In simple terms, allowlists implement default-deny behavior, while denylists implement default-allow with overrides. Choosing between them depends on the nature of what you're protecting, how dynamic your environment is, and how clearly you can define trust.

Building AI Agents Capable of Exploring Contextual Data for Taking Action

Aggregated on: 2025-07-18 16:14:22

Artificial intelligence is on a rapid evolutionary track, and the once awe-inspiring conversational capabilities of ChatGPT raise very few eyebrows these days. AI developers are shifting into a higher gear, and these days, the focus is all about agents. They’re building more advanced AI systems that transform large language models into thinkers, decision-makers, and action-takers, which can automate many kinds of work. To create an AI agent, the developer must assign an LLM to a specific role, assign it a clear goal to accomplish, and provide access to the necessary resources for the agent to fulfill its mission. When AI agents are focused on a clearly defined objective and can utilise APIs, web browsers, search engines, and databases as humans do, they can autonomously determine how to perform the assigned task.

How We Built a Smarter University Chatbot Using LLaMA2, AWS SageMaker, and RAG

Aggregated on: 2025-07-18 15:14:22

Every semester, university IT helpdesks are overwhelmed by repetitive queries from students — from course registration deadlines to tuition fees and campus services. Most existing systems either rely on outdated FAQs or rigid bots that can't adapt to multiple languages or real-time updates. Recognizing this gap, we developed a smarter, multilingual chatbot using LLaMA2, AWS SageMaker, LangChain, and Milvus, built around a Retrieval-Augmented Generation (RAG) pipeline. The Need for Smarter Campus Support Higher education institutions face growing demands to modernize how students interact with campus services. Traditional IT support models don’t scale well — especially when students ask the same questions repeatedly. Even chatbots built on rule-based logic often fall short due to poor language handling, limited context awareness, and rigid workflows. By mid-semester, helpdesk queues are swamped, leading to delays and user frustration.

Developing Secure REST API Using Spring Boot SSL Bundle Feature

Aggregated on: 2025-07-18 14:14:22

Secure Sockets Layer (SSL) is a key component in securing communication between systems, especially in layered or service-oriented architectures. In such environments, a typical Spring Boot service might expose a REST endpoint, which is then consumed by another Spring Boot service acting as a client. When a host service exposes a secure endpoint, it must ensure that only authorized services are allowed to connect.

Build AI Agents With MCP Server in C# and Run in VS Code

Aggregated on: 2025-07-18 13:14:22

Relatively newer AI agents based on large language models (LLMs), such as GPT-4o, Claude, or Gemini, are very proficient at general reasoning and answering broad questions. However, they usually struggle with domain-specific queries—like “Give me only Dell devices information”—because they don’t have access to proprietary, internal, or organization-level data. To answer these kinds of questions correctly, an LLM requires more than just a prompt: it needs contextual information made available through trusted internal sources. This article shows you how to build an AI agent that can access and use domain-specific context, thanks to the Model Context Protocol (MCP). It includes a code example of custom MCP Server creation and demonstrates how an MCP Host (in this case, VS Code) talks to the server and uses a Tool.

Practical Steps to Secure the Software Supply Chain End to End

Aggregated on: 2025-07-18 12:44:22

Editor's Note: The following is an article written for and published in DZone's 2025 Trend Report, Software Supply Chain Security: Enhancing Trust and Resilience Across the Software Development Lifecycle. The software supply chain has rapidly evolved into a critical vulnerability point and primary target for malicious actors. As we progress in 2025, organizations face an increasingly complex and dynamic threat landscape. This article offers a practical checklist for securing the software supply chain and clarifies the pivotal role of zero trust.

From Drift to Discipline: Operating Model for Regaining Enterprise Cloud Control

Aggregated on: 2025-07-18 12:29:22

Today’s biggest enterprise bets — AI, global scale, real-time everything — don’t just run on cloud infrastructure. They depend on it. But most enterprise infrastructure still operates in a state of reactive chaos. Cloud sprawl. Shadow resources. Security risks hiding in plain sight. Infrastructure built on the best intentions… all held together by duct tape and drift.

The Hidden World of Exit Codes: Tiny Integers With Big Meanings

Aggregated on: 2025-07-18 12:14:22

It's not what you say, it's how you say it - Albert Mehrabian In the land of your favorite TTY, the output (stdout, stderr) of the commands themselves are often not looked at, specifically within scripts that are meant to run in those terminals.

Implementing Event-Driven Systems With AWS Lambda and DynamoDB Streams

Aggregated on: 2025-07-18 11:14:22

As cloud-native architectures become the norm, developers are increasingly turning to event-driven design for building scalable and loosely coupled applications. One powerful pattern in this space leverages AWS Lambda in combination with DynamoDB Streams. This setup enables real-time, serverless responses to data changes—without polling or manual infrastructure management. This article explains how to implement an event-driven system using DynamoDB Streams and AWS Lambda. A step-by-step implementation example using LocalStack is also included to demonstrate how the architecture can be simulated locally for development and testing purposes.

Terraform vs Pulumi vs SST: A Tradeoffs Analysis

Aggregated on: 2025-07-17 20:14:22

Defining a deployment strategy is a key concern for any new software project. While Infrastructure as Code (IaC) has become the industry standard for provisioning and managing cloud infrastructure, choosing the best-fitting one among several viable options can be difficult. In this article, I look at three popular tools for writing infrastructure code and which one I would recommend based on the circumstances of the project. First though, let's start with some basics.

How Hackers Exploit Spring Core Vulnerability in 2025: Proactive Measures to Detect Emerging Cyber Threats

Aggregated on: 2025-07-17 19:14:22

API management has emerged as a critical and strategic factor in staying ahead of the market leaders. However, digital transformation has significant disadvantages, such as opening the door to hackers. Hackers have been quick to take advantage of a serious flaw in Spring Core, commonly known as SpringShell or Spring4Shell among security experts. The cybercriminal sends a specially created query to the Spring Core framework's web application server.

The Twelve-Factor Agents: Building Production-Ready LLM Applications

Aggregated on: 2025-07-17 18:14:22

After exploring and publishing articles around observability tools and architectural patterns related to AI Agents, I came across an interesting talk by Dex Horthy on YouTube and the Twelve-Factor Agent. This article delves into the concept of the Twelve-Factor Agent, an architectural pattern designed to create robust, scalable, and maintainable applications, particularly in the context of modern cloud environments. We will explore the core principles of this approach and how they contribute to building applications that are well-suited for deployment and operation in dynamic and distributed systems. The rise of large language models (LLMs) has created unprecedented opportunities for building intelligent applications, but it has also introduced new challenges for software engineering. The Twelve-Factor Agent methodology represents a set of principles for building LLM-powered software that's reliable enough to put in the hands of production customers, drawing inspiration from the original Twelve-Factor App methodology by Heroku.

The Underrated Hero of UI Testing: Why Screenshot Testing Matters

Aggregated on: 2025-07-17 17:14:22

As an Android engineer with years of experience, including six dedicated to screenshot testing, I’ve seen firsthand how this often-overlooked testing strategy can save teams from major headaches. While unit and integration tests dominate conversations about code quality, screenshot testing quietly stands out as a game-changer – especially for apps with complex design systems, multiple localizations, and countless UI states. Despite its niche popularity, screenshot testing is one of the most efficient ways to catch visual regressions early. In this article, I'll explore why every Android project should integrate screenshot testing into its CI/CD pipeline and why Paparazzi currently stands out as the most effective tool.

Best Practices for Syncing Hive Data to Apache Doris : From Scenario Matching to Performance Tuning

Aggregated on: 2025-07-17 16:29:22

In the realm of big data, Hive has long been a cornerstone for massive data warehousing and offline processing, while Apache Doris shines in real-time analytics and ad-hoc query scenarios with its robust OLAP capabilities. When enterprises aim to combine Hive’s storage prowess with Doris’s analytical agility, the challenge lies in efficiently and reliably syncing data between these two systems. This article provides a comprehensive guide to Hive-to-Doris data synchronization, covering use cases, technical solutions, model design, and performance optimization.

Migrating Traditional Workloads From Classic Compute to Serverless Compute on Databricks

Aggregated on: 2025-07-17 15:14:22

This article walks us through the process of how to migrate traditional workloads using Classic Compute to Serverless Compute for efficient cluster management, cost effectiveness, better scalability and optimized performance. Overview As data engineering evolves, so do the infrastructure needs of enterprise workloads. With growing demands for agility, scalability, and cost-efficiency, Databricks Serverless Compute provides a compelling alternative to classic clusters. In this article, we explore a practical roadmap to migrate your pipelines and analytics workloads from classic compute (manual clusters or job clusters) to Databricks Serverless Compute, with specific attention to data security, scheduling, costs, and operational resilience.

Rapid AWS Prototyping With LocalStack: A Developer’s Guide to Building AWS PoCs Locally

Aggregated on: 2025-07-17 14:14:22

Proof of Concepts (PoCs) play a critical role in modern software development. They allow engineers and architects to validate technical assumptions, test integrations, and explore new ideas quickly and with minimal investment. When working with Amazon Web Services (AWS), however, even simple experimentation often requires deploying cloud infrastructure. This can be time-consuming, costly, and constrained by organizational permissions. Enter LocalStack — a fully functional AWS cloud emulator that enables developers to simulate AWS services entirely on their local machines. By replicating AWS APIs and service behavior, LocalStack empowers teams to build and iterate faster without depending on live cloud environments.

11 Best Practices for Developing Secure Web Applications

Aggregated on: 2025-07-17 13:14:22

Applications related to the web enable business, e-commerce, and user interactions to be the backbones of the e-world of a more and more digital world. In this growth, there is one thing that has gone up, and that is web application security. Insecure web applications can lead to severe consequences such as data breaches and ransomware attacks, resulting in significant financial losses, legal liabilities, and reputational damage. Given the growing sophistication of cyber threats, it's crucial for both developers and business stakeholders to prioritize security from day one. This blog outlines 11 essential best practices for web application development to help you build robust, resilient, and attack-resistant systems.

AI-Powered Security for the Modern Software Supply Chain: Reinforcing Software Integrity in an Era of Autonomous Code and Expanding Risk

Aggregated on: 2025-07-17 12:59:22

Editor's Note: The following is an article written for and published in DZone's 2025 Trend Report, Software Supply Chain Security: Enhancing Trust and Resilience Across the Software Development Lifecycle. In today's software landscape, the supply chain has grown from a controlled pipeline to a vast, interconnected ecosystem. Modern development relies heavily on third-party dependencies, open-source components, distributed CI/CD pipelines, and ephemeral cloud-native environments. While this fosters rapid innovation, it also amplifies risk exposure. High-profile breaches like SolarWinds and Log4Shell revealed how a single weak link can cascade across thousands of organizations.