Author: Arie

The world of AI, especially with Large Language Models (LLMs) and Generative AI, is changing the game. It’s like we’ve unlocked a superpower for creating content, automating tasks, and solving tricky problems. But, as with any new superpower, there are new ways things can go wrong. Open Worldwide Application Security Project (OWASP) experts have put

If you’ve ever been nervous about deploying code on a Friday, trust me — you’re not alone. A few years ago, I was leading a team at a major e-commerce company, wrangling a monolithic beast that could break in a hundred creative ways. The idea of microservices was everywhere, but nobody really tells you about

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

Recently, I explored how the Model Context Protocol (MCP) is gaining traction in the Java ecosystem, with frameworks like Spring AI, Quarkus, and LangChain4j starting to adopt it for integrating language models via standardized interfaces. It was also time to start experimenting with writing an MCP Server myself (well maybe not the first time). Certainly,

CRITICAL_PROCESS_DIED is a notorious Windows error that triggers the dreaded Blue Screen of Death (BSOD), often leaving users frustrated and unsure of how to proceed. This error typically indicates that a critical system process has unexpectedly terminated, causing Windows to halt to prevent further damage. Encountering this error can disrupt your workflow and raise concerns

Software projects can have disastrous breaches resulting from security flaws that expose private information and compromise user confidence. Preventive security measures become critical as applications get more sophisticated. One of the best ways to find and reduce possible hazards before they turn into exploitable weaknesses is threat modeling. Structured approaches such as STRIDE and DREAD

Abstract: Healthcare systems around the world are at a critical juncture, navigating the pressures of digital transformation, rising cybersecurity threats, and fragmented data landscapes. While the volume of healthcare data grows exponentially, the capacity to manage it securely and effectively across stakeholders remains limited. Blockchain, a decentralized ledger technology known for transparency and immutability, is

Large language models are fast-developing and transforming the way we use technology. The rise of generative AI tools like ChatGPT and Gemini in 2022 has led to common business exploration and employee adoption, frequently including unapproved use of tools such as ChatGPT, Gemini, and multiple third-party add-ons. Beyond its origins, artificial intelligence has expanded to

Are we getting too aggressive with speed and efficiency in automation, losing the battle to security? If security isn’t prioritized, automation can accelerate risks as quickly as it accelerates processes, leading to severe consequences. A study conducted on the IBM Security X-Force Threat Intelligence Index 2024 reveals that, among the overall cyberattacks, 71% are attributed

As the degree of account takeovers and unauthorized access attempts continues to be more and more sophisticated, the time to notify users about security-critical situations has become a vital issue. The moment when a system becomes aware of irregular behavior — such as a log from a new device or suspicious activity — it is