20+ min ago (310+ words) If you're an engineer, you've likely been there: you receive an email from the VPE. "Our cloud burn rate is up 15% this quarter. Find the leak." Suddenly, you're spending a week digging through Cost Explorer when you should be shipping features. This reactive loop is a system failure. The cost of an S3 bucket or an undersized Redis cluster isn't hidden; it's just hidden from the people making the deployment choices (the developers). The Solution: Move Cost Awareness to the Merge Request. Step 1: The Cost Budget Function Most companies already use Infrastructure-as-Code (IaC) like Terraform or Pulumi. This is our lever. Before deploying, IaC generates a plan detailing what will be provisioned. The trick is to connect that plan to a cost estimator. Tools like Infracost or Terragrunt hooks can parse the plan output and give you a dollar estimate for…...

21+ min ago (356+ words) Most of us learn JavaScript objects like this: It looks simple. A key, a value. Done. But what if I told you that every property in an object has hidden settings? What if you wanted to create a property that cannot be deleted? Or a property that is invisible to loops? Or a value that is read-only, like Math.PI? Welcome to the world of Property Flags and Descriptors. This is how you take off the training wheels and gain full control over your objects. Imagine a file on your computer. It has content, but it also has attributes: Read-only, Hidden, or System file. JavaScript object properties work the same way. Besides the value, every property has three special "flags" (attributes) that are usually set to true by default: See? When you create an object normally, JavaScript is nice and…...

23+ min ago (803+ words) I understand why some of you might have reservations about DEI. It's partly due to the disruptive actions of some radical minorities. The recent move to abolish DEI in the U.S. is fresh in memory, and there may be engineers who inwardly applauded this decision. In fact, some tech companies have removed mentions of DEI from their websites. From the standpoint of a Knowledge Architect, I must say that DEI is actually crucial for engineers. This is not about accepting the radical actions of a minority. It's a more fundamental and forward-thinking issue. It helps protect you and is especially pertinent, if not essential, for those in roles like engineering managers or staff engineers who have a broader organizational perspective. We live in a VUCA world, and our standard of living and literacy have increased. To navigate this challenging era, the…...

28+ min ago (1204+ words) [ ] " Daily Learning Update " Linux Fundamentals " Today I learned Linux fundamentals, and it was a super valuable experience for me as an AWS & DevOps Engineer. " I understood how Linux is the backbone of most cloud environments, servers, and container systems like Docker & Kubernetes. It provides a secure, stable, and highly customizable platform, making it essential for automation, troubleshooting, and cloud deployment. Learning Linux is definitely boosting my confidence in building efficient cloud and DevOps solutions. " If you found this helpful, share your thoughts, experiences, or tips in the comments " I'd love to learn from you too! " " History of Linux Linux was created in 1991 by Linus Torvalds as a free and open-source alternative to UNIX. The first Linux kernel was released publicly, allowing global developers to contribute and improve it. Today, Linux powers servers, supercomputers, Android devices, and modern cloud platforms like…...

37+ min ago (122+ words) I'm tired of seeing "Hello World" RAG tutorials that pipe every single user query directly to OpenAI's API. It's lazy architecture. If you are building an LLM feature for production, you quickly realize two things: Most developers try to solve this with simple key-value caching (searching for an exact string match). But users don't type the same thing twice. Here is how I implemented a production-grade Semantic Cache layer using Python, Redis (VSS), and Sentence Transformers. We aren't just matching strings; we are matching vectors. Don't use OpenAI for embeddings here. It adds network latency. Run a small model locally or in a sidecar container. all-MiniLM-L6-v2 is 80MB and runs on CPU in milliseconds....

40+ min ago (113+ words) Most DevOps tutorials begin with AWS, GCP, or Kubernetes. But here's my honest advice: Start with Killercoda's Ubuntu playground instead. I recently deployed my full DevOps portfolio website using nothing but this environment and Nginx " and it was one of the most valuable hands-on exercises I've done. When you deploy on Killercoda, you learn the fundamentals that cloud providers hide behind fancy panels: It's the closest experience to running a real Linux server " without paying for one. If you're a beginner DevOps engineer or trying to build confidence: Forget the cloud for a moment. Deploy something raw. Learn the ground truth. Your terminal will become your greatest teacher....

41+ min ago (613+ words) There's something I wish more employers understood " something I didn't fully have the words for until I lived through it myself: when a developer says the work requires a full-time position, they're not exaggerating. They're telling you what it actually takes to build the thing you're asking for. I learned that lesson from the inside, as the developer whose role didn't match the expectations placed on it. A while back, I joined a small Norwegian company as their only developer. They handled services related to cemeteries and memorials, and they had a system that had grown organically over the years. The database was" let's say "creatively structured," and every architectural decision seemed to lean in a different direction. I wanted to do good work, so I began the slow process of rebuilding, refactoring, and trying to bring some order to…...

42+ min ago (204+ words) Recentemente, desenvolvi um template reutiliz'vel para aplica'es AWS Lambda em Python, integrando infraestrutura como c'digo via Terraform e automa'o de CI/CD com GitHub Actions. Neste artigo, compartilho minha experi'ncia, decises de arquitetura e exemplos pr'ticos para quem deseja acelerar projetos serverless na AWS. A estrutura que utilizei foi a seguinte: Implementei um handler que detecta automaticamente o tipo de evento recebido (HTTP, EventBridge, SNS, S3) e responde de forma adequada. Veja um exemplo simplificado: Utilizei m'dulos oficiais da AWS para Lambda, API Gateway, EventBridge, SNS e S3. A configura'o de vari'veis permite habilitar ou desabilitar triggers conforme o ambiente. Exemplo de vari'veis para produ'o: A detec'o autom'tica de Lambda Layers foi feita via local no Terraform: Implementei pipelines para valida'o, lint, scan de segurana, deploy em staging e produ'o, al'm de automa'o de releases e rollback. O workflow principal para produ'o…...

49+ min ago (1228+ words) When people report bugs or performance problems, developers need more than logs and metrics; they need context. That's where debugging and session replay tools enter the picture. These platforms log users' interactions, console logs and network activity, giving teams a window into what really happened before the error occurred. Some popular tools like LogRocket, Sentry, Datadog and FullStory have already established themselves as essential in modern product teams. They give companies the ability to issue track, and this results in better user experiences and the alignment of engineering with design. But a new player in the space, Multiplayer, is betting on developer-first debugging and visibility, which is based around live collaboration, rich context and without any vendor lock-in. This article will compare Multiplayer to LogRocket, Sentry, Datadog, and FullStory, breaking down their main features into an easy-to-digest pros and cons…...

53+ min ago (808+ words) The conversation dominating the development world today is speed: how fast can AI write a function, how quickly can it spin up a service, how efficiently can it generate tests? But as Simon Leigh, Director of Pure Reputation, I believe this focus on velocity dangerously overlooks the true bottleneck to sustainable progress: trust. We are building a future where AI handles the vast majority of rote code generation. This is exhilarating, but it poses an existential question for the developer community: when the code is automated, what is the irreplaceable human function? My answer is simple: judgment, integrity, and the resulting reputation. The foundation of any successful digital system is confidence. A user needs to trust that the software will perform as intended, that their data is secure, and that the creators acted with ethical intent. In a hyper-digital, hyper-connected…...