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Let's shine a spotlight on the open-source ecosystem. What are the best OSS products launched this year from your perspective? Dropping here are some of my favorite, most inspiring product launches so far, in no particular order. 5 awesome open-source products launched on Product Hunt in 2026 OpenClaw Launched last February on Product Hunt, the AI that "actually does things" is the fastest ever growing project on GitHub with 300k+ stars and 70k+ forks. It created a new category, enabling 50+ related products like moltbook (acquired by Meta) and KiloClaw - both ranked #1 Product of the Day. Kilo Code First launched last year, the open-source agentic engineering platform (19k+ GitHub stars) launched a code reviewer and a new VS Code extension this year. Both ranked #1 Product of the Day and #1 Product of the Week. InsForge The backend platform launched 2.0, hit 10k GitHub stars, ranked #1 Product of the Day, #3 Product of the Week, and joined YC. The Product Hunt effect? Tailgrids The 3.0 release of this React UI library ranked #1 Product of the Day. Ghost The latest project by @haydenbleasel , maker of next-forge , Kibo UI , and Ultracite , just cracked Product Hunt again, ranked #1 Product of the Day. Wrapping up Over to you! What are the best open-source products launched on Product Hunt in 2026 from your perspective? More awesome dev-first product launches in this repository for inspiration. Launched 42+ dev-first products on Product Hunt. AMA. fmerian fmerian fmerian Follow Feb 23 '25 Launched 42+ dev-first products on Product Hunt. AMA. # discuss # startup # marketing 1 reaction Comments Add Comment 5 min read

Three weeks ago, one of the teams we work with had a checkout outage. The root cause a malformed...

Introduction People keep telling me TanStack Start is kind of a big deal, and I wanted to...

Sharing my personal fetch wrapper I use in all my projects. I also added some Axios features to reduce my dependencies and wrote a guide about it submitted by /u/patchimou [link] [留言]

Hello everyone, i'm in the process of implementing a Sellsy integration on my app which is, for those who don't know, a service to generate and send invoices, estimates etc ... They have an API that i'm using. Right now i'm using the API keys and account the commercial is using for generating its documents but i add "TEST" prefix to the clients i'm working on while developing so it doesnt collide with existing data. My question is more of an architectural implementation question: how would you guys approach not colliding with production data in dev and staging environments. For example: if i need to work on the API integration, to prevent generating and sending invoices or if i need to generate them but prevent colliding with production data. Should i create another Sellsy account ? DEV or STAGING prefixes ? Any ideas are welcomed PS: i already asked AI, looking for human answers only submitted by /u/armlesskid [link] [留言]

HashiCorp has released Terraform 1.15, introducing dynamic module sources, a formal deprecation mechanism for variables and outputs, a new inline type conversion function, type constraints for output blocks, and native Windows ARM64 support. The release addresses several long-standing requests from the Terraform community. By Matt Saunders

Rocicorp has released Zero 1.0, a stable version of its sync engine after two years of development. This update introduces a schema change hook for Supabase and includes bug fixes. Zero operates by pairing a client library with a read-only Postgres cache. Community feedback highlights positive developer experience but raises concerns about production readiness and existing limitations. By Daniel Curtis

This is a submission for the June Solstice Game Jam Solstice Cipher is a browser puzzle game where...

When I started building OpinioZone , my goal was simple: create a platform where users could compare products, read reviews, and make informed buying decisions. At first, it seemed like a straightforward web application. Store products, display specifications, and allow users to browse information. However, as the platform grew, I quickly discovered that building a review and comparison website involves many technical and architectural challenges. Choosing the Technology Stack I selected ASP.NET Core as the primary framework because of its performance, flexibility, and long-term support. For data storage, I chose SQL Server since it provides strong reliability and works well with complex relationships between products, categories, reviews, ratings, and specifications. This combination allowed me to build a scalable foundation while keeping development manageable. Designing the Database One of the biggest challenges was designing a database structure that could support multiple product categories. A smartphone and a car have very different specifications, but the platform needed to handle both efficiently. Instead of creating completely separate systems, I designed a flexible structure that could store category-specific attributes while maintaining a consistent user experience. This decision made it easier to add new product categories without major database changes. Building Product Comparisons The comparison feature became one of the most important parts of the platform. Users expect side-by-side comparisons to load quickly and display meaningful differences between products. To achieve this, I had to optimize queries and carefully structure specification data. Performance became increasingly important as the number of products grew. SEO Challenges For a content-driven website, SEO is critical. Every product page requires: Unique titles Descriptions Structured content Internal linking Fast page loading One lesson I learned early was that technical SEO and content q

CSV files are one of the most common formats for storing and exchanging data. Whether you’re working with logs, analytics data, application exports, or reports, there will likely come a time when you need to load CSV data into ClickHouse®. The good news is that ClickHouse® makes CSV ingestion straightforward and efficient. In this guide, you’ll learn how to create a table, prepare a CSV file, load CSV data into ClickHouse®, and verify that the data has been imported successfully. Why Use CSV Files with ClickHouse®? CSV (Comma-Separated Values) files are simple, portable, and supported by virtually every data platform. Common use cases include: Importing exported application data Loading historical datasets Migrating data from other databases Testing analytics workloads Sharing data between systems Because ClickHouse® is designed for high-performance analytics, it can efficiently process and query large CSV datasets once they are loaded into a table. Sample CSV File Let’s assume we have a file named employees.csv with the following contents: id,name,department,salary 1,Alice,Engineering,75000 2,Bob,Marketing,60000 3,Charlie,Finance,70000 This simple dataset will help demonstrate how to load CSV data into ClickHouse®. Step 1: Create a Table in ClickHouse® Before importing data, create a table that matches the structure of the CSV file. CREATE TABLE employees ( id UInt32, name String, department String, salary UInt32 ) ENGINE = MergeTree() ORDER BY id; This table contains four columns that correspond directly to the columns in our CSV file. Step 2: Load CSV Data into ClickHouse® There are several ways to import CSV data, but one of the most common methods is using the ClickHouse® client. Run the following command: clickhouse-client --query=" INSERT INTO employees FORMAT CSVWithNames" < employees.csv The CSVWithNames format tells ClickHouse® that the first row contains column headers. After executing the command, ClickHouse® will read the CSV file and insert the records

I built ResizeKB — a free image and PDF resizer built specifically for Indian users. 25+ tools. Zero server uploads. Pure HTML, CSS, JavaScript. Here's how and why. The Problem Every Indian applying for government jobs, exams, or bank accounts hits the same wall — portals with strict KB limits rejecting documents. UPSC wants photo under 300KB. SSC wants under 50KB. Banks need Aadhaar PDF under 500KB. Every portal is different. Every rejection wastes someone's time and opportunity. Most people have no idea how to resize to an exact KB. They either give up or use random tools that upload their Aadhaar and PAN card to unknown servers. I built a tool that solves this in one click — with zero server upload. The Tech Stack No framework. No backend. No database. Canvas API for image processing pdf-lib for PDF compression Vanilla JavaScript only Cloudflare Pages for hosting — free, global CDN, auto deploys from GitHub Total infrastructure cost: ₹1,162 per year for the domain. Everything else free. Image Compression — The Binary Search Algorithm The core challenge is compressing to an exact KB target without over-compressing. Most tools use a fixed quality setting like 60% which destroys image quality. The right approach is binary search on JPEG quality: javascriptasync function compressToTargetSize(file, targetKB) { const targetBytes = targetKB * 1024; let low = 0.1; let high = 1.0; let result = null; const img = await loadImage(file); const canvas = document.createElement('canvas'); canvas.width = img.width; canvas.height = img.height; const ctx = canvas.getContext('2d'); ctx.drawImage(img, 0, 0); while (high - low > 0.01) { const mid = (low + high) / 2; const blob = await canvasToBlob(canvas, 'image/jpeg', mid); if (blob.size <= targetBytes) { result = blob; low = mid; } else { high = mid; } } return result; } This finds the highest quality setting that still hits your target KB. Result is the sharpest possible image at that file size — never over-compressed. PDF Compress

The main difference between a developer and an engineer is not just the code they write. It's how they think about building a system. How they optimize. How they use resources. I learned this from a real project. I had to read 10,000 JSON requests and write them into a file. Simple enough. I wrote the program the way I always did the developer way. Read all 10,000 requests, store everything in memory, then write to the file. Done. When I tested it, my memory usage was much higher than normal. Way higher than it should have been. The developer in me would have just moved on. It works, right? But something made me stop and ask why is this consuming so much memory? I dug into it. And I found the problem. What I was doing was basically doubling my memory usage without realizing it. First, I was loading all 10,000 records into memory to store the data. Then, I was holding all of it again in memory while writing to the file. Two copies of the same data sitting in memory at the same time. That's the thing about this approach it's not reliable when you're dealing with a large number of requests. It doesn't scale. It just quietly eats your resources. That's when I found streams. The idea behind streaming is simple but powerful. Instead of loading everything at once, you break the data into small chunks. At any given moment, only one chunk lives in memory. You read it, transform it, write it and move on to the next one. The transform step is the interesting part. It's not just about moving data from one place to another. Transform lets you validate each chunk, check if the structure is correct, clean it if needed before it ever reaches the file. So you're not just being efficient with memory, you're also processing your data with more control. And because you're always working on one small piece at a time, the memory usage stays low and consistent no matter if you're processing 100 requests or 100,000. That one question am I using my resources in a reliable way? is what pushe

Two weeks ago I shared a collection of 6 financial calculators. The response was incredible, so I kept building. Today, fi-calc.com has 25 completely free calculators covering every major personal finance need: 🏠 Housing • Mortgage Calculator (full PITI + amortization schedule + pie chart) • Rent vs Buy Calculator • House Affordability Calculator • Refinance Calculator 💰 Investing & Retirement • Compound Interest Calculator • Investment Return Calculator • Future Value & Present Value Calculators • ROI Calculator • Retirement Savings Calculator • 401(k) Calculator • FIRE Calculator (Financial Independence) 💳 Debt & Loans • Loan Comparison Calculator • Auto Loan Calculator • Student Loan Calculator • Credit Card Payoff Calculator • Debt Payoff Calculator (Avalanche method) 📊 Everyday Finance • Budget Planner (50/30/20 rule) • Savings Goal Calculator • Inflation Calculator • Salary & Take-Home Pay Calculator • Net Worth Calculator • Currency Converter (15+ currencies) • CD Calculator • Sales Tax Calculator ✨ Tech Stack • Pure vanilla HTML/CSS/JS — no frameworks • Chart.js for animated interactive charts • Responsive design (mobile-friendly) • All calculations run client-side in your browser • No data collection, no accounts, no cookies 🔗 Give it a try: fi-calc.com The entire site is free and open. I built it because I was tired of calculator sites with paywalls, signup walls, and bloated ad experiences. Would love feedback from the community! What other calculators should I build next?

The way developers write software has genuinely changed. Not incrementally — fundamentally. A year...

The Problem Wasn't Writing It was starting. Sometimes I wanted: A social media caption A motivational quote A writing prompt A meaningful message But my mind would go completely blank. Not because I had nothing to say. Because: Coming up with the right words at the right moment is surprisingly difficult. We've All Done This Open a new tab. Search: "Motivational quotes" "Success quotes" "Life quotes" "Funny quotes" Scroll for 10 minutes. Copy one. Close the tab. Why I Built This Tool So I built something simple: 👉 https://allinonetools.net/quote-generator-tool/ A tool that instantly generates quotes across different categories. Whether you need: Motivation Success Life Leadership Creativity Social media inspiration You can generate quotes in seconds. No signup. No setup. Just: Click → Generate → Use What I Realized People don't always look for quotes because they need content. Often they're looking for: A different perspective. A good quote can do something interesting. It can say in one sentence what takes us paragraphs to explain. The Surprising Part The most popular quotes are rarely complicated. They're simple. Short. Easy to remember. Yet somehow they stick with us for years. Why Quotes Still Matter In a world full of endless content: Attention is limited Time is limited Patience is limited A strong quote delivers an idea instantly. That's powerful. The Problem With Searching Manually Most quote websites feel: Cluttered Slow Full of ads Hard to browse And sometimes you spend more time searching than actually reading. What I Focused On I wanted the experience to feel: Fast Clean Inspiring Fun to explore Because finding inspiration shouldn't require effort. What Surprised Me After building it: Some people used it for: Social posts Presentations Daily motivation Writing inspiration But one thing surprised me most. People kept generating quote after quote. Not because they needed one. Because they enjoyed discovering them. The Real Insight Sometimes tools aren't abo

In Modern Time applications are no longer simple monolithic systems. Today organizations run: Microservices Kubernetes Containers Serverless Functions Multi-Cloud Platforms Distributed Systems As infrastructure becomes more distributed, troubleshooting becomes significantly harder. A single user request may travel through: Frontend ↓ API Gateway ↓ Microservice A ↓ Microservice B ↓ Database When something breaks, the biggest challenge becomes: "What exactly happened?" This is where Observability becomes critical. 🔗 Resources ** Support the Journey on GitHub: If you're following along, consider starring and forking the repo:** https://github.com/17J/30-Days-Cloud-DevSecOps-Journey What is Observability? Observability is the ability to understand the internal state of a system by analyzing the data it produces. In simple words: Can we understand what is happening inside our systems? Observability helps engineers answer: Why is the application slow? Which service is failing? Which request caused the issue? What changed recently? Where is latency occurring? Without observability: Problem Exists ↓ Guessing Begins With observability: Problem Exists ↓ Evidence Available ↓ Faster Resolution Why Observability Matters Modern cloud-native systems generate enormous amounts of data. Example: 100 Microservices ↓ Millions of Requests ↓ Thousands of Containers Traditional monitoring alone is no longer sufficient. Organizations need: Visibility Insights Correlation Root Cause Analysis Observability provides all of them. Monitoring vs Observability Many people confuse monitoring and observability. Monitoring asks: What is wrong? Observability asks: Why is it wrong? Example: Monitoring: CPU Usage = 95% Observability: Which service? Which request? Which dependency? Which deployment caused it? Observability provides context. The Three Pillars of Observability Modern observability is built on three primary pillars. Metrics Logs Traces Or: Monitoring Logging Tracing Together they provide a

Intro AI Avatar is a completely free app that lets your VRoid (VRM) 3D avatar animate in...

Last week I did something dumb: I sat down and wrote 50 Claude Code prompts in one sitting. Halfway through I was sure most of them would never get used. But I finished, pushed them to GitHub, and made myself use them for an entire week -- no ad-hoc prompting allowed. The result surprised me. Some skills were life-changing. Others were useless. Here is the honest breakdown. The Methodology I categorized the 50 skills into 5 types: Analysis (12), Generation (14), Debugging (8), Planning (10), Maintenance (6). Rule: every time I hit a task, I must use a skill file or admit I did not have one. The 7 That Actually Saved Me Hours 1. Code Review Assistant (saved ~3h) This was the biggest surprise. I usually review PRs by gut feel -- scan the diff, look for obvious bugs, approve. The Code Review skill forced me to be systematic: On a 400-line PR it caught 2 security issues I would have missed. That alone justified the experiment. 2. Bug Investigator (saved ~2h) Instead of pasting errors and asking "why?", this skill forces you to provide: error message, file context, hypothesis. 3. Dependency Audit (saved ~1h) Scanned a 3-year old Node project. Found 2 CVEs, 8 unused devDependencies (21 MB). 4. Auto Commit Messages (saved ~30m) Saves 2 minutes per commit. Over 15 commits in a week that is 30 minutes. 5. Test Generator (saved ~2h) Generates 5-8 test cases per function in seconds. 6. Refactoring Planner (saved ~1h) Reads the function, identifies extraction candidates, outputs a dependency-ordered plan. 7. Performance Audit (saved ~30m) Found an unoptimized 3 MB hero image and a render-blocking script. The Ones I Never Touched About 8 out of 50 were "not this week" -- Database Migrations, API Documentation, CI/CD Pipeline. What I Learned The ROI is in the analysis skills. Code review, bug investigation, dependency audit -- these are high-judgment tasks where Claude thoroughness beats speed. Skills are habit, not technology. The hardest part was not writing the prompts -- it w

submitted by /u/lune-soft [link] [留言]

Hey DEV community! 👋 I just completely rebuilt and launched Mailfo v2.0 , an privacy-focused temporary disposable email app for Android[cite: 1, 2]. The first version got the job done, but it lacked the fluid user experience, offline reliability, and sleek UI that modern mobile apps need. I decided to tear it down and rewrite it from scratch using Jetpack Compose , Room DB , and modern Android architecture[cite: 1]. Here is a breakdown of what went into the rebuild, why privacy tools like this are essential, and what's new[cite: 1]. 🛡️ Why Use a Temporary Disposable Email? We’ve all been there: you want to download a single source-code snippet, test a new app, or sign up for a one-time service, but you don't want your primary inbox flooded with endless marketing spam[cite: 1]. A disposable email address acts as your personal buffer[cite: 1]. It protects your personal data, prevents tracker exposure, and keeps your real inbox clean[cite: 1]. ⚠️ Pro-tip: Mailfo is designed strictly for low-risk temporary email needs[cite: 1]. Do not use disposable email addresses for banking, legal accounts, or primary account recoveries[cite: 1]! 🛠️ The Tech Stack & Architecture Upgrades Moving from version 1.0 to 2.0 meant migrating away from legacy views to a fully declarative UI workflow[cite: 1, 2]. UI/UX Architecture: Built entirely with Jetpack Compose for smooth performance, a modern look, and native Light, Dark, and System theme switching[cite: 1]. Navigation: Implemented an intuitive bottom navigation system dividing the app into distinct Home, Inbox, and Profile tabs[cite: 1]. Caching & Offline Stability: Integrated a local Room SQLite database to cache inbox summaries and message data[cite: 1]. This guarantees instantaneous screen transitions without annoying network loading spinners[cite: 1]. ✨ Key Features in Mailfo v2.0 Custom & Random Email Generator: Instantly spin up a completely randomized address or build a custom email username using multiple searchable domains[ci