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Senior Solution Architect Viktor Vedmich shares how engineering leaders can maximize application performance using Valkey. He discusses the open-source Redis fork's 100% API compatibility, explores advanced caching strategies like lazy loading, and explains how to implement powerful data structures for real-time analytics, rate limiting, and session stores to solve the thundering herd problem. By Viktor Vedmich

Earlier this year, the “Because I Got High” rapper went viral for winning a case against the cops. Now he’s crypto’s free-speech hero, even though he isn’t quite sure how the digital currency works.

Every time a course batch completes, you have a list of students who need certificates. The manual way: open Canva, duplicate the template, change the name, export, repeat — for every single student. If you have 10 students, that's annoying. If you have 200, that's a full afternoon. The better way A single n8n workflow that: Reads student names from Google Sheets Calls the RenderPix batch API Gets back 200 certificate images Emails each student their certificate Total time: ~2.5 minutes. Total manual work: zero. What you'll need A RenderPix account (free tier works for testing, Starter plan for production) n8n (self-hosted or cloud) n8n-nodes-renderpix community node A Google Sheet with student data Install the n8n node: npm install n8n-nodes-renderpix Or search "RenderPix" in n8n's community node panel. Step 1 — Design your certificate template Write your certificate in plain HTML. Here's a clean starting point: <div style= "width:1200px;height:850px;background:white; display:flex;flex-direction:column;align-items:center; justify-content:center;border:20px solid #0f172a; font-family:Georgia,serif;padding:60px;box-sizing:border-box" > <div style= "font-size:16px;letter-spacing:5px;color:#64748b; text-transform:uppercase;margin-bottom:24px" > Certificate of Completion </div> <div style= "width:80px;height:2px;background:#22d3ee;margin-bottom:32px" ></div> <div style= "font-size:52px;font-weight:700;color:#0f172a;margin-bottom:16px" > {{name}} </div> <div style= "font-size:18px;color:#475569;text-align:center;max-width:600px" > has successfully completed </div> <div style= "font-size:28px;font-weight:600;color:#1e293b;margin:16px 0 40px" > {{course}} </div> <div style= "font-size:14px;color:#94a3b8" > {{date}} </div> </div> Notice the {{name}} , {{course}} , {{date}} placeholders — RenderPix replaces these at render time. Step 2 — Set up Google Sheets Create a sheet with these columns: name course date Jane Smith Advanced n8n Automation June 2026 John Doe Advanced n8n

Everyone's writing specs for AI now. We hand the model a markdown file, tell it what we want, and hope it builds the right thing. It mostly works — until it doesn't. Markdown has quietly become the spec language. People reach for it as the DSL for their AI-driven workflows — headings, bullet lists, the odd table — and treat that loose structure as if it were a contract. The thing is, it isn't a DSL. It's markdown. It's prose formatting with no grammar to enforce, no structure you can execute, no shared vocabulary, and no way to tell whether the spec and the code still agree. You're leaning on a document format to do a job it was never built for, and you hit the limit the moment you want the spec to actually mean something a machine can check. Before you go down that road, I want to make a small, slightly absurd suggestion. Eat a cucumber. What I actually mean Gherkin is the plain-text language behind Cucumber , a tool that's been around for years in the behavior-driven development (BDD) world. It looks like this: Feature : User login Scenario : Successful login with valid credentials Given a registered user "ada@example.com" When she logs in with the correct password Then she should land on her dashboard And she should see a welcome message Scenario : Rejected login with wrong password Given a registered user "ada@example.com" When she logs in with an incorrect password Then she should see an "invalid credentials" error And she should remain on the login page That's it. Feature , Scenario , Given / When / Then . Structured enough that a machine can parse it, loose enough that a product manager can write it. The gap it bridges Most specs live at one of two extremes. On one end you have written specs : docs, tickets, markdown files. Readable by anyone, but inert. Nothing checks whether they're still true. They rot the moment the code moves on. On the other end you have tests : precise, executable, always honest — but written in code, illegible to half the people who a

The Anti-Bot Detection Checklist I Use Before Every Scraping Project Every scraping project I take on starts with this checklist. Not because I'm paranoid — but because I've learned the hard way that production scrapers fail silently. They return 200 OK with garbage data, or they get rate-limited so gradually you don't notice for days. This is the systematic approach I've refined over 50+ scraping projects. Pre-Scraping: Know Your Target 1. Identify the CDN and Protection Stack Before writing a single line of code, check what you're up against: # Check CDN and headers curl -I https://target-site.com # Look for these common protection headers: # X-Engine: akamai-html-protection # X-Served-By: DataDome # cf-ray: Cloudflare # X-Bot-Status: blocked Common protection platforms: Cloudflare → Look for cf-ray and __cfduid cookies DataDome → Look for datadome in headers or scripts PerimeterX → Look for _pxff cookies Akamai → Look for akamai-html-protection headers 2. Check Robots.txt Respectfully curl https://target-site.com/robots.txt | grep -v "^#" Don't take this as gospel — but it's a good signal. If they explicitly disallow your use case, that's a flag. 3. Map the Site's JavaScript Rendering Some sites are fully static (fast, easy). Others render everything with JavaScript (need Playwright/Puppeteer). Check: // Quick check - fetch raw HTML vs rendered content // If they differ significantly, you need JS rendering const https = require ( ' https ' ); const html = await fetch ( ' https://target.com ' ). then ( r => r . text ()); const hasAngularVueReact = /ng-app|vue|react|__NEXT_DATA__/i . test ( html ); console . log ( ' Needs JS rendering: ' , hasAngularVueReact ); Code-Time: Defensive Patterns 4. Rotate User Agents const USER_AGENTS = [ ' Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 Chrome/120 Safari ' , ' Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 Chrome/120 Edge/120 ' , ' Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 Chro

If you’ve ever spent hours debugging slow EC2 workloads or getting sticker shock from unexpected EBS IOPS charges, you’ve probably wondered if there’s a better storage option for temporary, high-performance data. AWS EC2 Instance Storage (also called Instance Store) is one of the most underutilized but powerful tools in the EC2 ecosystem—if you know how to use it correctly. This guide breaks down everything you need to know: core concepts, performance optimizations, use cases, limitations, and how it stacks up against EBS. By the end, you’ll be able to cut storage costs, boost workload performance, and avoid costly data loss mistakes. Table of Contents What Exactly Is AWS EC2 Instance Storage? Core Concepts of EC2 Instance Store Key Features That Make Instance Store Stand Out Which EC2 Instance Types Support Instance Store? Deep Dive: NVMe SSD Instance Store Volumes SSD Instance Store Performance Best Practices EC2 Instance Store vs EBS: Head-to-Head Comparison Top Real-World Use Cases for EC2 Instance Store Critical Limitations to Avoid Costly Mistakes Production-Grade Best Practices for Instance Store Root Volume Options: EBS-Backed vs Instance Store-Backed Instances EC2 Instance Store Pricing: No Hidden Costs Conclusion References What Exactly Is AWS EC2 Instance Storage? EC2 Instance Store is temporary block-level storage that is physically attached to the host server running your EC2 instance. Unlike standalone storage services like EBS, EFS, or S3, it is part of the EC2 service itself, with no network overhead between your instance and the storage disks. Its defining trait is its ephemeral nature: data stored on Instance Store only persists for the lifetime of the associated instance. If you stop, hibernate, or terminate your instance, all data on Instance Store volumes is permanently deleted. Core Concepts of EC2 Instance Store Before you start using Instance Store, make sure you understand these foundational rules: Device naming : Instance Store volumes are

In Part 1 we installed Presidio and ran a basic detection on clean sample text. Real data is messier. Emails have signatures with phone numbers buried in HTML. Support tickets mix PII with technical jargon. Chat logs have informal name references that NER models struggle with. And sometimes the PII isn't in text at all. It's in screenshots and scanned documents. This part covers how Presidio's detection engine actually works under the hood, how to process different text types you'll encounter in production, and how to handle structured data and images. How the Analyzer Engine Works Presidio doesn't rely on a single detection method. It layers three approaches and combines their results. Named Entity Recognition (NER) The NER model (spaCy by default) processes the text and identifies entities based on the language model's training. It's good at catching names, locations, and organizations even when they don't follow a fixed pattern. "John Smith" is easy. "Dr. J. Martinez-Garcia" is harder but the NER model handles it because it understands context and word patterns. The tradeoff is that NER is probabilistic. It can miss unusual names or flag common words as entities. That's why Presidio doesn't stop here. Pattern Matching (Regex) For entities with predictable formats, Presidio uses regex recognizers. Credit card numbers, SSNs, email addresses, IP addresses, phone numbers all have known patterns. A Luhn-validated 16-digit number is almost certainly a credit card. A string matching \d{3}-\d{2}-\d{4} in the right context is probably an SSN. Pattern-based detections typically get higher confidence scores than NER detections because the pattern itself is strong evidence. Context Scoring Here's where it gets interesting. Presidio looks at the words surrounding a potential match to boost or lower confidence. If the text says "my SSN is 123-45-6789," the phrase "my SSN is" provides strong context that the number is actually a social security number and not some random ID. Th

Have you ever wondered what the most indispensable app is for your favorite musician or how the world’s tech CEOs stay focused? Well, that’s the sort of thing we aim to uncover in our Verge Weekend Questionnaire. Think of it as a spiritual successor to Five Minutes on the Verge. Every Saturday, a different guest […]

Constantly being plugged into the news grind is mentally exhausting. Sometimes we just need to take a break, unwind, and do something fun. That’s why we’ve built up a collection of distracting time-wasters for when we need a break from being obsessively online. We figured you might enjoy these harmless rabbit holes, mildly addictive browser […]

Multi-Model AI API Routing: Cut Costs Without Sacrificing Quality Problem: You're building an AI-powered app, but relying on a single model (like GPT-4) for every request is burning through your budget. Simple tasks like summarization or classification don't need a heavyweight model, yet you're paying premium prices for them. Solution: Route requests intelligently to the cheapest model that can handle each task. This is multi-model AI API routing, and it can cut your costs by 60-80% while maintaining output quality. Prerequisites Python 3.8+ API keys for at least 2 AI providers (e.g., OpenAI, Anthropic, or NovaAPI) Basic understanding of async/await in Python Step 1: Define Your Routing Strategy First, create a routing configuration that maps task complexity to model tiers: # router_config.py ROUTING_CONFIG = { " simple " : { " models " : [ " nova-1-fast " , " gpt-3.5-turbo " ], " cost_per_token " : 0.0001 , " max_tokens " : 500 , " tasks " : [ " summarization " , " classification " , " entity_extraction " ] }, " medium " : { " models " : [ " nova-1-medium " , " gpt-4-mini " ], " cost_per_token " : 0.0005 , " max_tokens " : 2000 , " tasks " : [ " code_generation " , " translation " , " sentiment_analysis " ] }, " complex " : { " models " : [ " nova-1-pro " , " gpt-4 " ], " cost_per_token " : 0.002 , " max_tokens " : 4000 , " tasks " : [ " reasoning " , " creative_writing " , " complex_qa " ] } } Step 2: Build the Router Now implement the core routing logic with fallback capabilities: # ai_router.py import asyncio from typing import Dict , List , Optional import time class AIRouter : def __init__ ( self , config : Dict , api_keys : Dict [ str , str ]): self . config = config self . api_keys = api_keys self . metrics = { " cost " : 0 , " requests " : 0 , " failures " : 0 } async def route_request ( self , task : str , prompt : str ) -> str : """ Route request to appropriate model based on task complexity. """ tier = self . _classify_task ( task ) models = self . confi

How to Auto-Sync Your Hashnode Blog to Dev.to Using GitHub Actions (2026 Guide) FOLASAYO SAMUEL OLAYEMI FOLASAYO SAMUEL OLAYEMI FOLASAYO SAMUEL OLAYEMI Follow Jun 7 How to Auto-Sync Your Hashnode Blog to Dev.to Using GitHub Actions (2026 Guide) # discuss # automation # tutorial # devops 5 reactions Comments Add Comment 5 min read

A real look at the platform everyone's calling "the writer's alternative to Medium" Let me be...

You write await a dozen times before lunch. Fetch a row, await it. Call a service, await that. It works, you move on, and you never have to think about what the word is doing. Then one day someone asks you to explain it. Maybe it's an interviewer."But what does await actually do?" And you open your mouth and what comes out is "it, uh, waits for the promise." Which is true, and also explains nothing. We can build async/awit mechanism from scratch using generators as a learning exercise. It requires a pause button wired to a small loop that waits on a promise and then presses play again. You already know one half of that machinery if you read the last post in this series . The other half is a trick generators have that we glossed over. Put the two together and you can build a working version of async/await yourself, by hand, and watch it behave exactly like the real thing. Let's do that. The shape of the problem Strip await down to what it has to accomplish and you get two requirements: First, a function has to be able to stop in the middle. Right at the await, freeze everything, the local variables, the spot in the loop, all of it, and hand control back to whoever called it. Normal functions can't do this. They run start to finish and that's the deal. Second, something on the outside has to wait for the promise to settle and then nudge the frozen function back to life, handing it the resolved value as if the await expression had simply evaluated to it. That's the whole job. A function that pauses, and a driver that resumes it when a promise is ready. Hold that picture, because the rest of this is just filling in those two pieces with things JavaScript already gives you. The half you've seen: pausing A generator function, the function* kind, can pause itself with yield and resume later from the exact same spot. We leaned on that hard in the CSV piece to pull rows through a pipeline one at a time. A line came in, got yielded, and the generator sat frozen until someone

Kubernetes networking is one of the most misunderstood parts of running containerized workloads. A pod can reach another pod by IP — but why does that stop working after a deployment? A service exists and resolves in DNS — but traffic isn't arriving at the application. An Ingress resource is configured — but requests return 502. These puzzles are common and they stem from the same root: Kubernetes networking has several distinct layers, each solving a different problem, and it's easy to conflate them. This article walks through how Kubernetes networking actually works at each layer — from pod networking to services to Ingress to network policy — so the next time something breaks, you have a mental model to reason from. The fundamental promise: flat pod networking Kubernetes makes one core promise about networking: every pod can communicate directly with every other pod in the cluster without NAT. Every pod gets a real IP address from the cluster's pod CIDR range, and those IPs are routable between pods regardless of which node they're running on. This is not something Kubernetes itself implements. It's a contract that every Kubernetes-conformant CNI (Container Network Interface) plugin must fulfill. When you install Calico, Cilium, Flannel, Weave, or any other CNI, you're installing the component that actually creates this flat network. The mechanism varies — Flannel uses VXLAN overlays, Calico can use BGP for direct routing, Cilium uses eBPF — but the result is the same: pod-to-pod communication without NAT. Here's what a pod's network namespace looks like: $ kubectl exec -it my-pod -- ip addr 1: lo: ... 3: eth0@if12: ... inet 10.244.1.15/24 brd 10.244.1.255 scope global eth0 $ kubectl exec -it my-pod -- ip route default via 10.244.1.1 dev eth0 10.244.0.0/16 via 10.244.1.1 dev eth0 The pod has an IP ( 10.244.1.15 ) on a /24 subnet. The node this pod runs on has an IP from the same range — or a different /24 within the same /16. Traffic from this pod to 10.244.2.8 (

Old School RuneScape has some of the most punishing—and rewarding—boss fights in any MMORPG. But unlike modern games that hand-hold you through a linear storyline, OSRS drops you into a massive open world with dozens of bosses and almost no guidance on which ones you should actually fight at your current level. If you've ever asked yourself: "I have 70 Attack—now what? Where do I even start with bossing?"—this guide is for you. The reality is that boss progression in OSRS isn't just about combat level. It's about unlocking content , learning mechanics , building gear on a budget , and scaling difficulty at the right pace . Rush into Vorkath at combat 90 with Tier 30 gear, and you'll bleed GP on deaths. Wait too long, and you'll miss out on millions of GP/hour that could have accelerated your account. This roadmap is designed to take you from your first boss kill to endgame PvM—with exact combat level ranges, gear checkpoints, EXP/hour benchmarks, and the reasoning behind every step. Table of Contents Why Boss Progression Matters The Three Pillars of Boss Readiness Phase 1: Pre-Boss Foundation (Combat 1–60) Phase 2: Your First Boss Kills (Combat 60–75) Phase 3: Mid-Game Bossing (Combat 75–90) Phase 4: Late Mid-Game Unlocks (Combat 90–105) Phase 5: Endgame PvM (Combat 105–126) Gear Progression Pathway Common Progression Mistakes (And How to Avoid Them) Conclusion: Your Bossing Journey Starts Now Why Boss Progression Matters Most OSRS players approach bossing backwards. They see a max-level player at Vorkath making 2M GP/hour, and they want that. So they grind combat to 80, buy some mid-tier gear, and head straight to Vorkath. Result? They die twice, spend 500K on gear repairs and supplies, and walk away thinking bossing isn't worth it. The problem isn't the boss. It's the progression . Bossing in OSRS is a skill, just like any other. Every boss teaches you a specific mechanic: prayer flicking, movement, eating under pressure, or managing multiple enemies. If you skip

Aerospace completely revolutionized my workflow after 15 years of using macOS the way Apple intended. I no longer hunt for apps and windows in Mission Control or drag them around spaces to organize. I can open as many windows as I need and have them all under my fingertips. And instead of swiping around to find one, I instantly teleport to where they are. This incredible software is technically aimed at advanced users. It’s installed from the command line and offers extensive configuration options. For basic use though, you don’t need to configure it at all, and if you have opened the Terminal application before and know what running a command means, you should be good to go. Rest assured, I will not show you how to configure Aerospace with Vim, or show you how to create an elaborate but useless dashboard! Just the essentials to get you started. How to set up Aerospace Aerospace is a menu bar application, but you can’t download it from an App Store or get it as a DMG file. You need a package manager. Go to the Homebrew website and follow the installation guide. Make sure to accurately follow the on-screen instructions. This may include any of the following: A prompt to enter your password. When you type passwords in Terminal, you will not see stars or anything. Just make sure you’re typing the correct one and hit Enter. A prompt to install XCode Command Line Tools . Somewhere around the end of the installation process, you may get a prompt to run some extra commands, which depend on your system. Make sure you run them as instructed. To test if you have correctly installed Homebrew, run which brew in Terminal. If you see a path printed out, like /opt/homebrew/bin/brew , you’re good to go. If not, something has gone wrong. Try searching for other, more focused guides on installing Homebrew. With Homebrew, you can install applications from the Terminal app using the brew command. For Aerospace, you would run the following command: brew install --cask nikitabobko/tap/ae

Benn Jordan may have initially gained notoriety for his music as Flashbulb and later, reviewing synths and effects pedals on YouTube under Benn and Gear. But about five years ago, Benn decided to take his YouTube channel in a different direction. He didn't stop covering music gear overnight, but as time progressed, his channel became […]

Quark’s Outlines: Python User-Defined Methods Overview, Historical Timeline, Problems & Solutions An Overview of Python User-Defined Methods What is a Python user-defined method? When you define a function inside a class, Python does not treat it as just a function. When you call it from an instance, Python changes it into a method. This method knows which object it was called from. It adds that object as the first argument when the function runs. A Python user-defined method joins a function, a class, and a class instance (or None ). It is created when you get a function from a class or an instance. Python binds the instance to the function and forms a method. Python lets you bind a class function to an instance as a method. class Box : def show ( self , word ): print ( " Box says: " , word ) x = Box () x . show ( " hi " ) # prints: # Box says: hi The method x.show is bound to the instance x . Python passes x as the first argument. What does "bound method" mean in Python? When a method is bound, it remembers the instance that called it. A bound method is created when you get a method from an object. It holds a reference to both the function and the instance. Python will pass the instance automatically when you call the method. If you get the same method from the class, Python gives you an unbound method. That means the function is not tied to any one object. Python uses bound methods to remember which object to call with. class Lamp : def turn_on ( self ): print ( " The lamp is now on. " ) l = Lamp () m = Lamp () a = l . turn_on b = m . turn_on a () b () # prints: # The lamp is now on. # The lamp is now on. Each bound method remembers which Lamp it came from. A Historical Timeline of Python User-Defined Methods Where do Python user-defined methods come from? Python user-defined methods grew from early ideas in object-oriented design. In many languages, methods are just functions that get special treatment when called from an object. Python made this clear by lettin

Getting started with the OSI Model Simulator takes less than 60 seconds. The interface is thoughtfully designed to be intuitive for beginners while offering enough depth to satisfy advanced learners. Here's your complete step-by-step guide. Step 1: Open the Simulator Navigate to app.osi-model-simulator.roboticela.com in any modern web browser. No account required, no download necessary, and no cost. The app loads instantly and is ready to use immediately. Alternatively, visit the landing page to learn more about features and download the desktop app for offline use. Step 2: Enter Your Message In the message input field, type any text you like. This is the "data" your simulation will encapsulate. Examples: Hello, World! GET /index.html HTTP/1.1 {"user": "alice", "action": "login"} Your own name or a phrase you'll remember Using a personally meaningful message makes the encapsulation feel real rather than abstract. Step 3: Choose Your Protocol Select from five real protocols: HTTP, HTTPS, SMTP, DNS, or FTP. Each choice changes the Application Layer headers added to your data. For beginners, start with HTTP. Then re-run with HTTPS to see the Presentation Layer encryption difference. Step 4: Choose Your Transmission Medium Select your Physical Layer medium: Ethernet, Wi-Fi, Fiber Optic, Coaxial, or Radio. This affects how the Physical Layer is visualized at the end of the simulation. Step 5 (Optional): Set Custom IP Addresses For a more realistic Network Layer demonstration, enter a source IP address (simulating your device) and a destination IP address (simulating the server). This makes the Layer 3 packet header concrete and personally relevant. Step 6: Run the Simulati on Click the Run or Start button. Watch as your message travels through all seven layers: Application Layer adds protocol headers Presentation Layer adds encryption (if HTTPS) Session Layer adds session management Transport Layer segments and adds TCP/UDP header Network Layer wraps in IP packet Data Li

If you've ever hit Unexpected token in JSON at position 42 or Unterminated string , there's a good chance an unescaped character broke your payload. JSON is strict about what's allowed inside a string, and the fix is almost always escaping . Here's the practical version. What does escaping a JSON string mean? A JSON string is wrapped in double quotes. Any character that would confuse the parser must be replaced with a backslash escape sequence. Escaping doesn't change the meaning of your text — it just makes the string valid JSON so parsers can read it. Unescaping is the reverse: turning those sequences back into readable characters (handy when you copy a value out of logs or an API response). The characters you must escape JSON defines exactly seven characters that must be escaped inside a string: Character Escaped as Double quote " \" Backslash \ \\ Newline \n Carriage return \r Tab \t Backspace \b Form feed \f The forward slash / may optionally be escaped as \/ , but it isn't required. Unicode can be written as \uXXXX (four hex digits). JSON escape examples Double quotes — He said "hello" becomes: "He said \" hello \" " Backslashes (Windows paths) — C:\temp\file.txt becomes: "C: \\ temp \\ file.txt" Newlines and tabs — a two-line, tabbed string becomes: "Line 1 \n Line 2 \t Tabbed" How to escape and unescape JSON in code In production you rarely escape by hand — every language has it built in. JavaScript const escaped = JSON . stringify ( text ); // escape const back = JSON . parse ( escaped ); // unescape Python import json escaped = json . dumps ( text ) # escape back = json . loads ( escaped ) # unescape Java (Jackson) ObjectMapper mapper = new ObjectMapper (); String escaped = mapper . writeValueAsString ( text ); String back = mapper . readValue ( escaped , String . class ); C# (.NET) using System.Text.Json ; string escaped = JsonSerializer . Serialize ( text ); string back = JsonSerializer . Deserialize < string >( escaped ); Common escaping mistakes (and f