🔥 It's finally here! I'm excited to announce that @ShadowTrafficIO is now available. Head to the home page to get started for free. For my entire career, I've been baffled by how long it takes to build demos, load tests, and proof-of-concept projects. Everyone's built little internal data generator tools, but none of them are good. ShadowTraffic is a tasteful, complete product that rapidly simulates production traffic to your backend—@apachekafka, @PostgreSQL, and webhooks. Help me get the word out: 👨‍💻 Hacker News: I'm on the /newest page 🛠️ Product Hunt: I'm listed under Developer Tools 📰 Reshare this post ShadowTraffic was built completely in public in just 90 days, 100% bootstrapped on my own dime. Thank you *so* much for following along guys!

Some exciting progress to share: I just added support to ShadowTraffic for statistical distributions and histograms. 📊 Why does that matter? Because now it's easy to simulate data for real-world situations like: - 20% of the users send 80% of the tweets. - 99.99% of the time, the latency between messages is 10-20ms, but 0.01% of the time it spikes to 2000ms. - Customers open, on average 20 support tickets, with a standard deviation of 5 tickets. It takes thousands of lines of pain-in-the-neck code to do this, but I've boiled it to down to a simple JSON API with two attributes: throttling and matching (see the images). Throttling tells ShadowTraffic how long to wait until to another message: "throttle": { "ms": { "distribution": { "kind": "normal", "mean": 100, "sd": 40 } } } Matching tells ShadowTraffic how to pick a foreign key (think generating posts and choosing which user posted them). This one says that 25% of the customers are responsible for 97% of the traffic: "matching": { "to": "customers.key", "histogram": [ { "frequency": 97 }, { "frequency": 1 }, { "frequency": 1 }, { "frequency": 1 } ] } I'm really excited about these features because they make load testing far more realistic, which means more stable production systems. One thing I'd love to hear from anyone following along: what production situations do you wish you more easily test? Help me tune the API based on real feedback.

🚦Solving the $10,000 demo problem with ShadowTraffic Last week, I wrote about how every demo I've been a part of has sucked up at least $10,000 in people's time. It's complicated to inject the right kind of data into your system to elicit the behavior you want. Let's fix that. Meet ShadowTraffic (link's in my bio), a service for rapidly simulating production traffic to @apachekafka. Join the waitlist to see more, but in brief, ShadowTraffic: 🌲 Has an intuitive API that's shaped like your data 💳 Ships with a huge list of realistic generators out of the box, like `Finance.credit_card` and `Address.full_address` 🔑 Supports first-class foreign-key relationships (attribute `customerID` has a match across all data sets) 📊 Has built-in distribution functions (user `Fred` posts 80% more than 90% of all other users) 🪦 Ships with built-in Kafka-isms, like tombstoning. And soon, by popular demand... 😱 Postgres support! Thanks to everyone who gave early feedback, and please repost this for anyone who might need it!

To push myself as an entrepreneur, I’m going to try something really hard: I’m launching 4 startups, with 4 products, in quarters—each one run by just me, as a solopreneur. I wrote a little about why I’m doing this. open.substack.com/pub/michae… Wish me luck. 🔥