How Leo Built Hyperping to $16K/Month in a Market Full of Competitors
The uptime monitoring market in 2020 was not underserved. Pingdom, UptimeRobot, StatusPage, Better Uptime — established players with years of product development and large user bases. Leo launched Hyperping anyway.
He was right to.
The actual problem he was solving
Leo wasn't trying to replace Pingdom. He noticed something more specific: most existing uptime tools were built around the assumption that a website is a monolith. One URL, one status.
But web infrastructure had shifted. Teams running microservices needed to monitor dozens of endpoints simultaneously and communicate their status to non-technical stakeholders — product managers, clients, executives — who didn't want to read a wall of green and red dots.
The gap wasn't in uptime checking. It was in the status page that came after: the interface that turned monitoring data into something a non-engineer could understand at a glance.
That's what Hyperping built. The monitoring came first. The beautiful, customizable status page was the differentiator.
How he built it
Leo did not spend months planning. He built an MVP over evenings and weekends — roughly four weeks of part-time work — focused on the core loop: monitor an endpoint, display its status on a branded page.
| Stage | Duration | Focus |
|---|---|---|
| MVP build | 4 weeks (evenings) | Basic monitoring + status pages |
| Beta | 3 months | User feedback and iteration |
| Product Hunt launch | 1 day | Public exposure |
What he didn't do during this period: build features users hadn't asked for. He stayed deliberately narrow.
The launch and what it produced
Hyperping launched on Product Hunt and landed third place for the day. Not top of the charts — but enough.
Over 1,000 visitors came through in the first 24 hours. Some converted immediately to paid. The launch wasn't the end; it was the beginning of a feedback loop.
Leo's approach to feedback was unusually direct. He gave users his personal contact details. He sent messages like: "Hey, how's Hyperping working for you? Anything annoying you'd like me to fix?" He made it easy to reach him and responded quickly when people did.
This is less common than it sounds. Most founders hide behind a ticketing system or a support email by the time they launch. Leo's directness meant users became invested in improving the product — they weren't customers of a faceless tool, they were early collaborators on something being built in the open.
The revenue structure that got to $16K/month
The pricing model was simple. Three tiers targeting different use cases:
| Plan | Price | Primary use case |
|---|---|---|
| Basic | $14/month | Small teams, single project |
| Pro | $49/month | Multiple services, custom branding |
| Business | $199/month | Team accounts, priority support |
Most customers gravitated toward the mid and upper tiers — not because they were pushed there, but because the use case justified the price. A team using status pages to communicate with clients has a clear business reason to pay for custom branding.
Annual billing was offered at a discount. Many customers took it. This smoothed cash flow and reduced churn by committing customers to a longer window.
The path to $16K/month: roughly 150 customers averaging $100+ per account. Not thousands of $5/month users. A smaller number of customers getting genuine value from a product that solved a specific problem well.
What this illustrates
A few things stand out from Leo's approach that aren't obvious from the headline numbers:
He didn't need a new category. Uptime monitoring is decades old. He found a specific version of the problem — the status page communication gap — that incumbents had solved poorly. The market being crowded didn't matter because he wasn't going head-to-head.
Personal access was a strategy, not just a personality trait. Making himself reachable created a feedback loop that shaped the product in ways a support ticket queue wouldn't. It also built trust that reduced churn — users don't leave products built by people they can actually talk to.
He launched before it was ready and iterated after. The three-month beta period wasn't pre-launch polish. It was post-launch learning with real users. The product that reached $16K/month was meaningfully different from the product that launched on Product Hunt.
This kind of build — narrow focus, direct user access, iterating toward product-market fit rather than assuming it — is harder than it looks from the outside.
If you're working on something early-stage and trying to figure out what version of the problem to solve, that's a conversation worth having before you build.
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