7 Go-to-Market Lessons from Netdata’s Journey to 66,000 GitHub Stars

7 Go-to-Market Lessons from Netdata’s Journey to 66,000 GitHub Stars

Most infrastructure monitoring companies spend millions on sales and marketing. Netdata spent zero and still attracts 10,000 new users daily. In a recent episode of Category Visionaries, Costa Tsaousis, CEO and Founder of Netdata, revealed how they built a go-to-market engine powered by product quality.

Lesson 1: Solve the Real Problem, Not the Obvious One

Costa didn’t set out to build “better monitoring.” He wanted to eliminate console access entirely. “I was looking for a solution to kill the console. So I didn’t want my engineers and my team to spend time on the console tools and the likes,” he explains.

This reframing changed everything. Instead of incrementally improving existing monitoring workflows, Costa asked: what if you never needed SSH access at all? The answer required “everything the console provides, everything you can find by SSH into a server. So all the metrics, independently of whether they are useful or not, or whether we know about them or not.”

The GTM lesson: your customers say they want “better X” but what they actually need is to never think about X again. Find the elimination play, not the improvement play.

Lesson 2: Zero Configuration Beats Better Configuration

The monitoring market already had dozens of solutions when Netdata launched. What made it different wasn’t features—it was the elimination of setup time. “Once you build a thing and you know, this starts up and starts collecting stuff by itself, you don’t do anything,” Costa explains. “It finds a database server, it connects to, it starts connecting stuff from the database, it finds these containers, network interfaces, whatever it is there.”

Traditional monitoring tools required teams to manually configure every metric, dashboard, and alert. Netdata made a radical bet: automate everything. “Let the application know all the metrics, all the dashboards, all the alarms that need to be used here, and let it automatically start them up.”

This wasn’t just convenient—it was transformative. “The moment you install it, you have a comprehensive monitoring solution. You did nothing actually to get it.” When your product can deliver value in minutes instead of months, word-of-mouth becomes inevitable.

Lesson 3: Product Completeness Is a Moat

Costa describes Fortune 500 companies shutting down custom monitoring systems to use Netdata. “They shut down the monitoring systems that they have developed themselves using, of course, open source tools or proprietary tools or whatever, in order to use the data,” he notes.

Why? “They find that the completeness of the data is such that they can never do it by themselves. They don’t have the skills, the time, the effort.”

The insight: when you package standardized infrastructure knowledge into your product, you create unreplicable value. “All of the companies across the world have to go through the same process,” Costa observed. If 95% of infrastructure is standardized, why should every company recreate the same monitoring?

Lesson 4: Community Metrics Are Fundraising Metrics

When Costa started fundraising, he had no background in US venture capital. But he had something better: undeniable traction. “I would say that for me, it was relatively easy, mainly because the project has a lot of traction,” he explains.

The specific metrics that mattered: 66,000 GitHub stars, leading the CNCF observability category, 250,000 daily Docker Hub downloads, and 5,000-10,000 new user signups daily. “All this community and all these figures and all these stars and all these downloads, you know, and all this kind of stuff made it very appealing for them.”

For technical founders building in crowded markets: open source adoption metrics can carry more weight than revenue, especially early-stage. They prove product-market fit in a way that’s impossible to fake.

Lesson 5: Launch Timing Matters Less Than Launch Venue

Costa released Netdata on GitHub and “nothing happened.” He’d spent months building something that solved real problems, yet it languished in obscurity. Then he tried a different approach: “One morning, I write a post on Reddit and say, okay, guys, I build this tool, check it on GitHub if you like it. And boom, it went viral at the top of hacker news. Hundreds of people, thousands of installations.”

The product hadn’t changed. The venue had. For developer tools, being present where developers already congregate—Reddit, Hacker News, relevant subreddits—matters more than polish or perfect timing. One well-placed post in the right community can generate more traction than months of gradual GitHub growth.

Lesson 6: Rethink Distribution, Not Just Product

Netdata’s technical architecture enabled a GTM advantage. While competitors centralized data, creating bottlenecks, Netdata distributed it. “You install as many data agents as you need out there on all your servers,” Costa explains. The agents form “a massive distributed database that is spread all over the infrastructure.”

The result: “You can scale to infinity, and still you don’t need to scale up the servers by bigger servers and the likes just for monitoring.” A Fortune 500 company faces the same friction as a startup: none.

The lesson: technical architecture can eliminate sales objections before they arise. If your design removes scalability concerns, those aren’t just features—they’re sales accelerators.

Lesson 7: Your Hardest Problem Won’t Be the Product

After solving technical challenges from distributed databases to edge-based machine learning, Costa identifies an unexpected bottleneck: remote work. “Building the product is not that hard. But managing a company that is 100% remote is probably the toughest,” he admits.

The issue isn’t tools or communication—it’s knowledge management. Without proper systems, remote employees “will be struggling. There will be a lot of noise or misunderstanding or things that you heard here and there that are not company decisions.”

For founders scaling distributed teams: infrastructure for human coordination may matter more than infrastructure for code. The GTM machine only works if the team executing it has clarity on decisions, priorities, and direction.

The Meta-Pattern

Costa frames Netdata’s position uniquely: “We are racing against ourselves, we’re not racing against someone else, because the product is so unique.”

This captures the core GTM insight across all seven lessons. When you truly differentiate—by eliminating problems rather than improving solutions, by automating what others require manual work for, by building completeness that’s impossible to replicate internally—competition becomes largely irrelevant.

The market is “thirsty” for real solutions. Even Fortune 500 companies “need solutions, they need tools.” Your constraint becomes execution speed, not competitive positioning. Build something genuinely different, eliminate all setup friction, and let product quality drive distribution.