Why Datadog Broke Your Heart (and How groundcover Helps You Move On)

The Datadog Honeymoon: Love at First Dash

Every engineering team has a Datadog phase.

You’ve just landed Series A. You’re real now. You’ve got traffic, customers, a few dashboards and life is good.

So you do what everyone does: you sign up for Datadog. It’s the 800-pound gorilla of observability. Engineers know it, investors recognize it, and it feels like the “safe” choice.

And at first? It works. Your metrics show up, traces look pretty, and alerts actually alert.

Sure, setup takes 17 steps, agents multiply like rabbits, and you need three tabs open to find a single log—but it’s fine. You’ve got bigger fires to fight.

Until one day, the invoice hits.

From $30K to $3M: The Moment You Realize You’re the Product

The first Datadog bill that crosses six figures is a rite of passage. The second is a warning.

By the time you’re scaling hard—Series B, Series C, maybe an AI platform growing at warp speed and you’re staring at millions per year in observability costs.

You convince yourself it’s worth it: “We’re a serious company now. This is the Cadillac solution.”

But here’s the truth: you’re paying luxury prices for a shrinking view of your own system.

The Great Sampling Spiral

When the CFO starts asking why you’re spending like Netflix on monitoring, the sampling begins.

You start trimming logs.
Then metrics.
Then traces.

Then you stop indexing staging altogether because “Who needs observability in Dev, right?”

Congratulations. You’ve just built a two-tier observability experience:

• Prod is “premium” (when it works).
• Dev is “good luck, grep harder.”

Developers hate it. Debugging becomes guesswork. Tribal knowledge replaces real data. And when something blows up in production? You can’t reproduce it anywhere else.

You’ve lost visibility and ironically, you paid for it.

The Open Source Mirage

At this point, someone on the team suggests the inevitable: “Let’s go open source. We’ll save millions!”

So you spin up Grafana, Prometheus, maybe dabble in OpenTelemetry. And for a while, it feels empowering. You’re in control again.

Until the reality sets in: you’ve just traded an overpriced SaaS bill for a six-person internal team maintaining an observability Frankenstein. You’re drowning in YAML, exporters, and version mismatches.

The stack works. Barely. And it’s five times harder to keep alive than Datadog ever was.

The Real Problem: SaaS Wasn’t Built for Your Scale

Here’s the thing: Datadog doesn’t “fail.” It’s just not designed for companies that actually grow. SaaS observability is built on a volume-based pricing model. The more data you send, the more you pay. And guess what? The faster you succeed, the faster that data grows.

That’s the paradox: you’re punished for scaling.

Meanwhile, the “solutions” (sampling, splitting tools, hybrid setups) just delay the inevitable. You can cut costs this quarter but your telemetry firehose isn’t slowing down.

The BYOC & eBPF Revolution: Observability Without the Pain

This is where the next era begins and where teams finally start breathing again. Because groundcover BYOC changes everything. With Bring Your Own Cloud (BYOC), you can keep all of your data where it belongs while still getting full observability power. And when you pair it with eBPF, things really start to click. 

Instead of relying on agents, sidecars, and manual instrumentation, eBPF hooks directly into the Linux kernel. It captures the raw signals across network, system, and application layers. No code changes. No sampling. No bloat.

That means:

• Full visibility with zero trade-offs.
• Flat, predictable costs (because you’re not billed by the gigabyte).
• No more sampling roulette.
• Happy engineers who can debug anywhere, not just in prod.

At groundcover, we call it observability that actually scales with you. Not against you.

The Honest Conversation Every CTO Needs

If you’re running a hypergrowth startup and you’re still on Datadog or any SaaS observability tool it’s time for some tough love.

• Your data is growing faster than your cost savings ever will by switching to another SaaS provider.
• Your developers are wasting time juggling 10 dashboards just to correlate a trace.
• Your observability bill looks more like a ransom note than a SaaS invoice.

It’s not your fault. It’s the SaaS model’s fault. SaaS observability was built for companies that stay small. You’re not small anymore. And that’s the problem worth solving.

Conclusion: Take Back Control

You don’t have to accept that observability costs millions or that visibility means sampling.

With BYOC observability, you can see everything at any scale, without compromise.

That’s the real choice: Keep paying to see less. Or move to a model that lets you see it all.

Your engineers (and your CFO) will thank you.

Ready to break up with Datadog?

Let’s talk about how BYOC gives you your observability (and your budget) back.