The Hidden Cost of “We’ll Fix It Later”
Reliability Debt Explained
"We were two days from launch. The team was tired and the product demo worked.
So we agreed: We’ll fix it later.Two weeks later, we woke up to a flooded on-call channel, a customer escalation, and 17 pages of logs."
Sound familiar?
That quiet trade-off—the one you barely remember agreeing to—that’s reliability debt.
What Is Reliability Debt?
We’re all familiar with technical debt—the code shortcuts we take now that cost us later.
Reliability debt is similar, but sneakier. It’s the silent backlog of reliability risks we delay, downplay, or defer entirely. It’s the missing alert we didn’t configure. The retry logic we promised to add next quarter. The incident review we skipped because “we already know what went wrong.”
On the surface, it looks harmless. The service is still up. The metrics don’t scream red.
But reliability debt doesn't show up when things are calm. It shows up:
During peak traffic
When your most experienced SRE is out
Or, more often, at 3:12 a.m. on a Sunday
When It Comes Due
What makes reliability debt dangerous is its unpredictable interest rate.
Unlike tech debt, which breaks builds or slows dev work in obvious ways, reliability debt tends to explode under pressure—when you're least able to respond.
Here’s what it costs you:
Longer incident timelines because telemetry lacks clarity
On-call burnout from fighting the same fires repeatedly
Escalations from customers who assumed “stable” meant dependable
A growing fear of deploying—even small changes
And ironically, it often gets worse after growth. As scale increases, small decisions compound, and minor risks become production-grade failures.
How to Spot It Early
Some signs your team may be accumulating reliability debt:
Muted alerts that stay muted
Incident reviews with “action item: TBD”
Dashboards built for compliance, not action
New services without SLOs, ownership, or operational checklists
The phrase “We’ll monitor it in prod” said one too many times
But let’s be honest: we don’t ignore these things because we don’t care.
We ignore them because we’re overloaded.
There’s too much noise.
Too many false positives.
Too many alerts that fire but don’t clearly connect to user impact.
So we stop trusting the system. And when you can’t trust alerts, you don’t act.
“We’ll fix it later” becomes default—not from apathy, but alert fatigue.
Shifting the Mindset
We’ve been there. Shipping under pressure. Balancing trade-offs. Saying yes to the roadmap and no to the reliability work.
But part of growing as an engineering organization—and as thoughtful leaders—is learning when speed without safety costs more than it saves.
So how do you start addressing reliability debt? It starts by reconnecting our operational signals to what really matters: the Customer Experience: The Reliability metric that really matters.
1. Make Alerts Actionable (and Human-Friendly)
Tighten your alerting posture. Use SLIs that actually reflect user experience—latency, availability, error rates.
If an alert doesn’t tell you something is broken for someone, it probably needs to be rethought.
2. Treat Reliability work as first-class
Just like features have deadlines, resilience should have a roadmap. Track and surface reliability debt like any other backlog item. Make it visible. Make it worth fixing.
3. Embrace controlled chaos
Use chaos engineering (automated, not ad hoc) to proactively uncover where your reliability assumptions break down.
Better to simulate failure on a Tuesday morning than experience it on a Sunday night.
4. Make Incident Reviews matter
No more “we’ll do better next time.” Use reviews to identify system gaps and engineer them out. Tie findings back to alerts, automation, and process—not just the person who got paged.
Can AI Help? Yes—but only if you’ve laid the groundwork.
In my previous post on The Future of Reliability, I wrote about how GenAI, Causal AI, and Forecasting AI can help detect anomalies, predict patterns, and guide resolution.
But here’s the catch: AI can’t prioritize what you won’t.
It can help see the debt. It won’t decide to pay it down.
Use AI to spot patterns across incidents. To auto-generate runbooks. To summarize logs. But don’t rely on it to replace engineering judgment. That’s still our job.
Final Thought: Pay It Forward, Not Later
Reliability debt is invisible—until it's not.
Every skipped alert, every unreviewed escalation, every “we’ll get to it next sprint” becomes a future tax on your team’s focus, your customer’s trust, and your ability to scale safely.
Fixing it before it breaks is hard. But it's leadership.
And your 3 a.m. self will thank you.
Now Over to You
What forms of reliability debt have you seen creep into your systems?
How do you surface it early—before it costs you a weekend?
Drop your thoughts in the comments or DM me. Let’s swap scars and strategies.
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I advise startups, coach leaders and help in lots of ways. Also if you want to start adopting a culture of reliability and AI, feel free to Contact me.