Reliability engineers are the best SDLC problem solvers because...
they look at the system with fresh eyes and can spot patterns people too close to the problem have learned to ignore. I'll cover how you can do this later in the post.
One thing I’ve learned from watching reliability masters doing their magic is that SREs end up solving the SDLC problems no one else sees — at least not clearly.
It’s not because SREs are better at debugging.
It’s not because SREs are the “process optimizers” (that one still surprises people when I say it).
It’s because SREs look at the system from a different altitude.
They can see the parts of the SDLC that quietly shape everything but rarely show up as activities/outcomes in Jira, Git, or dashboards.
Most engineering teams have been indoctrinated into an industrialized version of DevOps. The daily mantra: ship new features, open more branches, close more tickets.
But a surprising amount of reliability pain comes from the parts of the SDLC that don’t fit neatly into that cycle. The things no one “owns,” because they’re not obviously tied to delivery velocity.
A few examples you’ll recognise instantly:
The release cadence frozen in 2022 - everyone remembers what kind of year that was
The ticket queue that magically moves because one engineer quietly triages it every morning
The API contract that changed three times, but half the dependent services never updated their call parameters
These things fade into the background because everyone’s racing to grow services, not slowing down to prune the system with bonsai-level care.
That’s where the outsider advantage kicks in.
Because SREs work across multiple teams and tech stacks, they spot patterns that day-to-day insiders simply stop seeing.
Not because those engineers lack skill, but because familiarity blinds you to the system’s oddities.
This clicked for me while recently watching a live lecture by William Dalrymple, the Scottish historian known for his work on India’s colonial period.
His biggest discoveries came from re-reading old sources differently.
He reviewed materials that other historians had access to but rarely prioritized, including Persian court chronicles, Maratha records, Portuguese archives, and private letters sent by English sailors.
He said his craft isn’t about hunting for hidden facts. It’s about noticing the things filtered out over time by local and foreign historians.
He compared it to walking through London as a tourist. Suddenly, every red postbox, royal crest, and double-decker bus jumps out at you.
Residents never see them that way. Their brains auto-classify those details as “background texture.”
Masterful SREs do something similar in the SDLC.
They notice the “background texture” that quietly shapes reliability but has become invisible to the people living inside the system every day.
Their edge isn’t extreme technical depth (though a baseline is obviously required).
Their edge is that they refuse to go numb to the system’s defaults.
My own soft landing into reliability looked exactly like this:
In the early 2010s, I co-founded a startup in a high-stakes finance vertical. Reliability wasn’t optional. It was the credibility signal that clients judged us on. If the system shook, the business shook. That forces one to notice what others gloss over.
Years later, the healthcare organization I worked in went through a messy public–private partnership digital-transformation program. You can imagine how well that went. Azure was still new to most of the engineers, incidents piled up, and we kept hitting reliability problems nobody could quite trace.
Somehow I ended up being the one who had to spot what everyone else missed and push it through the chain every week. Not the flashy issues — the structural ones: workflow drift, mismatched expectations, fuzzy ownership, and architecture shaped by people with PhDs in bureaucracy and technical skills ending with Internet Explorer.Here’s the part engineers sometimes underestimate:
Fresh eyes are a skill. You can train this skill.
A few practices could make a massive difference for your own reliability work:
1. Become a tourist every week
Write yourself a weekly tourist pass that lets you pick a workflow or pipeline at random, and then walk through it like you’ve never seen it.
What steps only make sense because you already know the history or how your org works? Because the next person working on this workflow or pipeline might not.
2. Audit the default settings
Most regressions result from defaults no one has revisited on a regular cadence, so review the retry logic and thresholds, but also the ownership and handoffs.
If you say to yourself, “Why is this the way it is?”, that’s your sign to dig deeper.
3. Seek out organizational complacency
Identify 3 things your org treats as normal — the “that’s how we’ve always done it” — but really shouldn’t be. For example, tech debt is easy to blame, but coordination debt is harder to pin down. How does it cause downstream issues?
Reliability improves the moment you start paying attention to the parts of the SDLC that everyone else filters out. That’s the real SRE advantage, and it’s available to anyone who wants to develop it.
When you mention "the parts of SDLC that others often overlook," how can I train myself to notice these risks earlier as an individual who just started working in the SRE space and has limited knowledge of the SDLC?