Everyone loves the fresh energy of a greenfield project: new code, clean architecture, exciting launches. Even mature code bases are fun to work with if you keep on the development side.
Even legacy codebases can spark joy when you’re on the development side, crafting new features and watching your Git commits paint green across the contribution graph.
But what happens when the champagne goes flat and the launch party ends?
What’s it really like to keep software breathing, growing, and thriving in a world where users span every timezone, expectations compound daily, and a single 500 error can trigger an avalanche of support tickets at 3 AM?
The Software Development Cycle: The Happy Path We All Know
The textbook flow looks deceptively elegant:
design → build → test → deploy
This linear progression dominates our bootcamps, methodology handbooks, and collective imagination. Delivery paradigms celebrate shipping frequency like a sacred metric.
“Move fast and break things” was once proclaimed by someone with scars of experience.
The development world has built an entire ecosystem around this forward momentum: productivity tools that measure story points completed, methodologies that optimize for feature delivery, and career ladders that reward builders over maintainers. We’ve made shipping software feel like crossing a finish line.
But here’s the uncomfortable truth: there is no finish line in real software.
The Maintenance Reality: Welcome to the Battlefield
It’s not glamorous, but someone has to keep the lights on.
Or “here’s where the child cries, but the mother doesn’t see it,” as the Brazilian saying goes.
While the development world celebrates velocity and innovation, the maintenance world operates by entirely different rules. It’s the difference between being an architect designing a beautiful building and being the superintendent who keeps it standing through earthquakes, floods, and decades of wear.
The Great Mindset Collision
Development Mode: Engineers optimize for speed, creativity, and feature delivery. Success looks like green builds, successful demos, and satisfied product managers. The dopamine hits come from solving new problems and seeing immediate results.
Maintenance Mode: Engineers optimize for stability, predictability, and risk mitigation. Success looks like silent nights, stable response times, and incidents that never happen. The satisfaction comes from disasters averted and systems that just… work.
These mindsets don’t just differ, they can actively clash. The developer who heroically ships a complex feature on Friday might create a nightmare for the engineer who gets paged about memory leaks on Sunday morning.
Consider Netflix’s experience: their development teams push thousands of deployments per day, but their Site Reliability Engineers have developed entirely separate systems for gradual rollouts, circuit breakers, and automated rollbacks. They’ve essentially built two complementary cultures within the same company.
Or look at WhatsApp’s legendary engineering efficiency: 32 engineers supporting 450 million users. Their secret wasn’t shipping faster but building robust systems that rarely needed intervention. Every line of code was written with maintenance in mind.
The Linear Illusion
Traditional methodologies assume a controlled, predictable environment where requirements are gathered, code is written, tests pass, and features ship in neat, sequential packages. But real software lives in chaos:
- Slack handles message surges during global events that make their traffic spike 10x overnight
- Zoom went from 10 million to 300 million daily users in four months during the pandemic
- Pokemon Go crashed repeatedly at launch because no model predicted players would literally gather in crowds to play
The linear model breaks down when you add:
- Exponential user growth that makes yesterday’s architecture decisions obsolete
- 24/7 global usage that eliminates maintenance windows
- Competitive pressure that demands both stability AND constant innovation
- Technical debt that compounds like interest on an unpaid credit card
Real-World Battle Stories
The GitHub Outage of 2018: A routine database maintenance task triggered a split-brain scenario that took down GitHub for 24 hours. The fix wasn’t a missing semicolon; it required coordinating database replication across multiple data centers while the entire software development world watched and waited.
Knight Capital’s $440 Million Bug: A deployment script error activated old trading code that bought and sold millions of shares in 45 minutes. The company lost nearly half a billion dollars because maintenance procedures didn’t account for dormant code reactivation.
The Heartbleed OpenSSL Bug: A memory management error in one of the internet’s most fundamental libraries exposed private keys, passwords, and personal data across millions of websites for two years. The bug wasn’t in flashy new features but in the unglamorous memory handling code that everyone assumed “just worked.”
The Constant Growth Pressure Cooker
Now add the reality of modern software markets: exponential growth in highly competitive, always-on environments.
Your infrastructure must scale from handling 1,000 requests per minute to 100,000 without dropping a single user session. Your database queries that worked fine with 50GB of data start timing out when you hit 50TB. Your authentication system that breezed through a few hundred logins per hour starts buckling under bot attacks attempting millions.
Spotify’s Growth Challenge: Spotify went from a Swedish startup to a global platform with 400+ million users. Their engineering team doesn’t just maintain code; they retain a living ecosystem that serves personalized playlists, handles real-time streaming, processes payment systems, and manages artist royalties across dozens of countries with different regulations. Every “simple” feature touches this entire interconnected web.
The development mindset says: “Ship the MVP, iterate based on feedback.” The maintenance reality says: “That MVP just became load-bearing infrastructure for millions of users who will revolt if it goes down for five minutes.”
The Hidden Heroes
The most critical work in software engineering often happens in the shadows:
- The engineer who spends three weeks optimizing a database query that shaves 200ms off response time; improvements users never notice but depend on
- The team that builds monitoring systems sophisticated enough to predict failures before they happen
- The architect who designs graceful degradation patterns so users get slightly slower service instead of error pages
- The on-call engineer who diagnoses race conditions at 2 AM while the rest of the world sleeps
In software, success isn’t just in shipping. It’s in the quiet uptime, the missed catastrophes, the seamless updates no one notices. That’s the real work, an inevitable phase of the software engineering one tells you.
Bridging Two Worlds
The future belongs to engineering cultures that honor both the builder and the keeper, the sprinter and the marathon runner. Companies like Amazon have institutionalized this with their “You build it, you run it” philosophy, making developers responsible for the operational health of their code.
Google’s Site Reliability Engineering model dedicates 50% of SRE time to engineering work that reduces operational burden, creating a feedback loop where maintenance work directly improves development velocity.
The most successful software teams don’t choose between development speed and operational excellence; they architect systems where both can thrive.
Because in the end, the most beautiful code isn’t the cleverest algorithm or the most elegant abstraction. It’s the system that runs quietly, scales gracefully, and lets users accomplish their goals without ever thinking about the engineering marvel that makes it all possible.
That’s the real romance of software engineering: building digital infrastructure so good it becomes invisible.
Originally published on my newsletter https://osns.substack.com/p/building-is-glamorous-maintenance