Introduction
Refactor that flaky component? Optimize this slow SQL query? Rewrite that service to support bulk operations?
Every startup accumulates technical debt—it’s not a bug, it’s a feature of moving fast. But when the team finally gets time to “invest in infrastructure,” it’s easy to get overwhelmed by the backlog. The temptation is to fix everything. After all, it’s all debt, right?
The truth is: not all tech debt is worth paying down, and not every optimization is actually an improvement. Some will save you time and money. Others are over-optimizations that burn engineering cycles without moving the needle.
That’s why backend optimization projects need structure. The most impactful ones start with a clear KPI, a focused scope, and a plan to deliver value fast and visibly.
In this post, I’ll walk through a simple framework I use when approaching backend optimization:
If you’re a backend engineer or platform team trying to turn good technical instincts into real results—this post is for you.
Step 1: Anchor the Work to a KPI That Justifies the Effort
The first step in any backend optimization project should be to define the specific metric you’re trying to move. This sounds obvious, but it’s surprisingly easy to skip—especially when the motivation is vague, like “we need to invest in infra” or “we have tech debt to clean up.”
But here’s the catch: the more accurate and meaningful your KPI is, the better your decisions will be throughout the project. A fuzzy goal leads to fuzzy execution. A sharp metric helps you stay focused, evaluate trade-offs, and measure impact along the way. Otherwise, you risk solving the wrong problem—clean code, better design… but no real value.
Ask yourself:
- Are we trying to reduce P99 latency on specific route?
- Cut infra cost (e.g. DB load, container count)?
- Improve stability (e.g. error rate, outages)?
- Reduce toil (e.g. on-call pages, flaky jobs)?
Here are a few examples of good, focused KPIs:
- “Bring all GET requests under 1 second to improve perceived speed and user experience.”
- “Support 2x write throughput to meet Q4 traffic growth without increased latency.”
Pick one KPI that matters outside your team—something product, ops, or leadership would recognize as valuable. If your project moves that number, it’s easier to justify the time spent, earn buy-in, and align others behind your effort.
Step 2: Map Out Your Optimization Options
Once you’ve picked a KPI, the next challenge is figuring out where the opportunities really are. This is where measurement and intuition intersect.
Sometimes the answers come from data, and sometimes from collective team intuition. Both are useful—but to turn intuition into action, you need to ask the right questions and dig into what’s actually happening in the system.
For example, if you’re trying to cut infra costs, start by asking:
- Which component is costing us the most? Is it the database, compute, or something else?
- What are the heaviest routes? Where does most of the traffic flow?
- How many external service calls are we making, and are they necessary?
This is often when you realize: we don’t actually know. Maybe you’re flying blind on certain paths, or your metrics aren’t broken down in a useful way.
That’s fine—just don’t skip it. Add the missing instrumentation. Add timers, counters, breakdowns by route, tenant, or feature. Even temporary logs can give you clarity. The sooner you do this, the sooner you can move from guessing to knowing—and the easier it is to justify your choices when you scope the project.
Step 3: Scope the Work for Maximum ROI
Now that you’ve got a list of possible improvements—and the metrics to back them—it’s time to make some decisions. The key here is to resist the urge to do everything. Instead, ask:
“What’s the smallest piece of work we can do to make progress toward the KPI?”
At this point, it helps to:
- Score each option by impact vs. effort — prioritize what gives the biggest return for the least work.
- Stay anchored to the KPI — every decision should bring you closer to the outcome you set in Step 1.
- Look for partial wins — for example, fix the slowest 20% of cases instead of rebuilding the entire system.
The goal isn’t just to solve the problem—it’s to solve the right slice of the problem.
Sometimes, that slice is smaller than you think.
In one project, we reduced our primary database load by 35% —just by removing a handful of unnecessary queries in our most heavily used route.
The key wasn’t some massive refactor. It was collecting the right metrics, understanding our traffic patterns, and realizing that some queries weren’t actually needed. A few well-placed changes—just rewriting or removing a couple of lines of code—had a huge impact.
Step 4: Ship in Small, Measurable Milestones
Once you’ve scoped the work, the focus shifts to delivery strategy. Backend optimization projects are especially risky when treated as “big bang” changes—hard to test, roll back, and tough to show progress. Instead, aim to break the work into small, safe, and measurable steps.
A few tactics that help:
- Use feature flags to control rollout by user, tenant, or traffic slice.
- Release behind kill switches in case of regressions.
- Track impact metrics from day one (even before full rollout).
- Structure the work in small PRs to keep velocity and reduce risk.
You want to create a delivery plan where each step builds confidence and shows value—internally or externally.
Summary
It’s easy to get lost in backend optimization—chasing cleanups, overhauls, or performance wins that don’t actually matter. I’ve made that mistake more than once.
What changed for me was realizing that optimization isn’t just about fixing things—it’s about focusing. It’s about knowing why you’re doing the work, what outcome you’re aiming for, and how to get there without burning weeks on things that don’t move the needle.
When you connect your effort to a real KPI, scope it smartly, and ship in small steps, backend work becomes more than tech debt cleanup—it becomes a force multiplier.