Upgrades Are Like Moving House—you Think It’s Just a New Address
Last week I bumped a project from Rust 1.89 to 1.90. I figured, “minor version, what could go wrong?”
The next morning, alerts yanked me out of bed. Service latency jumped from 0.4 ms to 0.5 ms, CPU from 62% to 71%, and P99 latency outright doubled.
My face was basically: this makes no sense, I didn’t change a single line.
Only later did I realize Rust 1.90 made a few “invisible” tweaks. It’s like moving into a new place and finding all the outlets are in different spots—same furniture, suddenly awkward to use.
What Changed? The Compiler’s Quiet Moves
Rust 1.90 adjusted two key internal behaviors:
- Async state machines got “fatter”: the compiler now keeps more intermediate states instead of aggressively optimizing them away.
- Borrow checking is stricter: code that used to “sneak by” now triggers deeper lifetime analysis.
Think of it as your building’s security: they used to just check the access card, now it’s card + face scan + fingerprints + ID. Safer, but the line to get in is longer.
Pitfall #1: The “Harmless” Iterator
Take this snippet—looks fine, right?
async fn compute(data: Vec<u8>) -> usize {
let sum: usize = data.iter().map(|x| *x as usize).sum();
sum
}
Looks normal, but there’s a performance trap.
In Rust 1.89 the compiler would aggressively optimize this iterator chain. In 1.90 the generated async state machine keeps more intermediate frames to guarantee memory layout safety.
Measured impact:
| Version | Per-call latency |
|---|---|
| 1.89 | 46 µs |
| 1.90 | 83 µs |
That’s a 37 µs gap. Tiny per call, catastrophic when you’re doing hundreds of thousands per second.
Fix? Switch the iterator chain to an explicit loop:
async fn compute_fast(data: &[u8]) -> usize {
let mut sum = 0_usize;
for x in data {
sum += *x as usize;
}
sum
}
That yields a simpler state machine and runs fast on 1.90 too. In practice you can recover 17–24% performance.
Pitfall #2: Poll “Rebuild” Cost Went Up
Rust devs share an unwritten assumption: if a Future finishes after a single poll, its internal state should be lightweight.
1.90 breaks that assumption.
Consider:
async fn run() {
for _ in 0..10 {
work().await;
}
}
async fn work() {
tokio::task::yield_now().await;
}
On 1.89, run() would reuse more internal state. On 1.90, each loop iteration rebuilds more than before.
Here’s the idea:
(Polling path)
+----------+ +-----------+
| Future | ---> | Poll #1 |
+----------+ +-----------+
| |
| Done? -------> No
| |
v v
+-----------+ +-----------+
| Rebuild | <--- | Poll #2 |
+-----------+ +-----------+
1.89 skipped some rebuild steps; 1.90 adds them back for safety.
Real impact: in high-throughput systems this adds roughly 6–11% overhead.
Pitfall #3: Compile Times Grew Too
Runtime isn’t the only victim—compile times ballooned as well.
Take this simple function:
fn parse<'a>(input: &'a str) -> Vec<&'a str> {
input.split(',').collect()
}
On its own it’s fine. But if your codebase has lots of nested iterators, inline closures, and generic modules, 1.90 performs deeper lifetime analysis.
Measured compile times:
| Code size | 1.89 build | 1.90 build |
|---|---|---|
| ~8k lines | 8.3 s | 12.6 s |
Over four extra seconds. If your CI runs hundreds of builds a day, that adds up fast.
Survival Kit: Three Moves
Move 1: Break Up Complex Iterators
Avoid long iterator chains inside async blocks:
// Not recommended
async fn process(items: Vec<Item>) -> Vec<Result> {
items.iter()
.filter(|x| x.is_valid())
.map(|x| transform(x))
.filter_map(|x| x.ok())
.collect()
}
// Recommended
async fn process(items: Vec<Item>) -> Vec<Result> {
let mut results = Vec::new();
for item in items {
if item.is_valid() {
if let Ok(r) = transform(&item) {
results.push(r);
}
}
}
results
}
Move 2: Keep CPU-heavy Work Out of async
Offload heavy computation with spawn_blocking:
async fn handler(buf: Vec<u8>) -> usize {
tokio::task::spawn_blocking(move || heavy_compute(buf))
.await
.unwrap()
}
fn heavy_compute(buf: Vec<u8>) -> usize {
buf.iter().fold(0usize, |s, x| s + *x as usize)
}
spawn_blocking has overhead, but it prevents async state machines from ballooning.
Move 3: Shorten Lifetime Chains
Split long iterator pipelines into steps:
// Not recommended
fn parse_complex(s: &str) -> Vec<&str> {
s.split(',').filter(|x| !x.is_empty()).map(|x| x.trim()).collect()
}
// Recommended
fn parse_simple(s: &str) -> Vec<&str> {
let items = s.split(',');
let filtered: Vec<_> = items.filter(|x| !x.is_empty()).collect();
filtered.iter().map(|x| x.trim()).collect()
}
When Should You Stay on 1.89?
Sometimes “not upgrading” is the right call:
- Your system handles over 200k async operations per second.
- Latency budget is razor-thin.
- CPU is already near saturation.
- Compile time directly gates deployments.
- You don’t need any 1.90 features.
Tune the hot paths on 1.89 first, then rebench on 1.90.
When Should You Upgrade?
1.90 isn’t all bad. It brings:
- More predictable compiler behavior.
- Better lifetime diagnostics.
- Fewer miscompiled Futures.
- A sturdier long-term ecosystem baseline.
The performance regression is short-term pain; the correctness gains are long-term benefits.
Checklist: Is Your Codebase at Risk?
Quick self-check:
- Long iterator chains inside async functions?
- CPU-heavy loops inside async blocks?
- Lots of short-lived Futures that finish in 1–2 polls?
- Many nested closures in generic functions?
- Complex lifetime coupling between types?
If you check three or more, benchmark before upgrading.
Parting Thoughts
Rust 1.90 didn’t “break” anything. It exposed the hidden assumptions we made about specific compiler behaviors.
The lesson is simple: if your performance relies on accidental compiler optimizations, that performance is fragile.
Write explicit loops, keep lifetimes clear, separate CPU work from async state—your code will stay steady across Rust releases.
Rust evolves, and the most resilient systems evolve with it.
Did this help?
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