The State of Async Rust: Runtimes | corrode Rust Consulting

Why Bother?

Through this series, I hope to address two different audiences:

Newcomers to async Rust, seeking to get an overview of the current state of the ecosystem.

Library maintainers and contributors to the async ecosystem, in the hope that my perspective can be a basis for discussion about the future of async Rust.

In the first article, we will focus on the current state of async Rust runtimes, their design choices, and their implications on the broader Rust async ecosystem.

One True Runtime

An inconvenient truth about async Rust is that libraries still need to be written against individual runtimes . Writing your async code in a runtime-agnostic fashion requires conditional compilation , compatibility layers and handling edge-cases .

This is the rationale behind most libraries gravitating towards the One True Runtime — Tokio .

Executor coupling is a big problem for async Rust as it breaks the ecosystem into silos. Documentation and examples for one runtime don’t work with the other runtimes .

Moreover, much of the existing documentation on async Rust feels outdated or incomplete. For example, the async book remains in draft, with concepts like cancellation, timeouts, and FuturesUnordered yet to be covered. (There is an open pull request , though.)

That leaves us with a situation that is unsatisfactory for everyone involved:

For new users, it is a big ask to navigate this space and make future-proof decisions.

For experienced users and library maintainers, supporting multiple runtimes is an additional burden . It’s no surprise that popular crates like


     reqwest

simply insist on Tokio as a runtime .

This close coupling, recognized by the async working group , has me worried about its potential long-term impact on the ecosystem.

The case of `async-std`

async-std was an attempt to create an alternative runtime that is closer to the Rust standard library. Its promise was that you could almost use it as a drop-in replacement.

Take, for instance, this straightforward synchronous file-reading code:

use std::fs::File;
use std::io::Read;
fn main() -> std::io::Result<()> {
    let mut file = File::open("foo.txt")?;
    let mut data = vec![];
    file.read_to_end(&mut data)?;
    Ok(())
In async-std, it is an async
operation
instead:
use async_std::prelude::*;
use async_std::fs::File;
use async_std::io;
async fn read_file(path: &str) -> io::Result<()> {
    let mut file = File::open(path).await?;
    let mut data = vec![];
    file.read_to_end(&mut data).await?;
    Ok(())
The only difference is the await keyword.
While the name might suggest it, async-std is not a drop-in replacement
for the standard library as there are many subtle differences between the
two.
Here are some examples of issues that are still open:
New thread is spawned for every I/O request
OpenOptionsExt missing for Windows?
Spawned task is stuck during flushing in
File.drop()
It is hard to create a runtime that is fully compatible with the standard
library. Even if it were a drop-in replacement, I’d still ponder its actual merit.
Rust is a language that values explicitness. This is especially true for
reasoning about runtime behavior, such as allocations and blocking operations.
The async-std’s teams proposal to “Stop worrying about
blocking”
was met with noticeable community skepticism and later retracted.
As of this writing, 1754 public crates have a dependency on
async-std and there
are companies that rely on it in
production.
However, looking at the commits over time async-std is essentially abandoned
as there is no active development
anymore:
Update: as of March 1, 2025, async-std has officially been discontinued.
The suggested replacement is smol, which is a

lightweight, much more explicit runtime, that is different to async-std in
many ways.
This leaves those reliant on the async-std
API – be it for concurrency
mechanisms, extension traits, or otherwise – in an unfortunate situation, as is
the case for libraries developed on top of async-std, such as
surf. The core of async-std has long been
powered by smol, but it is probably best to
use it directly for new projects.
Can’t we just embrace Tokio?
Tokio stands as Rust’s canonical async runtime.
But to label Tokio merely as a runtime would be an understatement.
It has extra modules for
net,
process- and signal
handling and
more.
That makes it more of a framework for asynchronous programming than just a
runtime.




    

Partially, this is because Tokio had a pioneering role in async Rust. It
explored the design space as it went along. And while you could exclusively use
the runtime and ignore the rest, it is easier and more common to buy into the
entire ecosystem.
Yet, my main concern with Tokio is that it makes a lot of assumptions about how
async code should be written and where it runs.
For example, at the beginning of the Tokio
documentation, they state:
“The easiest way to get started is to enable all features. Do this by enabling
the full feature flag”:
tokio = { version = "1", features = ["full"] }
By doing so, one would set up a
work-stealing,
multi-threaded runtime
which mandates that types are Send and 'static and makes it necessary to use
synchronization primitives such as
Arc and
Mutex for all but the
most trivial applications.
  A 'static trait bound mandates that the type does not contain any non-static
references. This means the receiver can hold on to the type
indefinitely without it becoming invalid until they decide to drop it.
Here is an example of an async function that has a 'static lifetime bound:
async fn process_data<T: 'static>(data: T) {
    // ...
Owned data passes a 'static lifetime bound if it, and all of its contents, do
not contain any non-static references — but, crucially, a reference to
that owned data generally does not.
Since tasks in async runtimes may outlive the scope they were created in
(especially in multi-threaded contexts), ensuring that references remain valid
for the duration of the task’s execution is challenging. This is why async tasks
often require 'static data, to guarantee that the data lives long enough or to
ensure ownership is transferred to the task.
This makes it hard to use references in async code, as borrowed data must live
as long as the task.
For most practical use-cases, this means that futures cannot borrow
data from the scope they are spawned from, unless the data lives long enough or
ownership is transferred.
This requirement marks a significant departure from
synchronous Rust, where borrowing data across function calls is commonplace.
It represents a fundamental shift in how we manage data lifetimes and ownership
in asynchronous compared to synchronous Rust.
The Original Sin of Rust async programming is making it multi-threaded by
default. If premature optimization is the root of all evil, this is the mother
of all premature optimizations, and it curses all your code with the unholy
Send + 'static, or worse yet Send + Sync + 'static, which just kills all the
joy of actually writing Rust.
— Maciej Hirsz
Any time we reach for an Arc or a Mutex it’s good idea to stop for a moment
and think about the future implications of that decision.
The choice to use Arc or Mutex might be indicative of a design that
hasn’t fully embraced the ownership and borrowing principles that Rust
emphasizes. It’s worth reconsidering if the shared state is genuinely necessary
or if there’s a simpler design that could minimize or eliminate the need
for shared mutable state (for instance by using channels).
The problem, of course, is that Tokio imposes this design on you. It’s not your
choice to make.
Beyond the complexities of architecting async code atop these synchronization
mechanisms, they carry a performance cost: Locking means runtime overhead and
additional memory usage; in embedded environments, these mechanisms are often
not available at all.
Multi-threaded-by-default runtimes cause accidental complexity completely
unrelated to the task of writing async code.
Futures should be designed for brief, scoped lifespans rather than the 'static lifetime.
Ideally, we’d lean on an explicit spawn::async instead of spawn::blocking.
Maciej suggested to use a local async
runtime which is
single-threaded by default and does not require types to be Send and
'static.
I fully agree.
However, I have little hope that the Rust community will change course at this
point. Tokio’s roots run deep within the ecosystem and it feels like for better
or worse we’re stuck with it.
In the realms of networking and web operations, it’s likely that one of your
dependencies integrates Tokio, effectively nudging you towards its adoption. At
the time of writing, Tokio is used at runtime in 20,768 crates (of which 5,245
depend on it optionally).
In spite of all this, we should not stop innovating in the async space!
Other Runtimes
Going beyond Tokio, several other runtimes deserve more attention:
smol: A small async runtime,
which is easy to understand. The entire executor is around
1000 lines of code
with other parts of the ecosystem being similarly small.
embassy: An async runtime for
embedded systems.
glommio: An async runtime for I/O-bound
workloads, built on top of io_uring
and using a thread-per-core model.
These runtimes are important, as they explore alternative paths or open up new
use cases for async Rust. Drawing a parallel with Rust’s error handling
story, the hope is that
competing designs will lead to a more robust foundation overall.
Especially, iterating on smaller runtimes that are less invasive and
single-threaded by default can help improve Rust’s async story.
Async vs Threads
If you don’t need async for performance reasons, threads can often be the
simpler alternative. — the Async Book
Modern operating systems come with highly optimized schedulers that are
excellent at multitasking and support async I/O through
io_uring and
splice. We should make better use of these
capabilities. At least we should fully lean into the capabilities of modern
operating systems.
Take our sync code to read a file from above for example.
We can call this function inside the new scoped
threads:
use std::error::Error;
use std::fs;
use std::io::Read;
use std::path::Path;
use std::{thread, time};
fn main() {
    thread::scope(|scope| {
        // worker thread 1
        scope.spawn(|| {
            let contents = fs::read_to_string("foo.txt");
            // do something with contents
        });
        // worker thread 2
        scope.spawn(|




    
| {
            let contents = fs::read_to_string("bar.txt");
            // ...
        });
        // worker thread 3
        scope.spawn(|| {
            let contents = fs::read_to_string("baz.txt");
            // ...
        });
    });
    // No join; threads get joined
    // automatically once the scope ends
(Link to playground)
Or, perhaps more aptly,
fn main() {
    let files = ["foo.txt", "bar.txt", "baz.txt"];
    thread::scope(|scope| {
        for file in files {
            scope.spawn(move || {
                let contents = fs::read_to_string(file);
                // ...
            });
    });
If this code were placed into a function, it would serve both synchronous and
asynchronous callers, completely removing the need for an asynchronous runtime.
The scheduling burden would shift to the operating system.
Async Rust promises efficient resource handling, at the cost of complexity and
worse ergonomics. As an example, if the function were async and you called it
outside of a runtime, it would compile, but not run. Futures do nothing unless
being polled; a common footgun for newcomers.
use tokio::fs;
#[tokio::main]
async fn main() {
    // This will print a warning, but compile
    // and do nothing at runtime
    fs::read_to_string("foo.txt");
(Link to playground)
If you find yourself needing to share state between threads, consider using a
channel:
use std::error::Error;
use std::fs;
use std::io::Read;
use std::path::Path;
use std::{thread, time};
use std::sync::mpsc;
fn main() {
    let (tx, rx) = mpsc::channel::<String>();
    let files = ["foo.txt", "bar.txt", "baz.txt"];
    thread::scope(|scope| {
        for file in files {
            scope.spawn(move || {
                let contents = fs::read_to_string(file);
                // ...
            });
    });
    // Receive messages from the channel
    for received in rx {
        println!("Got: {:?}", received);
(Link to playground)
Common Prejudice Against Threads
Asynchronous programming is often seen as the solution to improving performance
and scalability of I/O-bound workloads.
In a recent benchmark, traditional
threading outperformed the async approach in scenarios with a limited number of
threads. This underscores the core premise that, in real-world applications, the
performance difference between the two approaches is often negligible, if not
slightly favoring threads. Thus, it’s crucial not to gravitate towards async
Rust driven solely by anticipated performance gains.
Thread-based frameworks, like the now-inactive
iron, showcased the capability to effortlessly
handle tens of thousands of requests per
second.
This is further complemented by the fact modern Linux systems can manage tens
of thousands of
threads.
Traditional arguments against threads simply don’t apply to Rust.
Threaded code in Rust is protected from data races, null dereferences, and
dangling references, ensuring a level of safety that prevents many common
pitfalls found in other languages.
As an important caveat, threads are not available or feasible in all
environments, such as embedded systems. My context for this article is primarily
conventional server-side applications that run on top of platforms like Linux or
Windows.
Summary
Use Async Rust Sparingly
My original intention was to advise newcomers to sidestep async Rust for now,
giving the ecosystem time to mature. However, I since acknowledged that this is
not feasible, given that a lot of libraries are async-first and new users will
encounter async Rust one way or another.
Instead, I would recommend to use async Rust only when you really need it. Learn
how to write good synchronous Rust first and then, if necessary, transition to
async Rust. Learn to walk before you run.
If you have to use async Rust, stick to Tokio and well-established libraries
like reqwest and
sqlx.
While it may seem surprising given the context of this article, we can’t
overlook Tokio’s stronghold within the ecosystem. A vast majority of libraries
are tailored specifically for it. Navigating compatibility crates can pose
challenges, and sidestepping Tokio doesn’t guarantee your dependencies won’t
bring it in. I’m hoping for a future shift towards leaner runtimes, but for now,
Tokio stands out as the pragmatic choice for real-world implementations.
However, it’s valuable to know that there are alternatives to Tokio and that
they are worth exploring.
Consider The Alternatives
At its core, Rust and its standard library offer just the absolute
essentials for async/await. The bulk of the work is done in
crates developed by the Rust community.
We should make more use of the ability to iterate on async Rust and
experiment with different designs before we settle on a final solution.
In binary crates, think twice if you really need to use async. It’s probably
easier to just spawn a thread and get away with blocking I/O. In case you have a
CPU-bound workload, you can use rayon to
parallelize your code.
Isolate Async Code
If async is truly indispensable, consider isolating your async code from the
rest of your application.
Keep your domain logic synchronous and only use async for I/O and external
services. Following these guidelines will make your code more
composable
and accessible. On top of that, the error messages of sync Rust are much easier
to reason about than those of async Rust.
In your public library code, avoid async-only interfaces to make downstream
integration easier.
Keep It Simple
Async Rust feels like a different
dialect,
that is significantly more brittle than the rest of the language at the moment.
When writing libraries, the maintenance
overhead of supporting both async
and sync interfaces is not to be underestimated.
The default mode for writing Rust should be synchronous. Freely after
Stroustrup:

Inside Rust, there is a smaller, simpler language that is waiting to get out.
It is this language that most Rust code should be written in.
      Revision notes: In an earlier version of this article, I discussed async web frameworks.
However, to maintain focus, I’ve opted to address web frameworks in a dedicated
follow-up article.
Furthermore, I’ve added some clarifications regarding the performance
characteristics of async Rust after a discussion on Hacker News.
I’ve also extended the section on scoped threads for clarity.
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