For years, Rust has promised developers two things that rarely coexist peacefully in modern programming languages: uncompromising performance and expressive abstraction. Nowhere has that promise been more strained than in asynchronous programming. Async and await arrived in Rust as a watershed moment, bringing ergonomic concurrency to a language built for systems-level control. But they arrived with a catch. Traits containing async fn methods cannot be turned into trait objects. In practical terms, that means no straightforward dynamic dispatch — no &dyn Trait — for async traits on stable Rust Dynify.
This limitation is not a minor footnote. It shapes how libraries are designed, how embedded systems are written, and how extensible async frameworks are structured. Developers who need polymorphism at runtime have largely relied on workarounds, most notably the widely used async-trait macro, which rewrites async methods to return boxed futures allocated on the heap. That approach works, but it quietly breaks one of Rust’s most cherished guarantees: that you only pay for what you use.
Dynify emerges precisely at this fault line. It is a Rust crate designed to make async traits compatible with dynamic dispatch while preserving developer control over memory allocation. Rather than defaulting to heap-allocated futures, dynify enables in-place initialization of async state, allowing futures to live on the stack when possible. It does this entirely on stable Rust, without experimental compiler features, and with an explicit focus on environments where heap allocation is costly, undesirable, or impossible.
This article explores dynify not as a novelty, but as a signal — a sign of how far the Rust ecosystem has gone to reconcile safety, performance, and expressiveness, even when the language itself has not yet caught up.
The Core Problem: Async Traits and Object Safety
Rust’s object safety rules exist to guarantee that trait objects can be safely called through a vtable at runtime. Methods must have known calling conventions and return types that do not depend on the concrete implementor. Async functions violate this requirement in subtle but fundamental ways.
An async fn in a trait desugars into a method that returns an anonymous type implementing the Future trait. Each implementor of that trait produces a different concrete future type, even if the method signature looks identical. From the compiler’s perspective, there is no single return type that can be placed behind a vtable. As a result, async traits are not object-safe.
This design choice is intentional. Rust refuses to hide allocations or erase types implicitly. But the cost of that rigor is friction for developers who need runtime polymorphism. Without object safety, async traits cannot be used in plugin systems, heterogeneous collections, or runtime-selected backends without additional indirection.
The ecosystem responded with macros and patterns that bend, but do not break, the rules.
The Dominant Workaround: Boxing the Future
The most common solution is the async-trait pattern. Instead of returning an opaque future, async methods are rewritten to return a boxed, pinned dyn Future. The trait becomes object-safe because the return type is erased behind a pointer.
This trade-off is widely accepted because it is simple and works almost everywhere. But it introduces unavoidable heap allocation on every async call. In many applications, that overhead is negligible. In others, it is unacceptable.
Embedded systems may not have a global allocator at all. Low-latency servers may wish to minimize heap churn. Kernel-level or no-std environments may forbid allocation outright. For these use cases, async-trait solves one problem by creating another.
Dynify was designed explicitly for these cases.
Dynify’s Central Idea
Dynify does not attempt to make async traits object-safe directly. Instead, it generates a companion, dyn-compatible variant of a trait. This companion trait replaces async methods with methods that return constructor types — values that can later be used to initialize a future in a caller-provided memory location.
The key shift is conceptual. Rather than saying “this method returns a future,” dynify says “this method returns something that knows how to build a future.” The act of building the future is deferred until the caller decides where it should live.
This approach preserves dynamic dispatch while restoring control over allocation.
The crate provides macros that automate this transformation, allowing developers to annotate existing async traits and generate the corresponding dynified versions with minimal boilerplate.
Stack Allocation as a First-Class Goal
One of dynify’s most distinctive features is its support for in-place initialization. The caller supplies a fixed-size buffer — typically a stack-allocated array of uninitialized bytes. When the async method is invoked, dynify attempts to place the future into that buffer. If the future fits, no heap allocation occurs.
This design echoes patterns used in embedded C and C++, but expressed in Rust’s type system and safety guarantees. It allows developers to reason explicitly about memory usage, something that is often obscured in higher-level async abstractions.
Dynify does not prohibit heap allocation. Instead, it makes allocation an explicit choice. Developers can enable heap support as a fallback, or disable it entirely. The important distinction is that allocation is no longer implicit.
Inspired by, but Distinct from, Pin-Init
Dynify draws inspiration from in-place initialization patterns explored in crates like pin-init, which focus on safely initializing pinned data structures. Pin-init demonstrated that Rust can support complex initialization flows without sacrificing safety, but much of that work depends on unstable language features.
Dynify adapts similar ideas to async dispatch while remaining firmly within the bounds of stable Rust. Its focus is narrower — functions rather than structs — but its impact is broader for async trait ergonomics.
Where pin-init experiments with what Rust might eventually allow, dynify works with what Rust guarantees today.
Comparisons Within the Ecosystem
Dynify exists alongside other attempts to bridge async traits and dynamic dispatch.
Async-trait prioritizes ergonomics and broad compatibility, at the cost of allocation. Dynosaur explores hybrid models that preserve static dispatch where possible but still rely on heap allocation for dynamic cases. Pin-init offers powerful primitives but remains experimental.
Dynify distinguishes itself by treating heapless dynamic dispatch not as an optimization, but as a core design constraint. It does not aim to replace async-trait universally. Instead, it offers a different set of trade-offs, optimized for predictability and control.
Where Dynify Fits Best
Dynify is not for every Rust project. Its benefits are most pronounced in domains where memory behavior matters deeply.
Embedded development is an obvious candidate. When every byte of RAM is accounted for, the ability to perform dynamic dispatch without allocation can determine whether an architecture is viable.
Operating systems and low-level runtimes benefit similarly. In these environments, async abstractions are increasingly common, but heap allocation may be restricted to carefully controlled phases.
High-performance servers and networking stacks also stand to gain. Even when allocation is available, reducing pressure on the allocator can improve latency consistency and throughput.
Finally, dynify is attractive to library authors who want to offer async extensibility without forcing consumers into boxed futures or monomorphized generics.
Complexity as the Price of Control
Dynify’s approach is powerful, but it is not simple. Developers must understand lifetimes, constructor types, and buffer sizing. Error messages can be more complex than those produced by async-trait. The mental model is closer to systems programming than application scripting.
This complexity is intentional. Dynify assumes its users care deeply about memory layout and execution costs. It rewards that care with precision.
In a sense, dynify embodies a core Rust principle: abstractions should not erase important details. They should make them explicit.
Beyond Rust: Other Meanings of “Dynify”
The name “Dynify” also appears outside the Rust ecosystem, attached to unrelated companies and platforms. A consulting firm uses the name in the context of enterprise software and ERP implementations. A similarly spelled startup applies AI to contract catering and loyalty programs.
These entities share a name, but not a mission. The dynify crate stands apart as a niche, developer-focused tool addressing a specific language limitation. Its audience is small, but deeply invested.
Conclusion
Dynify is not a headline-grabbing framework or a mass-market library. It is something quieter and, in its own way, more revealing. It shows how far Rust developers are willing to go to preserve control over memory and performance, even in the face of language limitations.
By enabling dynamic dispatch for async traits without mandatory heap allocation, dynify fills a gap that many developers have simply learned to live with. It does so using stable Rust, careful design, and a willingness to trade simplicity for precision.
As the Rust language continues to evolve, native support for async trait objects may one day make crates like dynify obsolete. Until then, dynify stands as a testament to the ecosystem’s ingenuity — and to the enduring appeal of doing things the hard, correct way.
Frequently Asked Questions
What does dynify actually generate?
Dynify creates a companion, dyn-compatible version of an async trait, replacing async methods with constructor-based equivalents suitable for dynamic dispatch.
Does dynify eliminate heap allocation entirely?
It can. Dynify supports stack-only initialization when futures fit within caller-provided buffers, and heap allocation can be disabled entirely.
Is dynify a replacement for async-trait?
No. Async-trait remains simpler and more ergonomic for general use. Dynify targets specialized scenarios where allocation control matters.
Does dynify require nightly Rust?
No. Dynify is designed to work entirely on stable Rust.
Who should consider using dynify?
Developers working in embedded systems, low-level runtimes, or performance-critical async code where heap allocation is undesirable.
