Solve: How to Use FinalizationRegistry in Cloudflare Workers Without Missteps

Solve: How to Use FinalizationRegistry in Cloudflare Workers Without Missteps

Understanding the Challenge: Manual Memory in Wasm

In Cloudflare Workers, combining JavaScript with WebAssembly (Wasm) brings high-performance possibilities—but also complicates memory management. JavaScript employs automatic garbage collection, freeing developers from manual memory concerns. Wasm, however, uses a linear memory buffer that must be explicitly managed—allocating and deallocating memory manually to avoid leaks.

For example, consider this Rust-based Wasm snippet compiled for Workers:

rust

#[no_mangle]
pub extern "C" fn make_buffer(out_len: *mut usize) -> *mut u8 {
  let mut data = b"Hello from Rust".to_vec();
  let ptr = data.as_mut_ptr();
  let len = data.len();
  unsafe { *out_len = len };
  std::mem::forget(data); // JS must free this later
  ptr
}

#[no_mangle]
pub unsafe extern "C" fn free_buffer(ptr: *mut u8, len: usize) {
  let _ = Vec::from_raw_parts(ptr, len, len);
}

Then, in JavaScript:

javascript

const { instance } = await WebAssembly.instantiate(wasmBytes);
const { memory, make_buffer, free_buffer } = instance.exports;

let lenPtr = 0;
const ptr = make_buffer(lenPtr);
let len = new DataView(memory.buffer).getUint32(lenPtr, true);
const data = new Uint8Array(memory.buffer, ptr, len);
console.log(new TextDecoder().decode(data));  // “Hello from Rust”
free_buffer(ptr, len); // Must be called to avoid memory leak

The pattern clearly demands manual cleanup—forgetting free_buffer() leads to leaks and performance issues.

Enter FinalizationRegistry: What It Offers—and Limits

To help, Cloudflare now supports JavaScript’s FinalizationRegistry in Workers. This API attaches cleanup behavior to objects once they’re garbage-collected, which can simplify memory safety across such boundaries.

A typical implementation:

javascript

const cleanup = new FinalizationRegistry(({ptr, len}) => {
  free_buffer(ptr, len);
});

const buf = new Uint8Array(memory.buffer, ptr, len);
cleanup.register(buf, {ptr, len});

Once buf becomes unreachable, the registry may eventually invoke the callback to free the Wasm buffer.

But it’s non‑deterministic. Engine authors explicitly warn that finalizers may never run—or run much later, making them unreliable for crucial cleanup.

Cloudflare recommends using explicit freeing as the primary strategy. FinalizationRegistry is merely a safety net to catch leaks when other cleanup logic fails.

Practical Use & Developer Best Practices

To integrate FinalizationRegistry safely:

• Use explicit freeing at all logical code exit points.
• Wrap allocations in factory functions that both allocate and free deterministically.
• Use FinalizationRegistry only to guard forgotten cleanup, not perform essential logic.

Example combined approach:

javascript

class WasmBuffer {
  constructor(ptr, len) {
    this.ptr = ptr;
    this.len = len;
    this.data = new Uint8Array(memory.buffer, ptr, len);
    cleanup.register(this.data, {ptr, len});
  }

  dispose() {
    free_buffer(this.ptr, this.len);
    cleanup.unregister(this.data);
  }
}

When the buffer goes out of scope, dispose() is best; FinalizationRegistry catches ones that slip through.

Cloudflare’s Safeguards & the Future

Cloudflare deliberately restricts registry callbacks in Workers: no I/O, no fetches or logs, reducing dangerous dependencies on non-deterministic cleanup. Callbacks run only after microtasks complete, avoiding sync issues during event processing.

They also highlight the upcoming Explicit Resource Management (ERM) proposal—featuring using blocks and dispose protocols—for truly deterministic cleanup. Here's a preview:

javascript

class WasmBuffer {
  constructor(ptr, len) {
    this.ptr = ptr; this.len = len;
  }
  [Symbol.dispose]() {
    free_buffer(this.ptr, this.len);
  }
}

{
  using buf = new WasmBuffer(ptr, len);
  // work with buf…
} // cleanup runs here, deterministically

This next-generation approach pairs well with FinalizationRegistry as a fallback when ERM isn't viable.

Monitoring and Debugging Memory Leaks in Workers

When working with FinalizationRegistry and manual memory management, it’s not enough to write clean code—you also need to verify it behaves as expected. While Cloudflare Workers don’t currently offer deep per-request memory profiling, you can still observe runtime behavior through log output and system-level monitoring.

Start by checking memory usage via Workers dashboard logs or Logpush metrics. A steadily growing memory footprint in long-lived or Wasm-heavy Workers suggests leakage. Locally, tools like htop, top, or wrangler dev allow process-level observation.

Add temporary logging to your cleanup paths:

javascript

const cleanup = new FinalizationRegistry(({ptr, len}) => {
  console.log("Finalizer triggered for ptr:", ptr, "len:", len);
  free_buffer(ptr, len);
});

Or monitor that .dispose() is called explicitly. A high ratio of explicit disposals to finalizer invocations is a healthy signal.

Final Word

Cloudflare’s implementation of FinalizationRegistry in Workers is a welcome addition—but only as a secondary measure. Developers should design their systems around explicit cleanup, treating finalizers as a fallback against accidental leaks. With best practices, future ERM syntax, and visibility into memory use, this tool becomes part of a responsible memory strategy—not a risky shortcut.

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Written by Aaron Rose, software engineer and technology writer at Tech-Reader.blog.