How I turned Zig into my favorite language to write network programs in

Original Article ↗ Hacker News Discussion ↗

Zig’s IO Overhaul and Project Maturity

  • Several comments question whether now is a good time to adopt Zig, given the ongoing, intrusive redesign of its IO model (std.Io, new Reader/Writer, green-threading).
  • Experiences differ:
    • Some report multi‑year Zig projects where most upgrades required only minor namespace or option-name changes, plus a few painful LLVM or IO transitions.
    • Others say practically every release breaks non‑trivial code, and are deliberately waiting for 0.16 or even 1.0 before investing further.
  • There’s tension between “it’s fine for production, just pin a version” and “frequent breaking changes mean it’s only suitable for hobby use or applications, not shared libraries.”
  • A few users are holding at 0.15.x waiting for IO changes and native backends to stabilize; others praise large production users as evidence Zig is viable.

New std.Io Design and “Coloring”

  • Upcoming std.Io will route all file/network/mutex operations through an Io interface, passed explicitly like allocators are today.
  • Supporters see this as:
    • A powerful, explicit way to mark “does IO” without forcing separate sync/async APIs.
    • Allowing choice between sync event loops and async runtimes with minimal call‑site changes.
  • Critics point out this is still API churn (e.g., std.fs.openFile deprecation, Io‑based variants) and that older code won’t “just work” without edits.
  • Debate over “coloring”: some argue IO‑taking functions are effectively colored; others stress Zig’s stackful approach allows IO‑agnostic code to work with either blocking or non‑blocking runtimes.

Async Models: Stackful vs Stackless vs Callbacks

  • The article’s Zio library uses user‑space, stackful coroutines; commenters compare three models:
    • Callback/CPS (Node, Qt, Swift): minimal runtime needs, but closure allocation/complexity.
    • Stackful coroutines/fibers (Go, libtask, Zio): simple, synchronous-looking code but require stack management and can waste memory.
    • Stackless/polling (Rust): compiler‑generated state machines with precise persistent state and no stack resizing, but limitations around recursion and more visible “async coloring.”
  • There’s substantial discussion of why many modern systems languages prefer stackless/polling for scalability and FFI, based in part on C++ coroutine research.

Coroutine Performance and Context Switching

  • A claim that coroutine context switches are “virtually free” is challenged:
    • Concerns about return‑stack predictor disruption, register saves, and cache behavior.
    • Others note Zig’s implementation (and similar ones) explicitly only switch SP/FP/IP and rely on compiler clobbers, which can be strictly cheaper than naive save/restore of all registers.
    • Microbenchmarks with trivial ping‑pong workloads show extremely low overhead, but commenters stress that realistic benchmarks are tricky.

Memory, Stacks, and GC

  • Discussion over stackful coroutines’ RAM cost:
    • Fixed per‑task stacks risk either overflow or over‑allocation; tuning per platform is error‑prone.
    • Some argue you can use big virtual stacks and overcommit, or even dynamically grow stacks with VM tricks; others point out this is platform‑dependent and complicated by pointer aliasing.
  • Comparisons with Go’s growable stacks, older segmented stacks, and why those were abandoned for performance reasons.
  • Side discussion about garbage collection:
    • Examples of real‑time/low‑latency GCs in defense systems used to argue against blanket “GC phobia.”
    • Counter‑arguments that even best‑case GC latencies are in a much larger class than ~µs‑scale context‑switch costs, and thus unsuitable when ultra‑low latency/throughput is paramount.
    • Rust’s historical GC and green‑thread era is mentioned as something that was removed due to performance tradeoffs.

Timeouts and Cancellation in Async IO

  • A reader asks how Zio handles long‑blocking reads and application‑level heartbeats.
  • Library author sketches a future design similar to Python’s asyncio.timeout: a separate timeout object that cancels or wakes a task if it’s blocked in IO.
  • Multiple commenters note timeouts and cancellation are generally the hardest, most glossed‑over aspects of async frameworks; basic async read/write is comparatively easy.
  • One reminder that OS‑level socket read/write timeouts exist via setsockopt, but they’re a different mechanism from structured, task‑level cancellation.

Stackful Coroutines vs Clarity and Embedded Constraints

  • One embedded developer (with tight RAM budgets) prefers “colored” async (Rust‑style) because the synchronous illusion can obscure which calls truly block.
  • Another argues Zig’s forthcoming IO interface improves traceability of IO up the call chain while still letting code be oblivious to sync vs async scheduling.
  • There’s speculation that if Zig gains a built‑in way to compute maximum stack usage for a function (no recursion/FFI), some stackful vs stackless memory advantages may blur.

Why Callbacks (Still) Dominate

  • Several comments explore why callback‑style async became “standard”:
    • It maps naturally to interrupts and OS APIs.
    • Stackless/polling or callback models integrate more cleanly with existing tooling (debuggers, unwinding, GC, instrumentation) and compiler assumptions.
    • Stack‑manipulating runtimes can stress or break external tools and compiler backends, raising maintenance and ecosystem risks.

Naming Collisions and Ecosystem Notes

  • Multiple remarks highlight that “Zio/ZIO” is already a well‑known Scala concurrency library; some find the reuse confusing.
  • Brief mentions of related tools: Qt bindings for Zig and Go, Rust’s lack of a comparable, ergonomic Qt binding, and a meta‑comment that language discussions often conflate language design with ecosystem and async libraries.