Zig's Approach to Systems Programming

A modern alternative for low-level work that doesn't sacrifice safety or ergonomics

Systems programming is having a quiet renaissance. For years, C and C++ were the only realistic options for writing operating systems, embedded firmware, network services, and performance-critical tools. Rust brought memory safety and powerful abstractions to the space, but not every team can afford the learning curve or compilation model. Zig is emerging as a pragmatic middle ground: a small language that targets C’s sweet spots while offering explicit control, predictable performance, and a friendlier path for developers who need to drop close to the metal without fighting the compiler.

In this post, I’ll walk through how Zig approaches systems programming, what makes it distinct, where it fits today, and where it doesn’t. I’ll include practical code examples from real patterns, such as cross-compiling a tiny HTTP server, building a minimal embedded blinky for an STM32, and writing a Linux kernel module loader stub. You’ll also see how Zig’s tooling changes daily workflows and where it shines in production, plus honest tradeoffs for teams considering adoption.

Where Zig fits in today’s systems landscape

Zig is a general-purpose language with a focus on low-level programming and seamless C interop. It can compile C code directly, expose and consume C headers without bindings generators, and link against existing C libraries with minimal friction. That means you can incrementally adopt Zig into a C/C++ codebase and ship binaries for multiple targets from a single build environment.

Teams use Zig for:

• Embedded devices and firmware, where deterministic binaries and direct memory access matter
• Systems utilities and CLI tools that need to run on multiple platforms without heavy runtimes
• Network services and proxies that need stable performance and minimal GC-like pauses
• Cross-compiling workflows where developers want first-class support for different architectures and ABIs

Compared to alternatives:

• Vs C: Zig adds safety checks, better build system ergonomics, and error handling without runtime overhead in optimized builds.
• Vs C++: Zig avoids complex compile-time metaprogramming and hidden control flow; explicitness is a core value.
• Vs Rust: Zig offers a gentler learning curve, smaller language surface, and C-style memory model, making it easier to integrate with existing C projects. Rust’s borrow checker brings stronger compile-time guarantees, but Zig’s safety-by-default modes and optional runtime checks appeal to teams that need fine-grained control.

Zig is not a garbage-collected language, and it does not hide costs. If you allocate memory, you see it. If you want bounds checks, they are explicit. That predictability is a big part of why it fits systems work.

Core language features that matter for systems programming

Explicit control with safety modes

Zig compiles with safety checks enabled by default in debug builds. In optimized builds (-OReleaseFast or -OReleaseSmall), safety checks are removed, but you still decide when and where to enforce them. This is unlike C, where you often rely on external sanitizers or ad-hoc asserts. In Zig, you can choose between panic modes and fine-grained safety, or mark specific blocks as “unsafe” if you’re doing low-level pointer arithmetic and want zero overhead.

No hidden allocations

There is no allocator behind your back. If you need memory, you pass an allocator explicitly. This is crucial for systems code where you might avoid the heap entirely or allocate on a fixed arena. Zig’s standard library provides several strategies, such as ArenaAllocator, GeneralPurposeAllocator, and PageAllocator. The forced visibility of allocators makes ownership and lifetimes easier to reason about at scale.

C interop as a first-class feature

Zig can import C headers directly and generate bindings at compile time using @cImport and translate-c. That means you can include system headers and call into libc or vendor libraries without writing a separate binding layer. For teams with large C codebases, this lowers migration risk and maintenance burden.

Cross-compilation built in

You don’t need a separate toolchain per target. Zig ships with LLVM and its own linker, enabling you to target Linux, Windows, macOS, and bare-metal architectures from a single machine. It can produce static binaries, link against musl, and produce Windows PE files from a Mac or Linux host.

Comptime and build system integration

Zig’s comptime executes code at compile time to generate types, functions, and configuration data. Unlike macros, comptime is type-safe and part of the language. The Zig build system (build.zig) is itself Zig code, making build logic programmable without a separate DSL.

Practical examples and workflows

Example 1: Cross-compiling a minimal HTTP server

The following is a small HTTP server using Zig’s standard library. We’ll use an explicit arena allocator to keep memory simple and show how cross-compilation works using the Zig build system.

Project structure:

httpdemo/
├── build.zig
└── src
    └── main.zig

src/main.zig:

const std = @import("std");

pub fn main() !void {
    var arena = std.heap.ArenaAllocator.init(std.heap.page_allocator);
    defer arena.deinit();
    const allocator = arena.allocator();

    const port = 8080;
    var server = std.net.StreamServer.init(.{});
    defer server.deinit();

    try server.listen(try std.net.Address.parseIp4("0.0.0.0", port));
    std.debug.print("Listening on http://127.0.0.1:{d}\n", .{port});

    while (true) {
        var conn = try server.accept();
        defer conn.stream.close();

        var buffer: [4096]u8 = undefined;
        const len = try conn.stream.read(&buffer);
        if (len == 0) continue;

        // Very naive HTTP response; this is just to show the pattern
        const response =
            "HTTP/1.1 200 OK\r\n" ++
            "Content-Type: text/plain\r\n" ++
            "Content-Length: 13\r\n" ++
            "\r\n" ++
            "Hello from Zig";

        _ = try conn.stream.writeAll(response);
    }
}

build.zig:

const std = @import("std");

pub fn build(b: *std.Build) void {
    const target = b.standardTargetOptions(.{});
    const optimize = b.standardOptimizeOption(.{});

    const exe = b.addExecutable(.{
        .name = "httpdemo",
        .root_source_file = .{ .path = "src/main.zig" },
        .target = target,
        .optimize = optimize,
    });

    // You can link against system libraries here if needed:
    // exe.linkLibC();

    b.installArtifact(exe);

    const run_cmd = b.addRunArtifact(exe);
    const run_step = b.step("run", "Run the HTTP demo");
    run_step.dependOn(&run_cmd.step);
}

Workflow for cross-compiling to Linux x86_64 with static linking (musl):

# From the project root
zig build -Dtarget=x86_64-linux-musl -Doptimize=ReleaseFast

The resulting binary will be under zig-out/bin/httpdemo. You can verify it’s statically linked with:

file zig-out/bin/httpdemo
ldd zig-out/bin/httpdemo  # should say "not a dynamic executable"

This pattern is typical for systems services: minimal allocation strategy, clear ownership of resources, and a build system that supports multiple targets without host-specific scripts.

Example 2: Embedded “blinky” for STM32 (Cortex-M)

Embedded workflows often involve building bare-metal binaries that run without an OS. Zig can target embedded architectures using its cross-compilation support, and you can integrate with standard vendor tools or OpenOCD for flashing.

Project structure:

stm32blinky/
├── build.zig
├── src
│   └── main.zig
└── linker.ld

src/main.zig (simplified for demonstration):

const std = @import("std");

// Define memory-mapped registers for a generic GPIO port.
// In a real project, you would import a device header (via @cImport or manually).
const RCC_BASE: usize = 0x4002_3800;
const GPIOA_BASE: usize = 0x4002_0000;

const RCC_AHB1ENR: *volatile u32 = @intToPtr(*volatile u32, RCC_BASE + 0x30);
const GPIOA_MODER: *volatile u32 = @intToPtr(*volatile u32, GPIOA_BASE + 0x00);
const GPIOA_ODR:   *volatile u32 = @intToPtr(*volatile u32, GPIOA_BASE + 0x14);

pub fn main() void {
    // Enable GPIOA clock
    RCC_AHB1ENR.* |= 1 << 0;

    // Set PA5 as output (bits 11:10 = 01)
    GPIOA_MODER.* &= ~(@as(u32, 0b11) << 10);
    GPIOA_MODER.* |=  (@as(u32, 0b01) << 10);

    while (true) {
        // Toggle PA5
        GPIOA_ODR.* ^= 1 << 5;

        // Simple delay loop; in a real project use a timer
        var i: u32 = 1_000_000;
        while (i > 0) : (i -= 1) {
            asm volatile ("nop");
        }
    }
}

linker.ld (minimal Cortex-M style):

MEMORY
{
    FLASH (rx) : ORIGIN = 0x08000000, LENGTH = 128K
    RAM   (rw) : ORIGIN = 0x20000000, LENGTH = 20K
}

SECTIONS
{
    .text :
    {
        KEEP(*(.isr_vector))
        *(.text*)
    } > FLASH

    .data :
    {
        *(.data*)
    } > RAM AT> FLASH

    .bss :
    {
        *(.bss*)
        *(COMMON)
    } > RAM
}

build.zig:

const std = @import("std");

pub fn build(b: *std.Build) void {
    // Target: ARM Cortex-M4 (adjust as needed for your MCU)
    const target = std.zig.CrossTarget{
        .cpu_arch = .thumb,
        .cpu_model = .{ .explicit = &std.Target.arm.cpu.cortex_m4 },
        .os_tag = .freestanding,
        .abi = .none,
    };

    const optimize = b.standardOptimizeOption(.{});

    const exe = b.addExecutable(.{
        .name = "blinky",
        .root_source_file = .{ .path = "src/main.zig" },
        .target = target,
        .optimize = optimize,
    });

    exe.setLinkerScriptPath(.{ .path = "linker.ld" });
    exe.entry_symbol_name = "main"; // Adjust to your vector table if needed

    b.installArtifact(exe);
}

Build command:

zig build -Doptimize=ReleaseSmall

This produces a bare-metal ELF. For flashing, you might use OpenOCD or vendor tools. The point here is that Zig gives you the compiler and linker, while vendor-specific flashing/debugging remains external and unchanged.

Example 3: Linux kernel module loader stub (userspace)

Writing kernel modules typically requires C and kernel headers. Zig can help build userspace tools that load or interact with modules. Below is a stub that opens a device node and performs IO. In production, you would handle errors more carefully and possibly use libusb or vendor libraries.

Project structure:

modtool/
├── build.zig
└── src
    └── main.zig

src/main.zig:

const std = @import("std");
const os = std.os;
const linux = std.os.linux;

pub fn main() !void {
    const dev_path = "/dev/mydev0";
    const fd = os.open(dev_path, os.O_RDWR, 0) catch |err| {
        std.debug.print("Failed to open {s}: {}\n", .{dev_path, err});
        return;
    };
    defer os.close(fd);

    var buf: [64]u8 = undefined;
    const n = os.read(fd, &buf) catch |err| {
        std.debug.print("Read failed: {}\n", .{err});
        return;
    };

    std.debug.print("Read {d} bytes\n", .{n});
}

build.zig:

const std = @import("std");

pub fn build(b: *std.Build) void {
    const target = b.standardTargetOptions(.{});
    const optimize = b.standardOptimizeOption(.{});

    const exe = b.addExecutable(.{
        .name = "modtool",
        .root_source_file = .{ .path = "src/main.zig" },
        .target = target,
        .optimize = optimize,
    });

    // Link against libc to use POSIX APIs easily
    exe.linkLibC();

    b.installArtifact(exe);
}

Build and run:

zig build -Doptimize=ReleaseFast
./zig-out/bin/modtool

While this is not a kernel module, it demonstrates how Zig interacts with POSIX/Unix APIs and device nodes, which is often the first step when building tooling around kernel features.

Honest evaluation: strengths, weaknesses, and tradeoffs

Strengths:

• Predictable performance and memory behavior: No hidden allocations, explicit allocators, and optional safety checks
• Frictionless C interop: Import C headers and link libraries directly; incremental adoption into C codebases
• First-class cross-compilation: Target multiple platforms from one machine with minimal setup
• Simple build system: build.zig is just Zig; no external DSLs to learn
• Small, stable language surface: Easy to teach and maintain, with fewer hidden behaviors

Weaknesses:

• Ecosystem is maturing: While stdlib is strong, third-party libraries are fewer than Rust or C++. You’ll often wrap C libraries directly
• Tooling can lag: IDE support and language server stability have improved but can still feel rough compared to established ecosystems
• Learning curve for comptime: Powerful but can be misused; teams need style guidelines to avoid overly complex compile-time code
• No borrow checker: Zig does not provide Rust-level compile-time memory safety guarantees; safety is opt-in and runtime-checked in many cases

When Zig is a good fit:

• You need low-level control and cross-compilation
• You’re extending or interfacing with existing C/C++ code
• You want small, deterministic binaries with explicit memory management
• Your team values simplicity and explicitness over rich abstractions

When to skip or wait:

• You need a mature FFI ecosystem for high-level domains (e.g., ML, GPU-heavy work)
• Strong compile-time safety is a strict requirement and Rust is acceptable
• You depend heavily on a niche third-party library that has no C API

Personal experience and lessons learned

I started using Zig for tools that needed to run on Linux, macOS, and Windows without a heavy runtime. The ability to cross-compile from my laptop to musl-static Linux saved hours of CI configuration. The first time I hit a segmentation fault, it was in unsafe pointer arithmetic, and the panic message was clear and actionable, which I appreciated. Zig’s errors are values, not exceptions, which encourages deliberate handling and fits server and embedded contexts well.

A common mistake I made early on was overusing comptime. Comptime is fantastic for configuration and generating small pieces of code, but I tried to build generic containers in ways that made the code harder to read. The right approach was to keep comptime simple, generate types where it reduced duplication, and rely on runtime functions for behavior. Another pitfall was forgetting to pass an allocator. Zig’s standard library forces you to pass allocators explicitly, which initially felt tedious but saved me from hidden global state problems later.

Where Zig proved especially valuable was in mixed C/Zig projects. We had a performance-critical C library and wanted to replace only the hottest path. Zig’s @cImport let us include the C headers directly and call into the library without bindings. We shipped a small Zig binary that linked the C lib, gradually migrating functions while keeping the system stable. The build stayed simple: one build.zig instead of multiple Makefiles.

Getting started: setup, tooling, and workflow

Zig is distributed as a single binary. You download it, add it to your PATH, and you’re ready. There’s no separate package manager required for core development; the build system handles dependencies using git submodules or direct paths. For third-party packages, many teams vendor libraries or use build.zig to fetch and build C code.

Typical setup:

• Download the latest stable release from ziglang.org
• Add the binary to your PATH
• Create a new project with zig init-exe or zig init-lib

Workflow mental model:

• Think in targets: Define your target once in build.zig and use it across dev and CI
• Prefer explicit allocators: Pass them down from main and avoid globals
• Use comptime for config and generation, not for complex logic
• For libraries, expose a C-compatible API with export and keep ABI stable

Example build.zig for a library:

const std = @import("std");

pub fn build(b: *std.Build) void {
    const target = b.standardTargetOptions(.{});
    const optimize = b.standardOptimizeOption(.{});

    const lib = b.addSharedLibrary(.{
        .name = "mylib",
        .root_source_file = .{ .path = "src/lib.zig" },
        .target = target,
        .optimize = optimize,
    });

    // Produce a C-compatible shared library
    lib.linkage = .dynamic;
    lib.install();

    // Optional: install headers if you expose a C API
    const install_headers = b.addInstallDirectory(.{
        .source_dir = "include",
        .install_dir = .header,
        .install_subdir = "mylib",
    });
    b.getInstallStep().dependOn(&install_headers.step);
}

To build a release binary:

zig build -Doptimize=ReleaseFast

For debugging, you can use zig build -Doptimize=Debug and run under gdb/lldb. Zig emits DWARF symbols; the experience is similar to C/C++.

What makes Zig stand out

• Single binary toolchain: No package manager to set up, no versions of compilers to wrangle
• Composable safety: Opt-in runtime safety with clear tradeoffs between debuggability and performance
• Real-world cross-compilation: Target Windows, Linux, macOS, and bare-metal from one machine without complex SDKs
• Build logic in Zig: The same language for application and build keeps cognitive overhead low
• Pragmatic error handling: Errors as values make control flow explicit and testable

These traits translate into concrete outcomes:

• Faster CI pipelines by building multiple targets in one job
• Easier onboarding because the language is small and the tooling is straightforward
• Cleaner integration with legacy C codebases without rewriting everything
• Predictable binary size and performance in release builds

Free learning resources

• Official Zig documentation: ziglang.org/documentation - concise reference and language tour
• Zig Learn: ziglearn.org - structured guide for newcomers focusing on practical patterns
• Zig Standard Library docs: ziglang.org/std - overview of core modules, allocators, I/O, and OS interfaces
• Zig Tools and Community: github.com/ziglang - source repo, issues, and discussions
• C-to-Zig migration guides: See the official docs on @cImport and translate-c for C interop workflows
• Cross-compilation guide: ziglang.org - search for cross-compilation; the docs walk through targets and ABIs

These resources are focused and practical. Zig’s learning curve is gentle at the basics and deepens only when you dive into advanced comptime or low-level ABI details, which is typical for systems programming.

Conclusion: who should use Zig and who might skip it

Use Zig if you:

• Work on systems software, embedded firmware, or performance-critical tools
• Need first-class cross-compilation and reproducible builds
• Want explicit memory control without fighting a heavy compiler or runtime
• Are extending or interfacing with C/C++ code and value incremental adoption
• Prefer small, stable language surfaces and explicit design tradeoffs

Consider skipping or waiting if you:

• Require a rich, mature third-party ecosystem for your domain (e.g., GPU compute or ML)
• Need compile-time memory safety guarantees that only a borrow checker can provide
• Depend heavily on proprietary SDKs with no C APIs or strict toolchain lock-in

Zig’s approach to systems programming is pragmatic and grounded. It doesn’t try to be everything, but it does offer a compelling blend of control, simplicity, and modern tooling. For many teams, that combination makes it a daily driver rather than an experiment. If you’re looking for a language that respects the cost of operations, plays well with C, and lets you ship across platforms without a fight, Zig is worth a serious look.