Modern Linux Systems: gRPC, REST, and Process Communication

In today’s cloud-native landscape, understanding how systems communicate—and how they’re built—is essential for engineers. This post synthesizes key concepts around gRPC vs. REST, Linux process communication, and the role of Rust in the modern Linux kernel, clarifying common misconceptions and highlighting real-world architectures.

gRPC vs. REST: Choosing the Right Protocol

At the heart of microservices lies a fundamental design decision: how should services talk to each other?

Core Differences

REST (Representational State Transfer) is resource-oriented, using HTTP verbs (GET, POST, PUT) over JSON or XML. It’s human-readable, widely supported, and ideal for public APIs and browser clients.

gRPC, by contrast, is action-oriented. Built on HTTP/2 and Protocol Buffers (protobuf), it enables:

Binary serialization (60–80% smaller payloads than JSON)
Native streaming (server, client, and bidirectional)
Strong typing via compile-time code generation
Lower latency and higher throughput

Recent 2026 benchmarks show gRPC delivering 107% higher throughput and 48% lower latency than REST in high-load scenarios [[9]]. Another study found 45% average latency reduction with gRPC in internal service meshes [[10]].

When to Use Which?

Use Case	Recommended
Public APIs, browser clients	✅ REST (or GraphQL)
Internal microservices	✅ gRPC
Real-time telemetry, chat, live updates	✅ gRPC (streaming)
Simple CRUD with broad tooling needs	✅ REST

Many organizations adopt a hybrid model: expose REST externally via an API gateway while using gRPC internally for performance-critical paths.

How Docker and containerd Use gRPC (and What They Don’t)

A frequent point of confusion: Does the docker CLI use gRPC?

No. The Docker client communicates with the dockerd daemon via a RESTful API over a Unix socket (/var/run/docker.sock) [[26], [31]]. This is standard HTTP/JSON—not gRPC.

However, beneath Docker lies containerd—and that’s where gRPC shines.

The containerd gRPC Architecture

containerd is the industry-standard container runtime powering both Docker and Kubernetes. It exposes a full gRPC API over a Unix socket (/run/containerd/containerd.sock) [[17], [19], [25]].

Key services include:

Tasks: Manage container lifecycle (create, start, kill)
Images: Pull, push, and manage container images
Snapshots: Handle layered filesystems

Each running container is managed by a containerd-shim process, which also communicates with containerd via gRPC [[18], [22]]. This design allows containers to survive daemon restarts—a critical reliability feature.

Similarly, BuildKit, Docker’s modern builder, uses gRPC for advanced features like parallel builds, remote caching, and secret injection [[25]].

💡 Takeaway: gRPC is used within the container stack, not by the Docker CLI itself. It’s a deliberate choice for performance and streaming in infrastructure components.

Linux Process Communication: Sockets ≠ gRPC

Linux provides several Inter-Process Communication (IPC) mechanisms:

Unix domain sockets
TCP/UDP sockets
Pipes and FIFOs
Shared memory
Signals

These are kernel-provided primitives—low-level building blocks. gRPC is not one of them.

gRPC is a user-space framework that can run over a Unix socket or TCP connection—but so can REST, Thrift, or a custom binary protocol. The socket is just the transport; the protocol is the language spoken on top.

For example:

sshd uses a custom text-based protocol over sockets
systemd uses D-Bus (not gRPC)
nginx talks HTTP/JSON to upstream services

Only when an application explicitly chooses gRPC (like containerd or Kubernetes’ kubelet) does gRPC appear in the communication flow.

Rust in the Linux Kernel: Safety Over Speed

As of 2026, Rust is now a permanent, non-experimental part of the Linux kernel [[1], [2], [6]]. But this shift isn’t about raw performance—it’s about memory safety.

Why Rust?

Historically, ~70% of kernel vulnerabilities stemmed from memory errors in C code: buffer overflows, use-after-free bugs, null pointer dereferences [[19]]. Rust’s ownership model eliminates these at compile time.

Early data shows up to 75% fewer memory-related bugs in Rust-written drivers compared to equivalent C modules [[1]].

Performance Impact?

Rust compiles to machine code as efficient as C. The “speed” gain is indirect:

Fewer crashes → higher system uptime
Less need for CPU-intensive mitigations (like KASLR)
Cleaner abstractions enable better optimization

Importantly, Rust in the kernel has nothing to do with gRPC. The kernel operates in privileged space; gRPC runs in user space and depends on kernel services (like sockets)—not the other way around [[12]].

🔒 Bottom line: Rust makes the kernel more secure and maintainable, not inherently “faster.” And it doesn’t change how processes communicate—unless those processes are rewritten in Rust and choose gRPC.

The Bigger Picture: A Layered Stack

Modern systems stack these technologies cleanly:

┌───────────────────────┐
│   Applications        │ ← May use gRPC or REST (user space)
├───────────────────────┤
│   Container Runtime   │ ← containerd (gRPC API over Unix socket)
├───────────────────────┤
│   Linux Kernel        │ ← Now includes Rust modules (memory-safe drivers)
└───────────────────────┘

gRPC is a communication choice for applications.
Rust is a language choice for safer systems code.
Sockets are the transport layer provided by the OS.

They coexist—but operate at different layers.

Final Thoughts

Understanding these distinctions empowers you to:

Design efficient service architectures (REST externally, gRPC internally)
Debug container runtimes with confidence
Appreciate why Rust matters for long-term system security
Avoid conflating transport (sockets) with protocol (gRPC)

As cloud-native systems grow more complex, clarity about what runs where becomes invaluable. Whether you’re debugging a slow API, securing a kernel module, or optimizing container startup times—knowing the stack is half the battle.