Introduction
When teams choose a backend language for containerized services, memory behavior often becomes a deciding factor. Rust and Go are two popular choices, but many developers notice that they behave very differently once deployed in Docker or Kubernetes.
In simple terms, Rust and Go manage memory with very different philosophies. Rust relies on explicit ownership and allocators optimized for speed, while Go uses a garbage collector designed to automatically manage memory. These differences become very visible inside containers with strict memory limits.
Think of Rust as a warehouse that keeps shelves ready for fast loading, and Go as a warehouse that periodically cleans unused shelves automatically. Both work well—but in containers, the differences matter a lot. This article explains how Rust and Go memory behavior differ in real production environments.
What Developers Usually See in Production
Teams commonly report experiences like:
Rust services show a higher steady RSS than expected
Go services slowly increase memory and then drop
Rust pods get OOMKilled suddenly
Go pods show GC pauses under load
These observations often lead to confusion when comparing the two languages.
Wrong Assumption vs Reality
Wrong assumption: Go always uses less memory than Rust.
Reality: Go often returns memory to the OS more visibly, but Rust can be more memory-efficient under stable workloads.
Understanding the trade-offs avoids wrong architectural decisions.
How Rust Manages Memory in Containers
Rust uses deterministic memory management with no garbage collector.
Key characteristics:
Memory is allocated and freed explicitly
Allocators prefer reuse over returning memory
Memory usage stabilizes after warm-up
Real-world explanation:
“Rust keeps memory ready so future requests are fast, even if that memory is not actively used.”
In containers, this looks like high but stable RSS.
How Go Manages Memory in Containers
Go uses a garbage collector that periodically scans memory and frees unused objects.
Key characteristics:
Memory grows with workload
GC cycles reclaim unused memory
RSS may go up and down over time
Real-world explanation:
“Go cleans the warehouse regularly, returning unused shelves.”
This behavior looks more friendly to Kubernetes metrics.
RSS Behavior: Rust vs Go
Rust RSS Pattern
RSS rises during startup
RSS stabilizes
Rarely decreases
Go RSS Pattern
RSS grows with load
GC cycles reduce RSS
RSS fluctuates
Real Production Story
Rust:
“RSS stayed at 700 MB for days, but the service was fast and stable.”
Go:
“RSS oscillated between 400–650 MB depending on GC activity.”
Both were healthy, just different.
Memory Spikes and OOMKills
Rust
Go
Analogy:
“Rust hits the wall fast. Go slows down before hitting it.”
Latency vs Memory Trade-off
Rust
Go
This trade-off is critical for latency-sensitive systems.
Container Memory Limits Impact
Rust in Tight Limits
Needs headroom
Sensitive to spikes
Requires careful tuning
Go in Tight Limits
Neither language magically solves container memory limits.
When Rust Is a Better Fit
Rust is often better when:
Example:
“High-throughput APIs with strict latency SLAs.”
When Go Is a Better Fit
Go is often better when:
Example:
“Internal services with bursty workloads.”
Common Team Mistakes
Avoid these errors:
Each language needs different tuning strategies.
Simple Mental Checklist
When choosing between Rust and Go, ask:
The answers usually make the choice clear.
Summary
Rust and Go behave very differently in containerized environments because they follow different memory management models. Rust favors predictable performance and memory reuse, resulting in stable but higher RSS. Go uses garbage collection, leading to fluctuating memory usage and occasional pauses. Neither approach is better in all cases. Understanding these differences helps teams choose the right tool, size memory limits correctly, and avoid production surprises when running Rust or Go services in Docker and Kubernetes.