Common Ruby Pitfalls in Production and How to Avoid Them

Ruby is expressive, flexible, and highly productive. However, the same flexibility that makes development enjoyable can also introduce subtle problems in production systems. Many issues do not appear during early development but become visible under real load, long runtimes, or team collaboration.

In this article, we explore common Ruby pitfalls in production and practical ways to avoid them.

1. Memory Growth That Goes Unnoticed

One of the most frequent production issues in Ruby systems is gradual memory growth. Applications may run smoothly at first, but over time memory usage increases.

Common causes include:

• Large objects stored in global variables

• Unreleased references in long-lived processes

• Caching without size limits

• Symbol creation from dynamic input

How to avoid it:

• Monitor memory usage regularly

• Use memory profiling tools during development

• Avoid converting untrusted input directly into symbols

• Review long-lived background workers carefully

Understanding how Ruby’s garbage collector works is essential. Not every memory increase is a leak, but ignoring growth patterns can lead to instability.

2. Excessive Object Allocation

Ruby makes it easy to create objects, but frequent allocations can affect performance under load.

Typical examples:

• Creating temporary arrays in loops

• String concatenation inside iterations

• Unnecessary object wrapping

In high-traffic systems, small inefficiencies accumulate.

How to avoid it:

• Benchmark critical sections

• Reuse objects where reasonable

• Prefer lazy enumerators for large collections

• Profile allocation counts when optimizing

Performance improvements often come from reducing object churn rather than rewriting entire modules.

3. Overusing Monkey Patching

Monkey patching allows developers to modify existing classes, including core Ruby classes. While powerful, it can introduce unpredictable behavior, especially in large teams.

Risks include:

• Breaking third-party libraries

• Unexpected method overrides

• Hard-to-trace bugs

How to avoid it:

• Prefer modules and composition

• Use refinements for scoped changes

• Avoid altering core classes globally unless necessary

Clear boundaries between custom behavior and core functionality improve maintainability.

4. Ignoring Thread Safety

Ruby’s Global VM Lock (GVL) prevents certain parallel execution scenarios, but it does not automatically make code thread-safe.

Common mistakes:

• Sharing mutable objects between threads

• Modifying shared collections without synchronization

• Assuming code is safe because it runs under GVL

How to avoid it:

• Minimize shared mutable state

• Use thread-safe data structures

• Understand differences between threads, processes, and fibers

Concurrency issues are often intermittent and difficult to reproduce, so prevention is critical.

5. Inefficient Database Usage

In web applications, performance issues often come from database interaction rather than Ruby itself.

Frequent problems:

• N+1 queries

• Loading entire datasets into memory

• Missing indexes

• Excessive eager loading

How to avoid it:

• Analyze query logs

• Use database-level monitoring

• Load only required fields

• Review slow queries regularly

Optimizing database access typically provides more benefit than micro-optimizing Ruby code.

6. Large Classes and “God Objects”

As projects grow, it becomes tempting to centralize logic into single service classes. Over time, these classes become difficult to understand and test.

Symptoms include:

• Files exceeding hundreds or thousands of lines

• Mixed responsibilities

• Tight coupling between components

How to avoid it:

• Apply single responsibility principles

• Extract smaller service objects

• Organize code into clear domains

• Separate infrastructure from business logic

Clean structure reduces long-term maintenance cost.

7. Poor Error Handling

Ruby exceptions are powerful, but poorly structured error handling can hide real issues.

Common mistakes:

• Rescuing broad exceptions

• Silently ignoring errors

• Mixing business logic with rescue blocks

How to avoid it:

• Rescue specific exception classes

• Log errors with context

• Separate recovery logic from core functionality

Clear error boundaries improve observability and system reliability.

8. Neglecting Observability

Production systems require visibility. Without structured logging and metrics, diagnosing problems becomes guesswork.

Typical signs of weak observability:

• Logs without context

• No request correlation

• No memory or CPU tracking

How to avoid it:

• Use structured logging

• Introduce request IDs

• Track application-level metrics

• Monitor background job performance

Observability should be built into the architecture, not added after incidents occur.

9. Uncontrolled Dependency Growth

Adding gems is easy, but unmanaged dependencies increase risk.

Potential issues:

• Conflicting versions

• Abandoned libraries

• Deep dependency chains

How to avoid it:

• Audit dependencies periodically

• Prefer smaller, focused libraries

• Review maintenance activity before adoption

A smaller dependency tree often results in more predictable upgrades.

10. Skipping Profiling Until It’s Too Late

Many teams optimize only after performance degrades. However, profiling during development prevents expensive refactoring later.

Helpful tools include:

• rbspy

• ruby-prof

• stackprof

• memory profiling libraries

Profiling early helps identify bottlenecks before they affect users.

Final Thoughts

Most Ruby production issues are not caused by the language itself, but by architectural decisions, overlooked memory patterns, or lack of observability. Ruby offers flexibility, but that flexibility requires thoughtful structure.

Understanding memory behavior, concurrency, dependency management, and error handling transforms Ruby from a scripting tool into a stable production environment.

Production readiness is less about advanced tricks and more about disciplined engineering.