10 Best Logging Libraries for Golang Developers in 2026

A Golang logging library is a specialized software package used to record application events, errors, and operational data within Go programs. Of all over 50 libraries out there, choosing the right library can significantly impact your application's performance, debugging capabilities, and overall maintainability.

Depending on your project needs and purpose, like building high-throughput microservices, cloud-native applications, or enterprise systems, you need a dedicated one. In this blog, I'll suggest top 10 best Golang logging libraries with comparison based on use cases, complexity, and more to help you find the perfect solution for your Go project.

When evaluating which Golang logging library to use, comparing performance metrics and features side-by-side is essential. Here's a comprehensive comparison of all the Go logging libraries covered in this guide:

slog

slog is the official structured logging package introduced into the Go standard library. It gives Go developers a modern, consistent way to produce structured logs without relying on third-party dependencies.

Before slog, developers had to choose external libraries to get structured logging. Since Go 1.21, structured logging has been built directly into the language. This makes logging more consistent across projects, easier to maintain, and safer for long-term support. Also, slog's handler interface is easy to integrate with third-party libraries like Zap or Zerolog while maintaining a consistent API across your codebase.

Key Features:

• Built into the Go standard library (no external dependencies);
• Structured logging with key-value pairs;
• Multiple output handlers (JSON, text);
• Customizable handlers and log levels;
• Excellent performance for most use cases.

How to implement:

import "log/slog"

func main() {
    logger := slog.New(slog.NewJSONHandler(os.Stdout, nil))
    slog.SetDefault(logger)

    slog.Info("user logged in",
        "user_id", 12345,
        "email", "user@example.com",
        "action", "login",
    )
}

Output:

{"time":"2025-01-05T10:30:00Z","level":"INFO","msg":"user logged in","user_id":12345,"email":"user@example.com","action":"login"}

Best for: New Go projects starting with Go 1.21+, teams wanting to minimize dependencies, and applications where moderate performance is acceptable.

Zap

Developed by Uber, Zap is designed for fast, structured, and leveled logging with performance as its top priority. It's optimized for production environments where logging overhead must be minimal.

Most logging libraries rely on Go's interface{} and reflection to process logs, which is flexible but slow and memory-intensive. Zap avoids this by forcing you to specify the data type (e.g., zap.Int, zap.String) upfront. One of my tips is using Zap's SugaredLogger during development for convenience, then switching to the typed Logger in production for maximum performance.

Zap consistently ranks among the top performers in benchmarks, typically logging with near-zero allocations in its typed API mode. If your application handles thousands of requests per second, this is the library you need to prevent logging from becoming a bottleneck.

Key Features:

• Claims to be 4-10x faster than competing libraries;
• Two APIs: sugared (convenient) and structured (type-safe, fast);
• Minimal memory allocations;
• Built-in sampling to reduce log volume in production;
• Extensive customization options.

How to implement:

import "go.uber.org/zap"

func main() {
    logger, _ := zap.NewProduction()
    defer logger.Sync()

    logger.Info("user action",
        zap.Int("user_id", 12345),
        zap.String("action", "purchase"),
        zap.Float64("amount", 99.99),
    )
}

Best for: High-throughput microservices, latency-sensitive applications, and production systems where every microsecond counts.

>> Read more about building Golang microservices:

• How to Implement Golang NATS? Setup, Code, and Use Cases
• A Complete Guide to Implement Golang gRPC with Example

Zerolog - Best for Zero-Allocation Logging

Zerolog takes the philosophy of minimal allocations to the extreme, making it the fastest structured logging library for Go programs handling extremely high loads. If you want Zap's speed but hate its verbose syntax, Zerolog is a nice alternative for better developer experience.

It offers a cleaner, chainable API that is a joy to read and write. Let's use log.With() to create sub-loggers with persistent fields for request-scoped logging. Choose this library if your services generate large volumes of logs per second, such as event processors, streaming systems, or heavily loaded APIs.

Key Features:

• Zero-allocation JSON logger;
• Chainable API for building log messages;
• Contextual logging support;
• Sampling and hooks;
• Console writer for development;
• Integration with standard library's context package.

How to implement:

import (
    "github.com/rs/zerolog"
    "github.com/rs/zerolog/log"
)

func main() {
    zerolog.TimeFieldFormat = zerolog.TimeFormatUnix

    log.Info().
        Str("user_id", "12345").
        Str("action", "signup").
        Int("age", 25).
        Msg("new user registered")
}

Example with Context:

logger := log.With().
    Str("service", "auth-service").
    Str("version", "1.0.0").
    Logger()

logger.Info().Str("user", "john").Msg("login successful")

Best for: Applications requiring absolute minimum memory overhead, high-frequency logging scenarios, and systems where garbage collection pauses are critical.

Logrus

Logrus is one of the earliest structured logging libraries in the Go ecosystem. It uses locking mechanisms (mutexes) heavily, so it's slower than Zap or Zerolog in high-concurrency situations. Despite being no longer the fastest option available, it remains relevant in 2026 due to its rich feature set, extensive ecosystem, and wide community adoption.

Many existing Go projects still rely on Logrus, and its API is familiar to many developers. Its strength lies not in raw performance, but in flexibility, extensibility, and integrations with external systems. For teams maintaining older services or applications that depend heavily on logging hooks and third-party tooling, Logrus can still be a practical choice.

Note: Logrus is now in "maintenance mode." It is stable and safe, but don't expect new features. It is chosen today primarily for its Hooks, pre-built integrations that let you send log. So, let's leverage Logrus hooks to send critical logs to alerting systems like PagerDuty or Slack while writing all logs to your standard output.

Key Features:

• Rich formatting options (JSON, text, custom);
• Hooks for sending logs to external systems;
• Field-based structured logging;
• Multiple log levels;
• Compatible with standard library logger;
• Extensive third-party integrations.

Popular Hooks Available:

• Elasticsearch hook
• Slack notification hook
• Sentry integration
• Firebase hook
• AWS CloudWatch hook

How to implement:

import "github.com/sirupsen/logrus"

func main() {
    log := logrus.New()
    log.SetFormatter(&logrus.JSONFormatter{})
    log.SetLevel(logrus.InfoLevel)

    log.WithFields(logrus.Fields{
        "user_id": 12345,
        "action":  "checkout",
        "items":   3,
    }).Info("cart checkout completed")
}

Best for: Applications requiring extensive integrations, teams familiar with Ruby's Logrus, and projects needing feature richness rather than raw performance.

Apex/log

Apex Log provides a clean, simple API that's easy to learn and use, so developers who want structured logging without complexity can pick this. Its central design philosophy is separating the "logger" from the "handler," making it easy to swap outputs (e.g., from a pretty terminal output to JSON) without rewriting your application code.

For many applications like internal tools, small services, or early-stage products, developers need clarity and ease of use more than squeezing out the last bit of performance. Personally, I use the CLI handler during development for beautiful, readable output, then switch to JSON handler in production.

Key Features:

• Clean and intuitive APIl
• Multiple handlers (JSON, text, CLI, memory);
• Interface-based design for easy testing;
• Lightweight with minimal dependencies.

How to implement:

import (
    "github.com/apex/log"
    "github.com/apex/log/handlers/json"
)

func main() {
    log.SetHandler(json.New(os.Stdout))

    log.WithFields(log.Fields{
        "user":   "john",
        "action": "login",
    }).Info("user action recorded")
}

Best for: Small to medium projects, developers new to structured logging, and applications where simplicity is prioritized.

Go-kit Log

Go-kit's logging package is designed specifically for microservices and distributed systems, not just a general-purpose logging library. It provides a flexible foundation that integrates seamlessly with the rest of the Go-kit ecosystem.

Go-kit’s logging package treats a logger as a simple functional interface. Instead of using global loggers, it encourages passing the logger into services as a dependency. This makes code easier to test and allows you to wrap logging middleware, such as automatically tracking Prometheus metrics when errors occur.

I often combine Go-kit logger with its tracing and metrics packages for comprehensive observability in your microservices.

Key Features:

• Designed for microservices;
• Works with Go-kit's other components;
• Level-based logging;
• Contextual logging;
• Interface-driven design.

How to implement:

import (
    "github.com/go-kit/log"
    "github.com/go-kit/log/level"
)

func main() {
    logger := log.NewJSONLogger(os.Stdout)
    logger = log.With(logger, "service", "user-service", "ts", log.DefaultTimestamp)

    level.Info(logger).Log("msg", "service started", "port", 8080)
}

Best for: Microservices built with Go-kit, distributed systems requiring consistent logging patterns, and teams using the full Go-kit ecosystem.

>> Explore more: How to Debug Go Applications with Go Tracing?

Phuslu/log

Phuslu/log is an ultra-fast logging library that consistently outperforms even Zerolog in benchmarks while maintaining a simple API. It achieves this through aggressive low-level optimizations, including custom I/O buffering and hand-tuned implementations.

Unlike many performance-focused loggers that trade features for speed, Phuslu/log includes built-in file rotation and a Zerolog-compatible API to optimize performance for high-load systems.

Key Features:

• Fastest Go logger in benchmarks;
• Zero-dependency core;
• Zerolog-compatible API;
• Console and JSON output;
• Built-in file rotation;

How to implement:

import "github.com/phuslu/log"

func main() {
    log.Info().
        Str("app", "myservice").
        Int("port", 8080).
        Msg("server starting")
}

Best for: Extremely performance-critical applications, high-frequency trading systems, and scenarios where every nanosecond matters.

Charmbracelet/log

Created by the Charm team known for Go CLI tools with beautiful terminal UIs, Charmbracelet/log provides colorful, human-readable logging perfect for command-line applications.

Different from most logging libraries like Zap and Zerolog that optimize for machines (JSON output, log aggregation, and production observability), Charm Log focuses on user experience. It uses intelligent coloring, icons, and spacing to make logs scannable and visually appealing. 

Also, it implements the slog.Handler interface, meaning you can use the standard Go slog API but get Charm's beautiful output. For developer tools and command-line apps, this improves usability immediately without requiring custom formatting or extra setup.

Key Features:

• Beautiful, colorful terminal output;
• Minimal and intuitive API;
• Structured logging support;
• Configurable styling;
• Perfect for developer experience.

How to implement:

import "github.com/charmbracelet/log"

func main() {
    log.Info("Starting application", "version", "1.0.0")
    log.Warn("Configuration missing", "file", "config.yaml")
    log.Error("Failed to connect", "host", "localhost", "port", 5432)
}

Best for: CLI applications, development tools, and any Go program where human-readable output in the terminal is important.

Google/logger

Google's logger provides a simple, cross-platform solution that can log to Windows event log, Linux/macOS syslog, and standard io.Writers. No need to write to "Standard Output" (stdout/stderr) and rely on external tools (like Docker or Systemd) to capture logs like other libraries, Google/logger uses a cross-platform abstraction that writes directly to the OS's native logging facility.

This library is suitable for desktop applications or enterprise system agents where you want logs to appear without extra configuration.

Key Features:

• Cross-platform support (Windows, Linux, macOS, FreeBSD);
• System log integration;
• Simple API similar to standard library;
• Verbose logging support.

How to implement:

import "github.com/google/logger"

func main() {
    logger.Init("MyApp", true, false, os.Stdout)
    defer logger.Close()

    logger.Info("Application started")
    logger.Warning("Low memory warning")
    logger.Error("Connection failed")
}

Best for: Cross-platform desktop applications, system utilities, and applications requiring OS-native logging integration.

Gookit/slog

Gookit/slog is an easy-to-use, extensible logging library that supports multiple handlers and formatters out of the box. It allows you to adapt logging behavior through configuration rather than rewriting code.

Not to be confused with Go 1.21's standard log/slog. While the standard library is minimal, gookit/slog has more built-in features. Besides multiple output handlers, custom formatters, most importantly, it has built-in log file rotation and compression, features that usually require third-party plugins in other libraries.

Key Features:

• Multiple built-in handlers;
• Flexible formatter system;
• Log file rotation;
• Console coloring;
• Buffer writing support.

How to implement:

import "github.com/gookit/slog"

func main() {
    slog.Info("Application started")
    slog.WithFields(slog.M{
        "user_id": 123,
        "action":  "purchase",
    }).Info("user action")
}

Best for: Applications needing flexible output configurations, projects requiring built-in log rotation, and developers wanting an easy learning curve.

How to Choose the Right Golang Logging Library for Your Project?

Selecting the perfect Golang logging library depends on your specific project requirements. Consider these critical factors when evaluating your options:

Performance Requirements:

• Ultra-high performance: Phuslu/log or Zerolog
• High performance: Zap
• Moderate performance: slog, Logrus

Dependency Preferences:

• No external dependencies: slog (standard library)
• Minimal dependencies: Zerolog, Zap

Use Case:

• Microservices: Zap, Zerolog, Go-kit log
• CLI tools: Charmbracelet/log
• Enterprise applications: Logrus
• New projects: slog

Team Experience:

• New to Go: slog or Apex/log (simple APIs)
• Experienced teams: Zap or Zerolog (more control)

Best Practices for Golang Logging

Regardless of which library you choose, follow these logging best practices:

1. Use structured logging: Always prefer key-value pairs over string concatenation.
2. Include context: Add request IDs, user IDs, and trace information.
3. Choose appropriate levels: Use DEBUG, INFO, WARN, ERROR consistently.
4. Avoid logging sensitive data: Never log passwords, tokens, or PII.
5. Sample in production: Use sampling to reduce log volume in high-traffic systems.
6. Configure output format: Use JSON for production, text for development.

Conclusion

The Golang logging library landscape in 2026 offers helpful options for every use case. Whether you're searching for the fastest Go logging library or the most feature-rich Golang logging library, there's a solution that fits your needs. 

The key is to evaluate your specific requirements like performance needs, team experience, integration requirements, and dependency preferences before making your choice. With the libraries covered in this guide, you're equipped to implement robust, efficient logging in any Go application.