/quill

Asynchronous Low Latency C++ Logging Library

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Quill

Asynchronous Low Latency C++ Logging Library

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🧭 Table of Contents

✨ Introduction

Quill is a high-performance asynchronous logging library. It is particularly suited for performance-critical applications where every microsecond counts.

  • Performance-Focused: Quill consistently outperforms many popular logging libraries.
  • Feature-Rich: Packed with advanced features to meet diverse logging needs.
  • Battle-Tested: Proven in demanding production environments.
  • Extensive Documentation: Comprehensive guides and examples available.
  • Community-Driven: Open to contributions, feedback, and feature requests.

Try it on Compiler Explorer

⏩ Quick Start

Getting started is easy and straightforward. Follow these steps to integrate the library into your project:

Installation

You can install Quill using the package manager of your choice:

Package Manager Installation Command
vcpkg vcpkg install quill
Conan conan install quill
Homebrew brew install quill
Meson WrapDB meson wrap install quill
Conda conda install -c conda-forge quill
Bzlmod bazel_dep(name = "quill", version = "x.y.z")
xmake xrepo install quill
nix nix-shell -p quill-log

Setup

Once installed, you can start using Quill with the following code:

#include "quill/Backend.h"
#include "quill/Frontend.h"
#include "quill/LogMacros.h"
#include "quill/Logger.h"
#include "quill/sinks/ConsoleSink.h"
#include <string_view>

int main()
{
  quill::Backend::start();

  quill::Logger* logger = quill::Frontend::create_or_get_logger(
    "root", quill::Frontend::create_or_get_sink<quill::ConsoleSink>("sink_id_1"));

  LOG_INFO(logger, "Hello from {}!", std::string_view{"Quill"});
}

🎯 Features

  • High-Performance: Ultra-low latency performance. View Benchmarks
  • Asynchronous Processing: Background thread handles formatting and I/O, keeping your main thread responsive.
  • Minimal Header Includes:
    • Frontend: Only Logger.h and LogMacros.h needed for logging. Lightweight with minimal dependencies.
    • Backend: Single .cpp file inclusion. No backend code injection into other translation units.
  • Compile-Time Optimization: Eliminate specific log levels at compile time.
  • Custom Formatters: Define your own log output patterns. See Formatters.
  • Timestamp-Ordered Logs: Simplify debugging of multithreaded applications with chronologically ordered logs.
  • Flexible Timestamps: Support for rdtsc, chrono, or custom clocks - ideal for simulations and more.
  • Backtrace Logging: Store messages in a ring buffer for on-demand display. See Backtrace Logging
  • Multiple Output Sinks: Console (with color), files (with rotation), JSON, ability to create custom sinks and more.
  • Log Filtering: Process only relevant messages. See Filters.
  • JSON Logging: Structured log output. See JSON Logging
  • Configurable Queue Modes: bounded/unbounded and blocking/dropping options with monitoring on dropped messages, queue reallocations, and blocked hot threads.
  • Crash Handling: Built-in signal handler for log preservation during crashes.
  • Huge Pages Support (Linux): Leverage huge pages on the hot path for optimized performance.
  • Wide Character Support (Windows): Compatible with ASCII-encoded wide strings and STL containers consisting of wide strings.
  • Exception-Free Option: Configurable builds with or without exception handling.
  • Clean Codebase: Maintained to high standards, warning-free even at strict levels.
  • Type-Safe API: Built on {fmt} library.

πŸš€ Performance

System Configuration

  • OS: Linux RHEL 9.4

  • CPU: Intel Core i5-12600 (12th Gen) @ 4.8 GHz

  • Compiler: GCC 13.1

  • Benchmark-Tuned System: The system is specifically tuned for benchmarking.

  • Command Line Parameters:

    $ cat /proc/cmdline
    BOOT_IMAGE=(hd0,gpt2)/vmlinuz-5.14.0-427.13.1.el9_4.x86_64 root=/dev/mapper/rhel-root ro crashkernel=1G-4G:192M,4G-64G:256M,64G-:512M resume=/dev/mapper/rhel-swap rd.lvm.lv=rhel/root rd.lvm.lv=rhel/swap rhgb quiet nohz=on nohz_full=1-5 rcu_nocbs=1-5 isolcpus=1-5 mitigations=off transparent_hugepage=never intel_pstate=disable nosoftlockup irqaffinity=0 processor.max_cstate=1 nosoftirqd sched_tick_offload=0 spec_store_bypass_disable=off spectre_v2=off iommu=pt

You can find the benchmark code on the logger_benchmarks repository.

Latency

The results presented in the tables below are measured in nanoseconds (ns).

The tables are sorted by the 95th percentile

Logging Numbers

LOG_INFO(logger, "Logging int: {}, int: {}, double: {}", i, j, d).

1 Thread Logging
Library 50th 75th 90th 95th 99th 99.9th
Quill Bounded Dropping Queue 7 8 8 9 9 11
fmtlog 9 9 10 10 12 13
Quill Unbounded Queue 10 10 10 10 12 14
PlatformLab NanoLog 13 14 16 17 19 25
MS BinLog 21 21 22 22 56 93
XTR 7 7 29 30 33 53
Reckless 26 28 31 32 35 49
BqLog 29 29 30 49 56 71
Iyengar NanoLog 83 96 117 125 152 197
spdlog 143 147 152 158 165 177
g3log 1161 1259 1329 1419 1602 1827

numbers_1_thread_logging.webp

4 Threads Logging Simultaneously
Library 50th 75th 90th 95th 99th 99.9th
fmtlog 8 9 9 10 11 13
Quill Bounded Dropping Queue 8 9 10 10 12 14
XTR 7 8 9 11 31 38
Quill Unbounded Queue 10 11 11 12 13 15
PlatformLab NanoLog 15 17 20 23 27 32
MS BinLog 21 22 22 23 62 100
Reckless 19 23 26 28 34 55
BqLog 31 33 34 55 61 73
Iyengar NanoLog 58 90 123 131 168 242
spdlog 210 243 288 313 382 694
g3log 1271 1337 1396 1437 1614 1899

numbers_4_thread_logging.webp

Logging Large Strings

Logging std::string over 35 characters to prevent the short string optimization.

LOG_INFO(logger, "Logging int: {}, int: {}, string: {}", i, j, large_string).

1 Thread Logging
Library 50th 75th 90th 95th 99th 99.9th
Quill Bounded Dropping Queue 11 13 13 14 15 16
fmtlog 11 12 13 14 15 17
Quill Unbounded Queue 14 15 16 17 18 19
MS BinLog 22 23 24 25 61 100
PlatformLab NanoLog 15 17 21 27 33 39
XTR 8 9 29 31 35 54
BqLog 29 30 31 51 60 71
Reckless 91 107 115 118 124 135
Iyengar NanoLog 86 97 119 128 159 268
spdlog 120 124 128 132 141 151
g3log 881 956 1018 1089 1264 1494

large_strings_1_thread_logging.webp

4 Threads Logging Simultaneously
Library 50th 75th 90th 95th 99th 99.9th
XTR 9 11 13 14 32 40
fmtlog 11 12 13 14 16 19
Quill Bounded Dropping Queue 13 14 15 16 17 19
Quill Unbounded Queue 15 16 17 18 19 21
MS BinLog 23 25 27 28 65 105
PlatformLab NanoLog 16 20 32 38 44 51
BqLog 32 33 35 56 64 76
Reckless 79 94 104 107 114 132
Iyengar NanoLog 85 93 125 133 168 237
spdlog 178 218 261 281 381 651
g3log 992 1055 1121 1178 1360 1600

large_strings_4_thread_logging.webp

Logging Complex Types

Logging std::vector<std::string> containing 16 large strings, each ranging from 50 to 60 characters.

Note: some of the previous loggers do not support passing a std::vector as an argument.

LOG_INFO(logger, "Logging int: {}, int: {}, vector: {}", i, j, v).

1 Thread Logging
Library 50th 75th 90th 95th 99th 99.9th
Quill Bounded Dropping Queue 48 50 53 55 58 62
Quill Unbounded Queue 54 56 57 58 61 66
MS BinLog 68 69 72 74 79 281
XTR 284 294 340 346 356 575
fmtlog 711 730 754 770 804 834
spdlog 6191 6261 6330 6386 6633 7320

vector_1_thread_logging.webp

4 Threads Logging Simultaneously
Library 50th 75th 90th 95th 99th 99.9th
Quill Bounded Dropping Queue 50 52 54 56 60 82
MS BinLog 70 72 75 79 88 286
Quill Unbounded Queue 97 107 116 122 135 148
XTR 512 711 761 791 865 945
fmtlog 780 804 823 835 860 896
spdlog 6469 6549 6641 6735 7631 9430

vector_4_thread_logging.webp

The benchmark methodology involves logging 20 messages in a loop, calculating and storing the average latency for those 20 messages, then waiting around ~2 milliseconds, and repeating this process for a specified number of iterations.

In the Quill Bounded Dropping benchmarks, the dropping queue size is set to 262,144 bytes, which is double the default size of 131,072 bytes.

Throughput

Throughput is measured by calculating the maximum number of log messages the backend logging thread can write to a log file per second.

The tests were run on the same system used for the latency benchmarks.

Although Quill’s primary focus is not on maximizing throughput, it efficiently manages log messages across multiple threads. Benchmarking throughput of asynchronous logging libraries presents certain challenges. Some libraries may drop log messages, leading to smaller-than-expected log files, while others only provide asynchronous flushing, making it difficult to verify when the backend thread has fully processed all messages.

For comparison, we benchmark against other asynchronous logging libraries that offer guaranteed logging with a flush-and-wait mechanism.

Note that MS BinLog writes log data to a binary file, which requires offline formatting with an additional programβ€”this makes it an unfair comparison, but it is included for reference.

Similarly, BqLog (binary log) uses the compressed binary log appender, and its log files are not human-readable unless processed offline. However, it is included for reference. The other version of BqLog is using a text appender and produces human-readable log files.

In the same way, Platformlab Nanolog also outputs binary logs and is expected to deliver high throughput. However, for reasons unexplained, the benchmark runs significantly slower (10x longer) than the other libraries, so it is excluded from the table.

Logging 4 million times the message "Iteration: {} int: {} double: {}"

Library million msg/second elapsed time
MS BinLog (binary log) 63.80 62 ms
BqLog (binary log) 15.92 251 ms
Quill 5.70 701 ms
BqLog 4.93 811 ms
spdlog 3.54 1128 ms
fmtlog 2.90 1378 ms
Reckless 2.72 1471 ms
XTR 2.61 1534 ms

throughput_chart.webp

Compilation Time

Compile times are measured using clang 15 and for Release build.

Below, you can find the additional headers that the library will include when you need to log, following the recommended_usage example

quill_v5_1_compiler_profile.speedscope.png

There is also a compile-time benchmark measuring the compilation time of 2000 auto-generated log statements with various arguments. You can find it here. It takes approximately 30 seconds to compile.

quill_v5_1_compiler_bench.speedscope.png

Verdict

Quill excels in hot path latency benchmarks and supports high throughput, offering a rich set of features that outshines other logging libraries.

The human-readable log files facilitate easier debugging and analysis. While initially larger, they compress efficiently, with the size difference between human-readable and binary logs becoming minimal once zipped.

For example, for the same amount of messages:

ms_binlog_backend_total_time.blog (binary log): 177 MB
ms_binlog_backend_total_time.zip (zipped binary log): 35 MB
quill_backend_total_time.log (human-readable log): 448 MB
quill_backend_total_time.zip (zipped human-readable log): 47 MB

If Quill were not available, MS BinLog would be a strong alternative. It delivers great latency on the hot path and generates smaller binary log files. However, the binary logs necessitate offline processing with additional tools, which can be less convenient.

🧩 Usage

#include "quill/Backend.h"
#include "quill/Frontend.h"
#include "quill/LogMacros.h"
#include "quill/Logger.h"
#include "quill/sinks/ConsoleSink.h"
#include "quill/std/Array.h"

#include <string>
#include <utility>

int main()
{
  // Backend  
  quill::BackendOptions backend_options;
  quill::Backend::start(backend_options);

  // Frontend
  auto console_sink = quill::Frontend::create_or_get_sink<quill::ConsoleSink>("sink_id_1");
  quill::Logger* logger = quill::Frontend::create_or_get_logger("root", std::move(console_sink));

  // Change the LogLevel to print everything
  logger->set_log_level(quill::LogLevel::TraceL3);

  // A log message with number 123
  int a = 123;
  std::string l = "log";
  LOG_INFO(logger, "A {} message with number {}", l, a);

  // libfmt formatting language is supported 3.14e+00
  double pi = 3.141592653589793;
  LOG_INFO(logger, "libfmt formatting language is supported {:.2e}", pi);

  // Logging STD types is supported [1, 2, 3]
  std::array<int, 3> arr = {1, 2, 3};
  LOG_INFO(logger, "Logging STD types is supported {}", arr);

  // Logging STD types is supported [arr: [1, 2, 3]]
  LOGV_INFO(logger, "Logging STD types is supported", arr);

  // A message with two variables [a: 123, b: 3.17]
  double b = 3.17;
  LOGV_INFO(logger, "A message with two variables", a, b);

  for (uint32_t i = 0; i < 10; ++i)
  {
    // Will only log the message once per second
    LOG_INFO_LIMIT(std::chrono::seconds{1}, logger, "A {} message with number {}", l, a);
    LOGV_INFO_LIMIT(std::chrono::seconds{1}, logger, "A message with two variables", a, b);
  }

  LOG_TRACE_L3(logger, "Support for floats {:03.2f}", 1.23456);
  LOG_TRACE_L2(logger, "Positional arguments are {1} {0} ", "too", "supported");
  LOG_TRACE_L1(logger, "{:>30}", std::string_view {"right aligned"});
  LOG_DEBUG(logger, "Debugging foo {}", 1234);
  LOG_INFO(logger, "Welcome to Quill!");
  LOG_WARNING(logger, "A warning message.");
  LOG_ERROR(logger, "An error message. error code {}", 123);
  LOG_CRITICAL(logger, "A critical error.");
}

Output

example_output.png

External CMake

Building and Installing Quill

To get started with Quill, clone the repository and install it using CMake:

git clone http://github.com/odygrd/quill.git
mkdir cmake_build
cd cmake_build
cmake ..
make install
  • Custom Installation: Specify a custom directory with -DCMAKE_INSTALL_PREFIX=/path/to/install/dir.
  • Build Examples: Include examples with -DQUILL_BUILD_EXAMPLES=ON.

Next, add Quill to your project using find_package():

find_package(quill REQUIRED)
target_link_libraries(your_target PUBLIC quill::quill)

Sample Directory Structure

Organize your project directory like this:

my_project/
β”œβ”€β”€ CMakeLists.txt
β”œβ”€β”€ main.cpp

Sample CMakeLists.txt

Here’s a sample CMakeLists.txt to get you started:

# If Quill is in a non-standard directory, specify its path.
set(CMAKE_PREFIX_PATH /path/to/quill)

# Find and link the Quill library.
find_package(quill REQUIRED)
add_executable(example main.cpp)
target_link_libraries(example PUBLIC quill::quill)

Embedded CMake

For a more integrated approach, embed Quill directly into your project:

Sample Directory Structure

my_project/
β”œβ”€β”€ quill/            # Quill repo folder
β”œβ”€β”€ CMakeLists.txt
β”œβ”€β”€ main.cpp

Sample CMakeLists.txt

Use this CMakeLists.txt to include Quill directly:

cmake_minimum_required(VERSION 3.1.0)
project(my_project)

set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)

add_subdirectory(quill)
add_executable(my_project main.cpp)
target_link_libraries(my_project PUBLIC quill::quill)

Android NDK

Building Quill for Android? Add this flag during configuration:

-DQUILL_NO_THREAD_NAME_SUPPORT:BOOL=ON

Meson

Using WrapDB

Easily integrate Quill with Meson’s wrapdb:

meson wrap install quill

Manual Integration

Copy the repository contents to your subprojects directory and add the following to your meson.build:

quill = subproject('quill')
quill_dep = quill.get_variable('quill_dep')
my_build_target = executable('name', 'main.cpp', dependencies : [quill_dep], install : true)

Bazel

Using Blzmod

Quill is available on BLZMOD for easy integration.

Manual Integration

For manual setup, add Quill to your BUILD.bazel file like this:

cc_binary(name = "app", srcs = ["main.cpp"], deps = ["//quill_path:quill"])

πŸ“ Design

Frontend (caller-thread)

When invoking a LOG_ macro:

  1. Creates a static constexpr metadata object to store Metadata such as the format string and source location.

  2. Pushes the data SPSC lock-free queue. For each log message, the following variables are pushed

Variable Description
timestamp Current timestamp
Metadata* Pointer to metadata information
Logger* Pointer to the logger instance
DecodeFunc A pointer to a templated function containing all the log message argument types, used for decoding the message
Args... A serialized binary copy of each log message argument that was passed to the LOG_ macro

Backend

Consumes each message from the SPSC queue, retrieves all the necessary information and then formats the message. Subsequently, forwards the log message to all Sinks associated with the Logger.

design.jpg

🚨 Caveats

Quill may not work well with fork() since it spawns a background thread and fork() doesn't work well with multithreading.

If your application uses fork() and you want to log in the child processes as well, you should call quill::start() after the fork() call. Additionally, you should ensure that you write to different files in the parent and child processes to avoid conflicts.

For example :

#include "quill/Backend.h"
#include "quill/Frontend.h"
#include "quill/LogMacros.h"
#include "quill/Logger.h"
#include "quill/sinks/FileSink.h"

int main()
{
  // DO NOT CALL THIS BEFORE FORK
  // quill::Backend::start();

  if (fork() == 0)
  {
    quill::Backend::start();
        
    // Get or create a handler to the file - Write to a different file
    auto file_sink = quill::Frontend::create_or_get_sink<quill::FileSink>(
      "child.log");
    
    quill::Logger* logger = quill::Frontend::create_or_get_logger("root", std::move(file_sink));

    QUILL_LOG_INFO(logger, "Hello from Child {}", 123);
  }
  else
  {
    quill::Backend::start();
          
    // Get or create a handler to the file - Write to a different file
    auto file_sink = quill::Frontend::create_or_get_sink<quill::FileSink>(
      "parent.log");
    
    quill::Logger* logger = quill::Frontend::create_or_get_logger("root", std::move(file_sink));
    
    QUILL_LOG_INFO(logger, "Hello from Parent {}", 123);
  }
}

πŸ“ License

Quill is licensed under the MIT License

Quill depends on third party libraries with separate copyright notices and license terms. Your use of the source code for these subcomponents is subject to the terms and conditions of the following licenses.