Resque v Sidekiq for Ruby Background Jobs Processing

Background job processing is integral to modern software architecture. Background jobs allow resource-intensive tasks to be handled asynchronously, improving your application’s responsiveness and efficiency. 

You can use background processing for tasks such as sending emails, data processing, and batch jobs. If you were to run these synchronously, they could significantly degrade the user experience and system performance. Thus, most frameworks have libraries for running background jobs. Python has Celery and RQ, Java has Quartz and Spring Batch, Node.js offers Bull and Agenda, PHP is equipped with Gearman and Laravel Queue, while Ruby on Rails boasts Resque and Sidekiq.

Here, we’re thinking about those final two, Sidekiq and Resque, and how Ruby software architects can compare the two options. By evaluating various aspects such as performance, ease of use, reliability, and benchmarking, we want to enable Ruby architects and developers to make informed decisions based on their specific requirements, ensuring they select the most appropriate tool for their Rails background job processing needs. 

What Are Sidekiq and Resque for Rails?

Sidekiq, developed by Mike Perham in 2012, has emerged as a powerful Rails background job processing tool for Ruby applications. It gained popularity due to its efficient handling of multiple jobs concurrently, leveraging the power of multithreading. This is primarily facilitated by using Ruby threads, making Sidekiq a go-to choice for high-throughput environments.

The key features of Sidekiq are:

– Concurrency: Utilizing threads instead of processes, Sidekiq can perform multiple jobs simultaneously, enhancing throughput.

– Redis Dependency: Sidekiq relies on Redis, a high-performance in-memory data structure store, for managing job queues, which contributes to its speed and efficiency.

– Middleware Support: It offers a customizable middleware chain, allowing developers to plug in additional functionality or logic around job execution.

– Dashboard: An intuitive web interface for monitoring and managing jobs, a boon for debugging, and operational visibility.

The architecture of Sidekiq for Rails is straightforward. Background jobs are pushed into queues in Redis, from where Sidekiq workers pull and process them. The multi-threaded nature of Sidekiq allows it to handle many jobs with minimal process overhead, making it resource-efficient. Additionally, its reliable queue system ensures that background jobs are not lost in a failure.

Resque, created by GitHub, is another widely-adopted tool for background job processing in Ruby applications. It is known for its simplicity and reliability. Resque uses Redis as its backing store and processes background jobs sequentially using processes, which aligns well with the fork-unfriendly nature of some Ruby libraries.

Key features of Resque include:

– Process-based Work Model: Resque relies on creating new processes for each Rails background job, isolating them, and avoiding issues related to thread safety.

– Plugins: Resque supports a variety of plugins that extend its functionality, such as Resque-scheduler for scheduling jobs.

– Resilience: The process-based model provides a robust setup where the failure of one job does not impact others.

– Introspection: It offers a comprehensive view of queues and workers through its web interface, aiding in effective monitoring and management.

Resque’s architecture is centered around a master-worker model. Background jobs are enqueued in Redis, and workers, which are separate processes, pick up these jobs for execution. Each Rails background job is processed in isolation, mitigating the risk of memory leaks and ensuring better fault isolation.

Both Sidekiq and Github’s Resque stand out in their respective approaches to background job processing. Sidekiq’s multi-threaded model offers high throughput and efficiency, which is particularly suitable for I/O-bound jobs. Resque, with its process-based model, provides a more traditional, robust solution, especially beneficial in CPU-bound tasks and scenarios where thread safety is a concern. Understanding these nuances is critical to selecting the right tool for your architectural needs.

Using Sidekiq and Resque for Background Jobs

The ease of using both Sidekiq and Github’s Resque is a fundamental reason why these two background libraries have become so widely used. Let’s integrate both into a simple Rails app.

First, we just need to add them to our Gemfile:

gem 'sidekiq'
gem 'resque'

For Sidekiq, we can use the Rails generate command to generate a worker class for Sidekiq:

rails generate sidekiq:worker ImageProcessor

Sidekiq is straightforward to set up and integrate, especially within the Ruby on Rails ecosystem. Its reliance on threads rather than processes simplifies the architectural complexity, making it more accessible to developers familiar with multi-threaded environments.

This worker class, ImageProcessor, includes logic for processing background jobs. The file will contain a basic template for a Sidekiq worker class:

class ImageProcessorWorker
  include Sidekiq::Worker

  def perform(*args)
    # Do something
  end
end

The real power of Sidekiq lies in its customizability. Its middleware chain allows developers to inject custom logic into the job lifecycle, enabling high control over job processing. This is particularly useful for complex applications requiring tailored job handling. Additionally, Sidekiq’s support for different queue priorities and batched jobs provides flexibility for varied workload management.

Resque doesn’t have a generator, so we must manually create the core Class. Resque is still straightforward to set up, and its process-based model is easy to understand and implement, even for developers who might not be familiar with concurrency and threading. We can put our Class in app/jobs/resque_image_processor_job.rb:

class ResqueImageProcessorJob
 @queue = :image_processing_queue

 def self.perform(*args)
# Do something
    end
end

We need to create a ResqueImageProcessorJob class containing the logic that Resque will execute as a background job. Then, we use @queue = :image_processing_queue to specify the queue name that this job will be placed in. Resque uses this to organize and manage different types of background jobs. All instances of ResqueImageProcessorJob will be enqueued in the image_processing_queue. Finally, the self.perform method is what Resque calls to complete the job.

While Resque is less flexible than Sidekiq regarding in-built customization options, it supports a wide range of plugins that can extend its functionality. This includes additions for job scheduling, retry mechanisms, and queue prioritization. However, the process-based architecture may limit the scope of customization compared to a threaded environment like Sidekiq.

As you might have guessed, we will use Sidekiq and Resque to perform background image processing. We’ll use ImageMagick for this, so let’s add that Gem:

gem 'mini_magick'

The code within each worker is the same. We’ll resize each image, change it to black and white, and save it as a PNG. We’ll also time this process for benchmarking. First, Sidekiq:

require 'mini_magick'
require 'csv'

class ImageProcessorJob
 include Sidekiq::Worker

 def perform(image_path)
   start_time = Time.now

   image = MiniMagick::Image.open(image_path)
   image.resize "100x100"
   image.colorspace "Gray"
   image.format "png"

   # Create the sidekiq directory if it doesn't exist
   Dir.mkdir("sidekiq") unless Dir.exist?("sidekiq")
   processed_file_path = "sidekiq/processed_#{File.basename(image_path)}"
   image.write processed_file_path

   end_time = Time.now
   processing_time = end_time - start_time

   puts "Processed #{image_path} with Sidekiq in #{processing_time} seconds"

   # Append the result to a CSV file
   CSV.open("sidekiq_processing_times.csv", "ab") do |csv|
     csv << [image_path, processed_file_path, processing_time]
   end
 end
end

Then, Resque:

require 'mini_magick'
require 'csv'

class ResqueImageProcessorJob
 @queue = :image_processing_queue

 def self.perform(image_path)
   start_time = Time.now

   image = MiniMagick::Image.open(image_path)
   image.resize "100x100"
   image.colorspace "Gray"
   image.format "png"

   # Save the processed image in the resque directory
   Dir.mkdir("resque") unless Dir.exist?("resque")
   processed_file_path = "resque/processed_#{File.basename(image_path)}"
   image.write processed_file_path

   end_time = Time.now
   processing_time = end_time - start_time

   puts "Processed #{image_path} with Resque in #{processing_time} seconds"

   # Append the result to a CSV file
   CSV.open("resque_processing_times.csv", "ab") do |csv|
     csv << [image_path, processed_file_path, processing_time]
   end
 end
end

For both, you’ll need Redis running. You can download Redis from their site and then start a Redis server using:

redis-server

With Redis running, you then also need to start both background workers. Sidekiq is started using:

bundle exec sidekiq

Resque is started using:

QUEUE=image_processing_queue bundle exec rake resque:work

Here, QUEUE=image_processing_queue sets an environment variable specifying the queue name from which the Resque worker should pull and execute jobs. This worker continuously monitors the selected queue and processes any jobs it finds there, allowing for asynchronous task execution in the background.

Here is the Rake we’re using:

namespace :benchmark do
 task :process_images => :environment do
   image_files = Dir.glob("images/*")

   # Benchmark for Sidekiq
   puts "Benchmarking Sidekiq..."
   sidekiq_start_time = Time.now
   image_files.each do |file|
     ImageProcessorJob.perform_async(file)
   end
   sidekiq_end_time = Time.now
   puts "Sidekiq time: #{sidekiq_end_time - sidekiq_start_time} seconds"

   # Benchmark for Resque
   puts "Benchmarking Resque..."
   resque_start_time = Time.now
   image_files.each do |file|
     Resque.enqueue(ResqueImageProcessorJob, file)
   end
   resque_end_time = Time.now
   puts "Resque time: #{resque_end_time - resque_start_time} seconds"
 end
end

The task measures how quickly Sidekiq and Resque can enqueue image processing jobs. The actual processing will happen asynchronously and take longer; we’re measuring that separately. We’ll use 1,000 images from the food101 dataset.

With Sidekiq and Resque running, we can run this Rake using:

rake benchmark:process_images

We should get an output in the terminal like this:

Benchmarking Sidekiq...
Sidekiq time: 0.248602 seconds
Benchmarking Resque...
Resque time: 0.136393 seconds

This tells us that Sidekiq took slightly longer to enqueue the 1,000 images than Resque. We can then look at our CSV’s individual image processing timings to see how each library performed. Here’s our data as a boxplot:

The median processing time for Resque was quicker (0.07 seconds) compared to Sidekiq (0.1 seconds). There are also more outliers at the top of the range for Sidekiq.

This isn’t a definitive benchmarking but should give you a starting point for benchmarking Sidekiq and Resque yourself for your jobs.

Understanding more about Sidekiq and Resque with Scout APM

You can add manual timing and other checks into your code as above to understand Sidekiq and Resque more. But you can also use application performance monitoring. Scout APM has built-in support for monitoring both Sidekiq and Resque (as well as other background job services). Just sign up for Scout APM, add the Scout APM gem to your Gemfile, and install:

gem 'scout_apm'

Then add a configuration file under config/scout_apm.yml, which should look like this:

# This configuration file is used for Scout APM.
# Environment variables can also be used to configure Scout. See our help docs at https://scoutapm.com/docs/ruby/configuration#environment-variables for more information.
common: &defaults
 # key: Your Organization key for Scout APM. Found on the settings screen.
 # - Default: none
 key: <your-key>

 # log_level: Verboseness of logs.
 # - Default: 'info'
 # - Valid Options: debug, info, warn, error
 log_level: debug

 # use_prepend: Use the newer `prepend` instrumentation method. In some cases, gems
 #              that use `alias_method` can conflict with gems that use `prepend`.
 #              To avoid the conflict, change this setting to match the method
 #              that the other gems use.
 #              If you have another APM gem installed, such as DataDog or NewRelic,
 #              you will likely want to set `use_prepend` to true.
 #
 #              See https://scoutapm.com/docs/ruby/configuration#library-instrumentation-method
 #              for more information.
 # - Default: false
 # - Valid Options: true, false
 # use_prepend: true

 # name: Application name in APM Web UI
 # - Default: the application names comes from the Rails or Sinatra class name
 # name:

 # monitor: Enable Scout APM or not
 # - Default: none
 # - Valid Options: true, false
 monitor: true

production:
 <<: *defaults

development:
 <<: *defaults
 monitor: true

test:
 <<: *defaults
 monitor: true

staging:
 <<: *defaults

You can then monitor metrics for your background jobs:

Then, you can drill down into individual jobs:

Learn more about how to set this up and what you can measure in the Scout APM Ruby documentation.

Reliability and Fault Tolerance

In background job processing, reliability and fault tolerance are paramount. Both Sidekiq and Github’s Resque exhibit strong reliability and fault tolerance capabilities, albeit in different ways.

Sidekiq’s approach to error handling is robust. It includes built-in retry mechanisms, automatically retrieving failed jobs with an exponential backoff algorithm. This reduces the likelihood of job loss due to transient issues. Additionally, Sidekiq provides hooks to capture and log errors, allowing custom error-handling strategies to be implemented seamlessly.

One of the strengths of Sidekiq is its reliable queue system. In the event of a system crash or failure, Sidekiq ensures that the jobs are not lost, as they are persisted in Redis. Sidekiq resumes processing from the saved state upon restart, minimizing the risk of background job loss. Furthermore, using idempotent job patterns is encouraged to avoid duplicity or inconsistency in job processing.

Resque’s error handling is straightforward and effective. It provides a failure backend where failed background jobs are stored, allowing for manual inspection and retries. This can be particularly useful in scenarios requiring detailed error analysis and customized retry logic. The ability to plug in different failure backends adds to its flexibility in error management.

The process-based architecture of Resque naturally isolates job failures, preventing a single failing job from affecting others. Regarding recovery, while Resque does not have an automatic retry mechanism by default, its plugin ecosystem includes options for implementing retries and other fault tolerance features. Jobs in Resque also persist in Redis, aiding recovery after crashes and ensuring that the job queue remains intact.

The choice between the two will depend on your Rails application’s specific error handling and recovery requirements. If automated error recovery and minimal manual intervention are priorities, Sidekiq is the more suitable. On the other hand, if your application requires detailed error analysis and custom recovery processes, Resque’s approach might be more appropriate. Both tools offer the foundational reliability and fault tolerance needed for robust background job processing.

Choosing Between Resque and Sidekiq for Background Jobs

The choice between Sidekiq and Github’s Resque for background job processing can significantly impact your Rails application’s resource use, performance efficiency, and scalability. Sidekiq, known for its efficient use of system resources through multi-threading, is generally more performant, especially under heavy loads. Resque, while simpler and using a process-based model, may consume more memory but is often praised for its simplicity and reliability. 

Ultimately, the decision should align with your Rails application’s specific needs, existing infrastructure, and the team’s familiarity with these tools. Both Resque and Sidekiq offer robust solutions but differ in their approach to managing Ruby background jobs, which should be a key consideration in your selection process. As a software architect, the most important thing is to continually monitor your application’s performance and background job processing to ensure that the chosen solution adapts well to the evolving demands and scales efficiently with your growing user base or data processing needs.