Sidekiq in Practice

1h 4m 45s
English
Paid

Are you using Sidekiq to process your background jobs, but struggling with it as your application scales? Sidekiq can scale to 5,000 jobs per second with just a little effort and knowledge: in Sidekiq in Practice, I'll show you how.

Sidekiq in Practice takes a step-by-step approach towards building a complex, real-world application that runs a massive volume of jobs through Sidekiq.

Contents include:

1. How to understand scaling: how many processes and servers you need, and how to autoscale them efficiently.

2. Idempotency: Increase your scalability by discarding "unique jobs" and instead use basic computer science to make jobs work regardless of the number of times they are enqueued

3. Memory bloat. How to reduce and diagnose memory problems that are causing you to deal with massive server bills.

4. Concurrency settings, thread safety, queue design and structures, database pool sizes, and more.

Here's what you'll receive:

  • An interactive workshop, driven by a command-line experience. (try it now: gem install skp && skp list)
  • 9 hands-on exercises which show you how to put the principles of the course into real practice.
  • 60 minutes of HD video discussing additional topics on scaling Sidekiq.
  • A 100-page reference of the text content from the workshop, available in multiple formats.

Sidekiq Pro and/or Enterprise are not required. The workshop mostly covers features in Sidekiq OSS.

About the Author: Nate Berkopec

Nate Berkopec thumbnail
I make Ruby apps faster - across the entire stack. I'm the proprietor of Speedshop, a Ruby on Rails performance consultancy. I'm a contributor to several open source projects, such as Puma and Ruby on Rails. I appeared on Shark Tank, ABC's primetime entrepreneurship show, when I was nineteen.

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#1: Reducing Redis Load
All Course Lessons (9)
#Lesson TitleDurationAccess
1
Reducing Redis Load Demo
06:27
2
Multi-Server Setups
06:54
3
Amdahl's Law
06:37
4
Jobs are Cheaper
07:03
5
Load Shedding
06:56
6
Scaling Redis... with SQL
07:42
7
Managing SQL Load
07:12
8
Multi-Threading Inside a Job
07:47
9
Memory Profiling
08:07
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