Project
Reverse Dependencies for sidekiq
The projects listed here declare sidekiq as a runtime or development dependency
0.0
auto scaler of sidekiq worker deploymented to aws ecs
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Activity
0.0
Manually enqueue Sidekiq jobs from the web UI.
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Activity
0.0
Status of your sidekiq system - useful for Kubernetes liveness probes
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Activity
0.0
Label sidekiq exception.
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Activity
0.0
relatively simple but more efficient way to manage a large number of sidekiq retries.
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0.0
A simple asynchronous Producer/Consumer event bus extension for Sidekiq
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Activity
0.0
If you don't rely on sidekiq' retry behavior, you handle exceptions on your own and want to keep track of them - this thing is for you.
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Activity
0.0
This gem provides behavior similar to sidekiq's inline mode but respects starting dates for scheduled jobs. This is especially useful for integration testing when asserting that certain things happen within a certain time frame.
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0.0
More efficient scheduled job queue implementation for sidekiq to increase throughput in large installations.
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Activity
0.0
easier way to use ffmpeg in sidekiq
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0.0
Selectively encrypt fields in Sidekiq
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Activity
0.0
Run sidekiq jobs in separate forked subprocesses to prevent memory bloat.
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Activity
0.0
Sidekiq worker wrapper that provides optional timeout and after failure (reentrancy)
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Activity
0.0
Allows to group jobs into a set and follow their progress
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Activity
0.0
Transfer some metadata to sidekiq job, can tag sidekiq logs and add logging job args
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Activity
0.0
Easily monitor your sidekiq queus with Slack or some other notification service.
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0.0
Sidekiq middleware that fire a notification when a flagged worker has ended its job, successful or not.
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Activity
0.0
Tool to scale sidekiq dynos on Heroku
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Activity
0.0
Implement a structured logging approach for sidekiq.
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0.0
SidekiqInsight provides detailed CPU, memory, and wall-time profiling for Sidekiq jobs and Rails requests, automatically detects memory leaks, stores metrics in Redis, and displays everything in a clean, modern dashboard. Ideal for monitoring production workload performance.
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