Resque
keda
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Resque | keda | |
---|---|---|
5 | 90 | |
9,383 | 7,624 | |
0.2% | 2.3% | |
4.1 | 9.5 | |
4 months ago | 6 days ago | |
Ruby | Go | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Resque
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Mike Perham of Sidekiq: “If you build something valuable, charge money for it.”
The free version acts exactly like Resque, the previous market leader in Ruby background jobs. If it was good enough reliability for GitHub and Shopify to use for years, it was good enough for Sidekiq OSS too.
Here's Resque literally using `lpop` which is destructive and will lose jobs.
https://github.com/resque/resque/blob/7623b8dfbdd0a07eb04b19...
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Add web scraping data into the database at regular intervals [ruby & ror]
You can use a background job queue like Resque to scrape and process data in the background, and a scheduler like resque-scheduler to schedule jobs to run your scraper periodically.
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How to run a really long task from a Rails web request
So how do we trigger such a long-running process from a Rails request? The first option that comes to mind is a background job run by some of the queuing back-ends such as Sidekiq, Resque or DelayedJob, possibly governed by ActiveJob. While this would surely work, the problem with all these solutions is that they usually have a limited number of workers available on the server and we didn’t want to potentially block other important background tasks for so long.
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Building a dynamic staging platform
Background jobs are another limitation. Since only the Aha! web service runs in a dynamic staging, the host environment's workers would process any Resque jobs that were sent to the shared Redis instance. If your branch hadn't updated any background-able methods, this would be no big deal. But if you were hoping to test changes to these methods, you would be out of luck.
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Autoscaling Redis applications on Kubernetes 🚀🚀
Redis Lists are quite versatile and used as the backbone for implementing scalable architectural patterns such as consumer-producer (based on queues), where producer applications push items into a List, and consumers (also called workers) process those items. Popular projects such as resque, sidekiq, celery etc. use Redis behind the scenes to implement background jobs.
keda
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Tortoise: Shell-Shockingly-Good Kubernetes Autoscaling
Microsoft does a good job with KEDA, providing an open source autoscaling architecture that isn't tied to Azure.
https://keda.sh/ - project website
Most just utilize out of the box macro resources available in HPA.
For more advanced use cases there is keda - https://keda.sh/
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Root Cause Chronicles: Quivering Queue
Thankfully KEDA operator was already part of the cluster, and all Robin had to do was create a ScaledObject manifest targeting the Dispatch ScaleUp event, based on the rabbitmq_global_messages_received_total metric from Prometheus.
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Five tools to add to your K8s cluster
Keda
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Best Kubernetes DevOps Tools: A Comprehensive Guide
KEDA introduces event-driven scaling to Kubernetes workloads. It integrates with Kubernetes Horizontal Pod Autoscalers and can scale pods based on external metrics from services like databases and message queues (Kafka, RabbitMQ, MongoDB).
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Auto-scaling DynamoDB Streams applications on Kubernetes
This is where KEDA comes in.
# update version 2.8.2 if required kubectl apply -f https://github.com/kedacore/keda/releases/download/v2.8.2/keda-2.8.2.yaml
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What is the difference in production for scale to zero usecases - Keda vs Lambda ?
This is traditionally a AWS Lambda usecase - or an OpenFaas kind of usecase. But very recently i discovered https://keda.sh/ and it seems it is specifically meant for this in a kubernetes environment.
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Ingesting Data into OpenSearch using Apache Kafka and Go
If you deploy the application to Amazon EKS, you can also consider using KEDA to auto-scale your consumer application based on the number of messages in the MSK topic.
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Is there a product that can orchestrate running jobs?
Maybe this https://keda.sh/
What are some alternatives?
k8s-prometheus-adapter - An implementation of the custom.metrics.k8s.io API using Prometheus
Sidekiq - Simple, efficient background processing for Ruby
argo - Workflow Engine for Kubernetes
istio - Connect, secure, control, and observe services.
karpenter-provider-aws - Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.
helm - The Kubernetes Package Manager
Shoryuken - A super efficient Amazon SQS thread based message processor for Ruby
http-add-on - Add-on for KEDA to scale HTTP workloads
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
another-autoscaler - Another Autoscaler is a Kubernetes controller that automatically starts, stops, or restarts pods from a deployment at a specified time using a cron expression.
Sneakers - A fast background processing framework for Ruby and RabbitMQ
argo-cd - Declarative Continuous Deployment for Kubernetes