HORIZONTAL SCALING K8S PODS USING KEDA AUTOSCALER
DOI:
https://doi.org/10.24867/28BE46StanicKeywords:
Kubernetes, KEDA, SQS, horizontal scalingAbstract
The paper presents the implementation of a configuration management software for K8s pods and autoscaling based on number of messages in SQS. It is described how to use KEDA autoscaler with K8s container orchestrator and Python library for cloud and K8s resource management.
References
[1] IBM Data Science - Best Practices https://ibm.github.io/data-science-best-practices/scaling.html
[2] Kubernetes https://kubernetes.io/
[3] KEDA https://keda.sh/
[4] SQS https://aws.amazon.com/sqs/
[5] Minikube https://minikube.sigs.k8s.io/docs/start/
[6] ElasticMQ https://github.com/softwaremill/elasticmq
[7] Helm https://helm.sh/
[2] Kubernetes https://kubernetes.io/
[3] KEDA https://keda.sh/
[4] SQS https://aws.amazon.com/sqs/
[5] Minikube https://minikube.sigs.k8s.io/docs/start/
[6] ElasticMQ https://github.com/softwaremill/elasticmq
[7] Helm https://helm.sh/
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Published
2024-09-06
Issue
Section
Electrotechnical and Computer Engineering
