keda
k8s-prometheus-adapter
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keda | k8s-prometheus-adapter | |
---|---|---|
91 | 13 | |
7,729 | 1,824 | |
2.5% | 1.8% | |
9.5 | 6.2 | |
7 days ago | 7 days ago | |
Go | Go | |
Apache License 2.0 | 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.
keda
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Ask HN: What's the right way to scale K8s for GPU workloads?
It seems you want something like KEDA (https://keda.sh)
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Tortoise: Shell-Shockingly-Good Kubernetes Autoscaling
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
- K8s latencies in chained services - Using RL?
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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
# 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
- KEDA
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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.
k8s-prometheus-adapter
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Upgrading Hundreds of Kubernetes Clusters
The last one is mostly an observability stack with Prometheus, Metric server, and Prometheus adapter to have excellent insights into what is happening on the cluster. You can reuse the same stack for autoscaling by repurposing all the data collected for monitoring.
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Helm: Is there a way to access templates of a sibling subchart
I'm deploying kube-prometheus-stack along with prometheus-adapter in my monitoring stack for custom metrics.
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Deploy prometheus-adapter with kube-prometheus-stack monitoring stack?
I would like to see if anyone deployed prometheus-adapter and kube-prometheus-stack together for monitoring?
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Horizontal Pod Autoscale
For us it is saturation of CPU and thread pool. It's implemented by exposing metrics of the thread pool to prometheus and turning that into a custom metric. (see) Looking at scaling based on job queue length next.
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Steps to write own adaptor
If you are using Prometheus or kube-prometheus-stack, you will need https://github.com/kubernetes-sigs/prometheus-adapter We are using it to scale our Pods based on number of messages in RabbitMQ queue. There also a walkthrough on https://github.com/kubernetes-sigs/prometheus-adapter/blob/master/docs/walkthrough.md
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Monitoring Your Spacelift Account via Prometheus
A prometheus-adapter installation.
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Advanced Features of Kubernetes' Horizontal Pod Autoscaler
Prometheus adapter to get custom/external metrics from Prometheus instance into Kubernetes API.
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Pod spread by percentage
I never tested this but you have customized metrics API if the value % is available should work from my point of view Check this here https://github.com/kubernetes-sigs/prometheus-adapter
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Practical Introduction to Kubernetes Autoscaling Tools with Linode Kubernetes Engine
CPU and memory might not be the right metrics for your application to make scaling decisions. In such cases, you can use HPA (or VPA) with custom metrics as an alternative. To use custom metrics for autoscaling, you can use a custom metrics adapter instead of the Kubernetes Metrics Server. Popular custom metrics adapters are the Prometheus adapter and Kubernetes Event-Driven Autoscaler (KEDA).
- How to scale containers that are unrelated to physical traits like CPU or Memory?
What are some alternatives?
argo - Workflow Engine for Kubernetes
metrics-server - Scalable and efficient source of container resource metrics for Kubernetes built-in autoscaling pipelines.
istio - Connect, secure, control, and observe services.
k9s - 🐶 Kubernetes CLI To Manage Your Clusters In Style!
karpenter-provider-aws - Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.
cluster-proportional-autoscaler - Kubernetes Cluster Proportional Autoscaler Container
helm - The Kubernetes Package Manager
spring-auto-scaling-k8
http-add-on - Add-on for KEDA to scale HTTP workloads
prometheus - The Prometheus monitoring system and time series database.
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.
helm-charts - Prometheus community Helm charts