karpenter-provider-aws
keda
karpenter-provider-aws | keda | |
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47 | 91 | |
5,902 | 7,791 | |
3.1% | 1.8% | |
9.9 | 9.5 | |
3 days ago | 5 days ago | |
Go | Go | |
Apache License 2.0 | Apache License 2.0 |
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karpenter-provider-aws
- Karpenter
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Stress testing Karpenter with EKS and Qovery
If you’re not familiar with Karpenter — watch my quick intro. But in a nutshell, Karpenter is a better node autoscaler for Kubernetes (say goodbye to wasted compute resources). It is open-source and built by the AWS team. Qovery is an Internal Developer Platform I’m a co-founder) that we’ll use to spin up our EKS cluster with Karpenter.
- Tortoise: Shell-Shockingly-Good Kubernetes Autoscaling
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Five tools to add to your K8s cluster
Karpenter
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Architecting for Resilience: Crafting Opinionated EKS Clusters with Karpenter & Cilium Cluster Mesh — Part 1
Here are a few reference links about the previous services and tools: What is Amazon EKS? Cluster Mesh Karpenter
- Scaling with Karpenter and Empty Pod(A.k.a Overprovisioning)
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Reducing Cloud Costs on Kubernetes Dev Envs
Autoscaling over EKS can be accomplished using either the cluster-autoscaler project or Karpenter. If you want to use Spot instances, consider using Karpenter, as it has better integrations with AWS for optimizing spot pricing and availability, minimizing interruptions, and falling back to on-demand nodes if no spot instances are available.
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Help required
Kubernetes has its own learning curve, but when tools like Karpenter exist it's kinda hard to beat for "auto-scaled compute" that is vendor agnostic. We leverage Karpenter for burst in our vSphere environment as well as our EC2 environment. Karpenter is invoking roughly the same Terraform code in both cases, just using different modules for the particular virtualization. Say we want to go to Azure and GCP -- we add an Azure and GCP module to the same Terraform codebase, and not much else needs to change from the "scale up / scale down" perspective.
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Workload Operator. What do you think?
Also https://github.com/aws/karpenter/issues/331
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Running Airflow task intensive Dags on Fargate.
Why don't you stick to the KubernetesPodOperator though? I fail to see a benefit in using the ECS operator considering you're already running Airflow in EKS. You can look into something like karpenter to manage your nodes.
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.
What are some alternatives?
autoscaler - Autoscaling components for Kubernetes
k8s-prometheus-adapter - An implementation of the custom.metrics.k8s.io API using Prometheus
bedrock - Automation for Production Kubernetes Clusters with a GitOps Workflow
argo - Workflow Engine for Kubernetes
karpenterwebsite
istio - Connect, secure, control, and observe services.
dapr - Dapr is a portable, event-driven, runtime for building distributed applications across cloud and edge.
helm - The Kubernetes Package Manager
camel-k - Apache Camel K is a lightweight integration platform, born on Kubernetes, with serverless superpowers
http-add-on - Add-on for KEDA to scale HTTP workloads
karpenterREADME.md
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.