k3d-nfs-dynamic-volumes
karpenter-provider-aws
k3d-nfs-dynamic-volumes | karpenter-provider-aws | |
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1 | 46 | |
0 | 5,877 | |
- | 2.7% | |
10.0 | 9.9 | |
over 3 years ago | 6 days ago | |
Go | ||
- | Apache License 2.0 |
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k3d-nfs-dynamic-volumes
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How to Deploy and Scale Strapi on a Kubernetes Cluster 2/2
Now, for the purposes of this article, in case you don't have an NFS server available, we will use a simple NFS Server Provisioner, which we'll use only for example purposes. As mentioned before, using a managed solution from a cloud provider or a properly configured HA NFS server in your infrastructure is highly recommended. We'll install not the most up-to-date solution, but it should work for example purposes. We will follow the Quickstart found in the repo, mixed with this repo which does some small tweaks to make it work with K3d, which is summarized in the following commands run from the helm folder:
karpenter-provider-aws
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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.
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How to automate gitlab runner autoscaling on ec2 instances
We use the Kubernetes runner and Karpenter.
What are some alternatives?
argo-cd - Declarative Continuous Deployment for Kubernetes
keda - KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes
autoscaler - Autoscaling components for Kubernetes
strapi-k8s-blog-post - All resources for the blog post titled "How to Deploy and Scale Strapi on a Kubernetes Cluster"
bedrock - Automation for Production Kubernetes Clusters with a GitOps Workflow
falco - Cloud Native Runtime Security
karpenterwebsite
rook - Storage Orchestration for Kubernetes
dapr - Dapr is a portable, event-driven, runtime for building distributed applications across cloud and edge.
jaeger - CNCF Jaeger, a Distributed Tracing Platform
camel-k - Apache Camel K is a lightweight integration platform, born on Kubernetes, with serverless superpowers