karpenter-provider-aws
rook
karpenter-provider-aws | rook | |
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47 | 51 | |
5,902 | 11,949 | |
3.1% | 0.8% | |
9.9 | 9.9 | |
3 days ago | 6 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.
rook
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Ceph: A Journey to 1 TiB/s
I have some experience with Ceph, both for work, and with homelab-y stuff.
First, bear in mind that Ceph is a distributed storage system - so the idea is that you will have multiple nodes.
For learning, you can definitely virtualise it all on a single box - but you'll have a better time with discrete physical machines.
Also, Ceph does prefer physical access to disks (similar to ZFS).
And you do need decent networking connectivity - I think that's the main thing people think of, when they think of high hardware requirements for Ceph. Ideally 10Gbe at the minimum - although more if you want higher performance - there can be a lot of network traffic, particularly with things like backfill. (25Gbps if you can find that gear cheap for homelab - 50Gbps is a technological dead-end. 100Gbps works well).
But honestly, for a homelab, a cheap mini PC or NUC with 10Gbe will work fine, and you should get acceptable performance, and it'll be good for learning.
You can install Ceph directly on bare-metal, or if you want to do the homelab k8s route, you can use Rook (https://rook.io/).
Hope this helps, and good luck! Let me know if you have any other questions.
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Running stateful workloads on Kubernetes with Rook Ceph
Another option is to leverage a Kubernetes-native distributed storage solution such as Rook Ceph as the storage backend for stateful components running on Kubernetes. This has the benefit of simplifying application configuration while addressing business requirements for data backup and recovery such as the ability to take volume snapshots at a regular interval and perform application-level data recovery in case of a disaster.
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People who run Nextcloud in Docker: Where do you store your data/files? In a Docker volume, or on a remote server/NAS?
This is beyond your question but might help someone else: I switch from docker-compose to kubernetes for my home lab a while ago. The storage solution I've settled on is Rook. It was a bit of up-front work learning how to get it up but now that it's done my storage is automatically managed by Ceph. I can swap out drives and Ceph basically takes care of everything itself.
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Rook/Ceph with VM nodes on research cluster?
The stumbling point I am at is I want to use rook.io(Ceph) as my storage solution for the cluster. The Ceph prerequisites are one of the following:
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Asking for recommendation on remote Kubernetes storage for a small cluster and databases
Have you looked at Rook?
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Want advice on planned evolution: k3os/Longhorn --> Talos/Ceph, plus Consul and Vault
I've briefly run ceph in an external mode, you can actually use a rook deployment to manage it (sort of). Here is the documentation for doing that. For me it didn't pass my testing phase because I need better networking equipment before I can try that.
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ATARI is still alive: Atari Partition of Fear
This article explains the data corruption issue happened in Rook in 2021. The root cause lies in an unexpected place and can also occurs in all Ceph environment. It's interesting that Rook had started to encounter this problem recently even though this problem has existed for a long time. It's due to a series of coincidences. I wrote this article because the word "Atari" used in a non-historical context in 2021.
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How to Deploy and Scale Strapi on a Kubernetes Cluster 2/2
Rook (this is a nice article for Rook NFS)
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Running on-premise k8s with a small team: possible or potential nightmare?
Storage: Favor any distributed storage you know to start with for Persistent Volumes: Ceph maybe via rook.io, Longhorn if you go rancher etc
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My completely automated Homelab featuring Kubernetes
I've dealt with a lot of issues that are very close to just unplugging a node. Unfortunately on node lost, my stateful workloads using rook-ceph block storage won't migrate over to another node automatically due to an issue with rook. Stateless apps (ingress nginx, etc..) not using rook-ceph block failover to another node just fine. I've kind of accepted this for now and I know Longhorn has a feature that makes this work but I find rook-ceph to be more stable for my workloads.
What are some alternatives?
keda - KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes
longhorn - Cloud-Native distributed storage built on and for Kubernetes
autoscaler - Autoscaling components for Kubernetes
ceph-csi - CSI driver for Ceph
bedrock - Automation for Production Kubernetes Clusters with a GitOps Workflow
velero - Backup and migrate Kubernetes applications and their persistent volumes
karpenterwebsite
Nginx Proxy Manager - Docker container for managing Nginx proxy hosts with a simple, powerful interface
dapr - Dapr is a portable, event-driven, runtime for building distributed applications across cloud and edge.
Ceph - Ceph is a distributed object, block, and file storage platform
camel-k - Apache Camel K is a lightweight integration platform, born on Kubernetes, with serverless superpowers
hub-feedback - Feedback and bug reports for the Docker Hub