polar
nydus
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polar
nydus
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Ask HN: Have You Left Kubernetes?
If you're pulling big images you could try kube-fledged (it's the simplest option, a CRD that works like a pre-puller for your images), or if you have a big cluster you can try a p2p distributor, like kraken or dragonfly2.
Also there's that project called Nydus that allows starting up big containers way faster. IIRC, starts the container before pulling the whole image, and begins to pull data as needed from the registry.
https://github.com/senthilrch/kube-fledged
https://github.com/dragonflyoss/Dragonfly2
https://github.com/uber/kraken
https://nydus.dev/
- Increase the speed of NPM install by more than 8 times
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new "EROFS over Fscache" Linux container image architecture for CNCF Dragonfly Nydus
Nydus-fscache user guide: https://github.com/dragonflyoss/image-service/blob/master/docs/nydus-fscache.md
What are some alternatives?
plural - Deploy open source software on Kubernetes in record time. 🚀
docker-volume-hetzner - Docker Volume Plugin for accessing Hetzner Cloud Volumes
k8s-config-connector - GCP Config Connector, a Kubernetes add-on for managing GCP resources
swarmsible - Ansible based Tooling and production grade example Docker Stacks. Updated with new learnings from running Docker Swarm in production
Dragonfly2 - Dragonfly is an open source P2P-based file distribution and image acceleration system. It is hosted by the Cloud Native Computing Foundation (CNCF) as an Incubating Level Project.
terraform-cdk - Define infrastructure resources using programming constructs and provision them using HashiCorp Terraform
external-dns - Configure external DNS servers (AWS Route53, Google CloudDNS and others) for Kubernetes Ingresses and Services
enhancements - Enhancements tracking repo for Kubernetes
cachemachine - Kubernetes image prepuller for the Rubin Science Platform
spire - Bugout knowledgebase module.
kraken - P2P Docker registry capable of distributing TBs of data in seconds
kube-fledged - A kubernetes operator for creating and managing a cache of container images directly on the cluster worker nodes, so application pods start almost instantly