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hyperhq
runv
Go2015–2021
hyperhq / runv · Archived

runv

Hypervisor-based Runtime for OCI

11Distinct people
14Mentions
0Explicit recommenders
828GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Hypervisor-based Runtime for OCI

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year14 dated mentions

Observed mentions: 2015-09-24 10:30:08 UTC to 2021-09-01 01:43:51 UTC.

0123452015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20152016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 5 mentions; 0 submissions, 5 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC101
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC413
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC505
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC202
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC101
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101

What Hacker News says

14 sources
I think this is how I most commonly recognize someone that is familiar with lxc +/- docker and containerization in general. A firm grasp of the fact that they're just beefy processes, isolated wiht namespaces and cgroups is the best, most succint way to describe docker (without even mentioning the benefits), but it also requires that the hearer knows what namespaces and cgroups are. If I had to rank understanding in explanations of docker: 1. "Makes your application really portable"/other explanations that only cover the benefits of docker not how it works 2. "Lightweight VMs" 3. "LXC + some other stuff" 4. "processes + namespaces + cgroups (+/- image management tools, etc)" 100% agreed on the point you made, pretty sure docker+swarm and other orchestration efforts have basically lost the competition. Kubernetes just has the mind share, a
Read the rest
nd even better than that -- it's actually good. Kubernetes also has multiple competing container runtimes all rushing to fit the CRI (Container Runtime Interface). Just some of the stuff out there: * cri-containerd - https://github.com/containerd/cri-containerd * runv (hypervisor based) - https://github.com/hyperhq/runv * clear containers (hypervisor based) - https://github.com/clearcontainers/runtime * kata containers (hypervisor based, collaboration of runv + clear container) - https://katacontainers.io/ * frakti (combination of runv & docker, enabling switching @ runtime) - https://github.com/kubernetes/frakti A bunch of the projects are in their infancy, but the CNCF/kubernetes and the community are doing the right thing investing in lots of them, and letting the good ones bubble to the top. I don't run a production kubernetes cluster but I've found cri-containerd to be really easy to use and haven't had any major problems with it, mostly small configuration things. The last one, frakti, gets me really excited, because it lets you be flexible about which containers run in more protected environments and which don't. Also really exciting is frakti v2 (https://github.com/kubernetes/frakti/tree/containerd-kata), which is kata + containerd.
In A Workshop on Linux Containers: Rebuild Docker from Scratch
But Hyper.sh is still competitive, I think, even though it's super young. They already have a high level AWS Lambda alternative (Hyper Func) that uses containers and is fully language agnostic, and they have reasonable pricing-per-minute figured out. They also have open sourced their tech [1], so for certain companies they probably are compelling. Perhaps they should provide the kind of ease-of-use on top of the stuff they already provide that will cut open a steady market for them, like a Heroku but with this underlying tech and thus more dynamic on scaling and flexible on tech stack. [1] https://github.com/hyperhq/runv is one example
In Azure Container Instances
In my context it's because big data became a thing. Nobody wants to pay the virtualization IO overheads anymore. That said, I've found myself swinging back towards preferring VMs - with docker-like infrastructure made available. The runv project (https://github.com/hyperhq/runv/) is an interesting and functional take on Docker-with-VMs since I spend way too much time wanting to do privileged things in containers.
In Docker in Production: A retort
I like the initial idea very much. As I can see this is a wrapper over QEMU and controlled by QMP [1][2], so they are providing a kernel, initrd and a image. It is also configuring a machine profile (memory, vcpu, bus, devices, etc.). There are also interfaces for libvirt, xen and others virtualization technologies. This also looks similar of what Docker is doing now in Windows with HyperV. My question here is: from where comes the speed improvement in relation with a classical VM approach? [1] https://github.com/hyperhq/runv/blob/master/hypervisor/qemu/... [2] https://github.com/hyperhq/runv/blob/master/hypervisor/qemu/...
In Hyper Is Docker Done the Right Way

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