1,882 karma · joined December 8, 2017
From my experience, the cloud bill on Hetzner can sometimes be as low as 20% of an equivalent AWS bill. However, this cost advantage comes with significant trade-offs.
On Kubernetes with Hetzner, we managed a Ceph cluster using NVMe storage, MariaDB operators, Cilium for networking, and ArgoCD for deploying Helm charts. We had to handle Kubernetes cluster updates ourselves, which included facing a complete cluster failure at one point. We also encountered various bugs in both Kubernetes and Ceph, many of which were documented in GitHub issues and Ceph trackers. The list of tasks to manage and monitor was endless. Depending on the number of workloads and the overall complexity of the environment, maintaining such a setup can quickly become a full-time job for a DevOps team.
In contrast, using AWS or other major cloud providers allows for a more hands-off setup. With managed services, maintenance often requires significantly less effort, reducing the operational burden on your team.
In essence, with AWS, your DevOps workload is reduced by a significant factor, while on Hetzner, your cloud bill is significantly lower.
Determining which option is more cost-effective requires a thorough TCO (Total Cost of Ownership) analysis. While Hetzner may seem cheaper upfront, the additional hours required for DevOps work can offset those savings.
IMDb works mainly by user reviews who rate videos from 1 to 10. But personally, I think any system can be gamed, just like GitHub Stars. When I'm interested in the GitHub Top 250 (as equivalent to IMDb Top 250), I just do a GitHub search with a filter for the language I'm interested in, e.g., Python, and then sort by stars. This works good enough for me.
Wait. I know where you are coming from, but this is simply not true.
Ceph, with which I have much experience, is a very solid and quite bulletproof storage solution that offers S3 protocol and FS. However, maintaining it in the long run is really challenging. You better become a Ceph expert.
SeaweedFS struggles with managing large data groups. It's inspired by an outdated Facebook study (Haystack) and is intended for storing and sharing large images. However, I think it's only average—it has poor documentation, underwhelming performance, and a confusing set of components to install. Its design allows each server process to use one big file for storage, bypassing slow file metadata operations. It offers various access points through gateways.
MinIO has evolved a lot recently, making it hard to evaluate. MinIO relies on many small databases. Currently, it's phasing out some features, like the gateway, and mainly consists of two parts: a command line interface (CLI) and a server. While MinIO's setup is complex, SeaweedFS's setup is much simpler. MinIO also seems to be moving from an open-source model towards a more commercial one, but I have not closely followed this transition.
All of these solutions are not simple enough to be the base for a distributed database application. What we really need would be something like an Ext4 successor, let's call it Ext5, with native distributed storage capabilities in the most dead-simple way. ZFS is another good candidate. ZFS has already solved the problem of how to distribute storage across multiple hard drives within one server very well, but it still lacks a good solution on how to distribute storage across different hard drives on different servers connected via a network.
Yes, I know there is the CAP theorem, so it is really a hard challenge to solve, but I think we can do better in terms of self-hosted solutions.
xterm (389-1)
alacritty (0.13.1-1)
kitty-tuned (0.31.0-1)
zutty (0.14-2)
st (master 95f22c5)
urxvt (9.31-4)
konsole (24.02.0-1)
kitty (0.31.0-1)
wezterm (20230712.072601)
gnome-terminal (3.50.1-1)
xfce4-terminal (1.1.1-2)
terminator (2.1.3-3)
tilix (1.9.6-3)
hyper (v3.4.1)
I only tested for software latency (monitor, keyboard and other hardware latency is not included in Typometer benchmarks). I ran the test on Arch Linux with Xorg + bswpwm without compositor. You can find the full results on by blog https://beuke.org/terminal-latency/.For a company, this should definitely not be something to worry about. However, if I were able to single out individual IPs that are attacking me, then I would simply block them, report them (use the abuse form from the hoster of the attacking IP), and call it a day. This way, you can at least hope that the hoster will do something about it, either by kicking the hacker off its platform or, if it is some kind of service reflection attack, inform the victim to close the security loophole on their server and remove themselves from the botnet. If your attacks originate from a vast amount of different IPs from Russia and China, consider geoblocking.
[root@archlinux ~]# pacman -Qi xz | head -n2
Name : xz
Version : 5.6.1-2
[root@archlinux ~]# pacman -Qi openssh | head -n2
Name : openssh
Version : 9.7p1-1
[root@archlinux ~]# ldd $(which sshd) | grep liblzma
[root@archlinux ~]#
It seems that Arch Linux is not affected.For a project where multiple people are involved, I think it's better to split concerns. Deployment should be handled transparently and reproducible in a CI pipeline that the team members who are allowed to deploy have access to.
I wouldn't count on that. It required a 90-minute video for you to get going with Wordpress. I would say, if you know some basic stuff (e.g., know how to install gem, how to write markdown/html), you can set up Jekyll in under 90 minutes:
gem install jekyll bundler; jekyll new myblog; cd myblog; bundle exec jekyll serve
Now, you have a server up and running. You can start creating a post by creating a markdown file in the _posts folder.
For me personally, it would be faster to learn any easy-to-use static site generator than Wordpress.
Okay, but unless you have cooling with liquid nitrogen you cannot maintain 6.2 GHz for long due to thermals in practice, hence after a short sprint it will fall back to a much lower frequency.