Another user posted the blog where they discuss their speedup techniques: https://tailscale.com/blog/more-throughput/

It’s likely that the kernel version can use similar techniques to surpass the performance of the userspace version that tailscale uses, but no one has put in the work to to make the kernel implementation as sophisticated as the userspace one.

Like helping to find a bug, discussing about how to setup an application for a certain use case or anything like that? Answering questions on Stack overflow is an example but is that the best way?

Generally the best way to help out is to do a thing that’s needed and that you can figure out how to do. Your list includes a bunch of good options, and I’ve been thanked for doing all those things at one point or another. Some common growth paths include:

1. Using the software
2. Encountering bugs, problems, or small opportunities for improvement.
3. Discussing those informally in forums and helping people find workarounds.
4. Identifying some of those issues as common things other things experience as well, so filing bugs for them with clear explanations and links to related forum discussions.
5. Reading source code to better understand bugs.
6. Discussing potential fixes in developer bug threads (or in GitHub or whatever).
7. Submitting small fixes for simple bugs as pull requests.

Another path might be:

1. Using the software and reading forums/docs for help.
2. Answering basic questions on forums, looking to old threads and relevant docs.
3. Learning about common questions.
4. Writing blogs or forum posts about common questions.
5. Submitting improvements to official docs to clarify common areas of confusion.

There are other paths as well, the main thing is to use a thing so you learn about it and then use that knowledge to make it a little easier for the next person. Good luck!

I had a look through the comments on this HN thread the other day and came away more intrigued by https://github.com/openobserve/openobserve than hyperdx. Hyperdx is built on top of clickhouse whereas open observe has it’s own storage engines based on parquet files that can be accessed from local disk, S3, or a few other protocols.

I haven’t tried either option yet… I’m, currently using netdata for metrics and don’t do anything special for logs or tracing, but at tiny self-hosting scale I often find software with it’s own storage engines (often sqlite) to be extra hassle-free. I’m curious to kick the tires on openobserve for that reason.

This is a very strong explanation of what’s going on. And as a follow-up, I believe that ZeroTier present a single Ethernet broadcast domain, and so WoL tricks are more likely to work naturally there than with Wireguard. I haven’t used ZeroTier, and I do use Wireguard via Tailscale/Headscale. I’ve never missed the Ethernet features of ZeroTier and they CAN result in a very chatty wan if you’re not careful. But I think ZT would make this straightforward.

Though as other people note… the simplest/least-disruptive change is probably to expose some scripty thing on the rpi that can be triggered via be triggered over a routed protocol and then have the rpi emit the Ethernet broadcast packets from the physical network.

I don’t think titles directly transfer between companies, and yet the industry allows it. It’s a very useful tool for advancement.

This may be true on some corners of the industry, but at the more competitive end (both in terms of competitive pay, and a competitive pool of candidates)… I believe it’s common to relevel on hire. I’ve seen folks go from director to senior and from senior to junior at my org. The candidates being offered those seemingly big “demotions” often seem to be somewhere between unphased and enthusiastic about the change, presumably because the compensation package we offer at the lower level beats what they were getting with an inflated title and because they know their inflated title is nonsense and they’re frustrated with the other aspects of organizational dysfunction that accompany title inflation at their current company.

What you say is real, and sometimes a promotion in one org can help bridge you into an org that would have been hard to get hired into as a junior, or harder to get promoted in. It’s not without risk though. All things being equal, I’d much rather spend my time working on a strong team and learning a lot and being challenged than to be in a weaker org that’s handing out inflated titles. Getting gud isn’t a guarantee of advancement, but it’s at least as reliable over the long haul as title inflation.

No no, sorry. I mean can I still have all my network traffic go through some VPN service (mine or a providers) while Tailscale is activated?

Tailscale just partnered with Mullvad so this works out of the box for that setup: https://tailscale.com/blog/mullvad-integration/

For others, it’s a “yes on paper” situation. It will probably often not work out of the box, but it seems likely to be possible as an advanced configuration. At the end of the line of possibilities, it would definitely be possible to set up a couple of docker containers as one-armed routers, one with your VPN and one with Tailscale as an exit node. Then they can each have their own networking stack and you can set up your own routes and DNS delegating only the necessary bits to each one. That’s a pretty advanced setup and you may not have the knowhow for it, but it demonstrates what’s possible.

To a first approximation, Tailscale/Headscale don’t route and traffic.

Ah, well damn. Is there a way to achieve this while using Tailscale as well, or is that even recommended?

Is there a way to achieve what? Force tailscale to route all traffic through the DERP servers? I don’t know, and I don’t know why you’d want to. When my laptop is at home on the same network as my file-server, I certainly don’t want tailscale sending filserver traffic out to my Headscale server on the Internet just to download it back to my laptop on the same network it came from. I want NAT traversal to allow my laptop and file-server to negotiate the most efficient network path that works for them… whether that’s within my home lab when I’m there, across the internet when I’m traveling, or routing through the DERP server when no other option works.

OpenVPN or vanilla Wireguard are commonly setup with simple hub-and-spoke routing topologies that send all VPN traffic through “the VPN server”, but this is generally slower path than a direct connection. It might be imperceptibly slower over the Internet, but it will be MUCH slower than the local network unless you do some split-dns shenanigans to special-case the local-network scenario. With Tailscale, it all more or less works the same wherever you are which is a big benefit. Of course excepting if you have a true multigigabit network at home and the encryption overhead slows you down… Wireguard is pretty fast though and not a problematic throughout limiter for the vast majority of cases.

Have a read through https://tailscale.com/blog/how-nat-traversal-works/

You, and many commenters are pretty confused about out tailscale/Headscale work.

1. To a first approximation, Tailscale/Headscale don’t route and traffic. They perform NAT traversal and data flows directly between nodes on the tailnet, without traversing Headscale/Tailscale directly.
2. If NAT traversal fails badly enough, it’s POSSIBLE that bulk traffic can flow through the headscale/tailscale DERP nodes… but that’s an unusual scenario.
3. You probably can’t run Headscale from your home network and have it perform the NAT traversal functions correctly. Of course, I can’t know that for sure because I don’t know anything about your ISP… but home ISPs preventing Headscale from doing it’s NAT traversal job are the norm… one would be pleasantly surprised to find that a home network can do that properly.
4. Are younreally expecting 10gb/s speeds over your encrypted links? I don’t want to say it’s impossible, people do it… but you’d generally only expect to see this on fairly burly servers that are properly configured. Tailscale just in April bragged about hitting 10gb speeds with recent optimizations: https://tailscale.com/blog/more-throughput/ and on home hardware with novice configd I’d generally expect to see roughly more like single gigabit.

I don’t know what’s up on your case, but I would not jump to the conclusion that it’s impossible to use tailscale with any other VPN in any circumstance.

Rather, tailscale and Mullvad will now work easily and out of the box. For other VPNs, you may need to do understand the topology and routing of virtual devices and have the technical ability and system permissions to make deep networking changes.

So I’d expect one can probably find a way for most things to coexist on a Linux server. On a non-rootrr android phone? I’m less confident.

So I have a question, what can I do to prevent that from happening? Apart from hosting everything on my own hardware of course, for now I prefer to use VPS for different reasons.

Others have mentioned that client-caching can act as a read-only stopgap while you restore Vaultwarden.

But otherwise the solution is backup/restore. If you run Vaultwarden in docker or podman container using volumes to hold state… then you know that as long as you can restart Vaultwarden without losing data that you also know exactly what data needs to be backed up and what needs to be done to restore it. Set up a nightly cron job somewhere (your laptop is fine enough if you don’t have somewhere better) to shut down Vaultwarden, rsync it’s volume dirs, and start it up again. If you VPS explodes, copy these directories to a new VPS at the same DNS name and restart Vaultwarden using the same podman or docker-compose setup.

All that said, keeypass+filesync is a great solution as well. The reason I moved to Vaultwarden was so I could share passwords with others in a controlled way. For single-user, I prefer how keypass folders work and keepass generally has better organization features… I’d still be using it for only myself.

And just today with a comment by a world admin! Hopefully they’ll get it sorted soon.

That’s an interesting report but it’s possible to “work” at different latencies. And unless you have specialized audio capture/playback hardware and have done some tuning and testing to determine the lowest stable latency that your system is capable of achieving… “works” for you is likely to mean something very different than it does to someone who does a lot of music production.

It remains an interesting question to some users whether Wayland changes the minimum stable latency relative to X and if so whether it does so for better or worse.

I’d consider asking in a Linux audio or music production community (I’m not aware of any on Lemmy that are big enough to have a likely answer though). If music production is a primary use case and audio latency matters to you, almost no general users are going to be able to comment on the difference between X and Wayland from a latency perspective. There may not be a difference, but there might and you won’t be likely to learn about it outside of an audio-focused discussion.

It may seem kinda stupid to consider that an accomplishment, but I feel quite genuinely proud of myself for actually succeeding at this instead of just throwing in the towel…

Way to go. I’ve been at this a decent while and do some pretty esoteric stuff at work and at home… but this loop of feeling stupid, doing the work, and feeling good about a success has been a constant throughout. I spent a week struggling to port some advanced container setups to podman a month or so ago, same feeling of pride when I got them humming.

It’s not stupid to be proud of an accomplishment even if it’s a fundamental one that’s early in a bigger learning curve. Soak it in, then on to the next high. Good luck.

You connect to Headscale using the tailscale clients, and configuration is exactly the same irrespective of which control server you use… with the exception of having to configure the custom server url with Headscale (which requires navigating some hoops and poor docs for mobile/windows clients).

But to my knowledge there are no client-side configs related to NAT traversal (which is kind of the goal… to work seamlessly everywhere). The configs themselves on the headscale server aren’t so bad either, but the networking concepts involved are extremely advanced, so debugging if anything goes sideways or validating that your server-side NAT traversal setup is working as expected can be a deep dive. With Tailscale, you know any problems are client-side and can focus your attention accordingly… which simplifies initial debugging quite a lot.

… only if you are in the US and get an API key from NCMEC. They are very protective of who gets the keys and require a zoom call as well.

Do you have a source for these statements, because they directly contradict the Cloudflare product announcement at https://blog.cloudflare.com/the-csam-scanning-tool/ which states:

Beginning today, every Cloudflare customer can login to their dashboard and enable access to the CSAM Scanning Tool.

… and shows a screenshot of a config screen with no field for an API key. Some CSAM scanners do have fairly limited access, but Cloudflare’s appears to be broadly available.

Yeah, misread the pricing page. Fixed the post, thanks for the correction.

I use Headscale, but Tailscale is a great service and what I generally recommend to strangers who want to approximate my setup. The tradeoffs are pretty straightforward:

• Tailscale is going to have better uptime than any single-machine Headscale setup, though not better uptime than the single-machine services I use it to access… so not a big deal to me either way.
• Tailscale doesn’t require you to wrestle with certs or the networking setup required to do NAT traversal. And they do it well, you don’t have to wonder whether you’ve screwed something up that’s degrading NAT traversal only in certain conditions. It just works. That said, I’ve been through the wringer already on these topics so Headscale is not painful for me.
• Headscale is self-hosted, for better and worse.
• In the default config (and in any reasonable user-friendly, non professional config), Tailscale can inject a node into your network. They don’t and won’t. They can’t sniff your traffic without adding a node to your tailnet. But they do have the technical capability to join a node to your tailnet without your consent… their policy to not do that protects you… but their technology doesn’t. This isn’t some surveillance power grab though, it’s a risk that’s essential to the service they provide… which is determining what nodes can join your tailnet. IMO, the tailscale security architecture is strong. I’d have no qualms about trusting them with my network.
• Beyond 3 devices users, Tailscale costs money… about $6 US in that geography. It’s a pretty reasonable cost for the service, and proportional in the grand scheme of what most self-hosters spend on their setups annually. IMO, it’s good value and I wouldn’t feel bad paying it.

Tailscale is great, and there’s no compelling reason that should prevent most self-hosters that want it from using it. I use Headscale because I can and I’m comfortable doing so… But they’re both awesome options.

My money is also on IO. Outside of CPU and RAM, it’s the most likely resource to get saturated (especially if using rotational magnetic disks rather than an SSD, magnetic disks are going to be the performance limiter by a lot for many workloads), and also the one that OP said nothing about, suggesting it’s a blind spot for them.

In addition to the excellent command-line approaches suggested above, I recommend installing netdata on the box as it will show you a very comprehensive set of performance metrics without having to learn to collect each one on the CLI. A downside is that it will use RAM proportional to the data retention period, which if you’re swapping hard will be an issue. But even a few hours of data can be very useful and with 16gb of ram I feel like any swapping is likely to be a gross misconfiguration rather than true memory demand… and once that’s sorted dedicating a gig or two to observability will be a good investment.

I use k8s at work and have built a k8s cluster in my homelab… but I did not like it. I tore it down, and currently using podman, and don’t think I would go back to k8s (though I would definitely use docker as an alternative to podman and would probably even recommend it over podman for beginners even though I’ve settled on podman for myself).

1. K8s itself is quite resource-consuming, especially on ram. My homelab is built on old/junk hardware from retired workstations. I don’t want the kubelet itself sucking up half my ram. Things like k3s help with this considerably, but that’s not quite precisely k8s either. If I’m going to start trimming off the parts of k8s I don’t need, I end up going all the way to single-node podman/docker… not the halfway point that is k3s.
2. If you don’t use hostNetworking, the k8s model of traffic routes only with the cluster except for egress is all pure overhead. It’s totally necessary with you have a thousand engineers slinging services around your cluster, but there’s no benefit to this level fo rigor in service management in a homelab. Here again, the networking in podman/docker is more straightforward and maps better to the stuff I want to do in my homelab.
3. Podman accepts a subset of k8s resource-yaml as a docker-compose-like config interface. This lets me use my familiarity with k8s configs iny podman setup.

Overall, the simplicity and lightweight resource consumption of podman/docker are are what I value at home. The extra layers of abstraction and constraints k8s employs are valuable at work, where we have a lot of machines and alot of people that must coordinate effectively… but I don’t have those problems at home and the overhead (compute overhead, conceptual overhead, and config-overhesd) of k8s’ solutions to them is annoying there.