progress on LXD post
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@ -48,10 +48,10 @@ migrate as soon as there's an installable release.
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RAM, it's going to make do with 200 MBs of RAM and the kernel's <abbr
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RAM, it's going to make do with 200 MBs of RAM and the kernel's <abbr
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title="Out Of Memory">OOM</abbr> killer is going to have a fun time 🤠
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title="Out Of Memory">OOM</abbr> killer is going to have a fun time 🤠
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- **Portability:** once set up and configured, VMs and containers can mostly be
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- **Portability:** once set up and configured, VMs and containers can mostly be
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treated as black boxes; as long as the surrounding environment of the new host
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treated as closed boxes; as long as the surrounding environment of the new
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is similar to the previous in terms of communication (proxies, web servers,
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host is similar to the previous in terms of communication (proxies, web
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etc.), they can just be picked up and dropped between various hosts as
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servers, etc.), they can just be picked up and dropped between various hosts
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necessary.
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as necessary.
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- **Density:** applications are usually much lighter than the systems they're
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- **Density:** applications are usually much lighter than the systems they're
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running on, so it makes sense to run many applications on one system. VMs and
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running on, so it makes sense to run many applications on one system. VMs and
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containers facilitate that without sacrificing security.
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containers facilitate that without sacrificing security.
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@ -124,19 +124,43 @@ hk.os.h.k3.os3.app3: Many apps
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## Containers
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## Containers
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As most people know them right now, containers are exclusive to Linux.[^1] This is
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VMs use virtualisation to achieve isolation. Containers use **namespaces** and
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because they use namespaces and cgroups to achieve isolation.
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**cgroups**, technologies pioneered in the Linux kernel. By now, though, there
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are [equivalents for Windows] and possibly other platforms.
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- **[Linux namespaces]** partition kernel resources like process IDs, hostnames,
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[equivalents for Windows]: https://learn.microsoft.com/en-us/virtualization/community/team-blog/2017/20170127-introducing-the-host-compute-service-hcs
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user IDs, directory hierarchies, network access, etc.
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- **[Cgroups]** limit, track, and isolate the hardware resource use of a set of
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**[Linux namespaces]** partition kernel resources like process IDs, hostnames,
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processes
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user IDs, directory hierarchies, network access, etc. This prevents one
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collection of processes from seeing or gaining access to data regarding another
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collection of processes.
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**[Cgroups]** limit, track, and isolate the hardware resource use of a
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collection of processes. If you tell a cgroup that it's only allowed to spawn
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500 child processes and someone executes a fork bomb, the fork bomb will expand
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until it hits that limit. The kernel will prevent it from spawning further
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children and you'll have to resolve the issue the same way you would with VMs:
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delete and re-create it, restore from a good backup, etc. You can also limit CPU
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use, the number of CPU cores it can access, RAM, disk use, and so on.
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[Linux namespaces]: https://en.wikipedia.org/wiki/Linux_namespaces
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[Linux namespaces]: https://en.wikipedia.org/wiki/Linux_namespaces
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[Cgroups]: https://en.wikipedia.org/wiki/Cgroups
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[Cgroups]: https://en.wikipedia.org/wiki/Cgroups
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### Application containers
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### Application containers
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The most well-known example of application container tech is probably
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[Docker.][docker] The goal here is to run a single application as minimally as
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possible inside each container. In the case of a single, statically-linked Go
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binary, a minimal Docker container might contain nothing more than the binary.
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If it's a Python application, you're more likely to use an [Alpine Linux image]
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and add your Python dependencies on top of that. If a database is required, that
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goes in a separate container. If you've got a web server to handle TLS
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termination and proxy your application, that's a third container. One cohesive
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system might require many Docker containers to function as intended.
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[docker]: https://docker.com/
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[Alpine Linux image]: https://hub.docker.com/_/alpine
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```kroki {type=d2,d2theme=flagship-terrastruct,d2sketch=true}
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```kroki {type=d2,d2theme=flagship-terrastruct,d2sketch=true}
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Host kernel.Container runtime.c1: Container
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Host kernel.Container runtime.c1: Container
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Host kernel.Container runtime.c2: Container
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Host kernel.Container runtime.c2: Container
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@ -149,6 +173,21 @@ Host kernel.Container runtime.c3.Full OS.Many apps
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### System containers
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### System containers
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One of the most well-known examples of system container tech is the subject of
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this post: LXD! Rather than containing a single application or a very small set
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of them, system containers are designed to house entire operating systems, like
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[Debian] or [Rocky Linux,][rocky] along with everything required for your
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application. Using our examples from above, a single statically-linked Go binary
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might run in a full Debian container, just like the Python application might.
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The database and webserver might go in _that same_ container.
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[Debian]: https://www.debian.org/
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[rocky]: https://rockylinux.org/
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You treat each container more like you would a VM, but you get the performance
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benefit of _not_ virtualising everything. Containers are _much_ lighter than any
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virtual machine.
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```kroki {type=d2,d2theme=flagship-terrastruct,d2sketch=true}
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```kroki {type=d2,d2theme=flagship-terrastruct,d2sketch=true}
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hk: Host kernel
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hk: Host kernel
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hk.c1: Container
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hk.c1: Container
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@ -162,28 +201,41 @@ hk.c2.os2.app2: Many apps
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hk.c3.os3.app3: Many apps
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hk.c3.os3.app3: Many apps
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```
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```
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## When to use VMs
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## When to use which
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- Virtualising esoteric hardware
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{{< adm type="warn" >}}
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- Virtualising non-Linux operating systems (Windows, macOS)
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**Warning:** this is my personal opinion. Please evaluate each technology and
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- Completely isolating processes from one another with a decades-old, battle-tested technique
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determine for yourself whether it's a suitable fit for your environment.
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{{< adm type="note" >}}
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See Drew DeVault's blog post [_In praise of qemu_](https://earl.run/rmBs) for a great use of VMs
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{{< /adm >}}
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{{< /adm >}}
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### When you use application containers
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As far as I'm aware, VMs are your only option when you want to work with
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esoteric hardware or hardware you don't physically have on-hand. It's also your
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only option when you want to work with foreign operating systems: running Linux
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on Windows, Windows on Linux, or OpenBSD on a Mac all require virtualisation.
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Another reason to stick with VMs is for compliance purposes. Containers are
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still very new and some regulatory bodies require virtualisation because it's a
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decades-old and battle-tested isolation technique.
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{{< adm type="note" >}}
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See Drew DeVault's blog post [_In praise of qemu_][qemu] for a great use of VMs
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[qemu]: https://drewdevault.com/2022/09/02/2022-09-02-In-praise-of-qemu.html
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{{< /adm >}}
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Application containers are particularly popular for [microservices] and
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[reproducible builds,][repb] though I personally think [NixOS] is a better fit
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for the latter. App containers are also your only option if you want to use
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cloud platforms with extreme scaling capabilities like Google Cloud's App Engine
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standard environment or AWS's Fargate.
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[microservices]: https://en.wikipedia.org/wiki/Microservices
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[repb]: https://en.wikipedia.org/wiki/Reproducible_builds
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[NixOS]: https://nixos.org/
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- Microservices
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- Extremely reproducible builds
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- (NixOS.org would likely be a better fit though)
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- Dead-set on using cloud platforms with extreme scaling capabilities (AWS, GCP, etc.)
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- When the app you want to run is _only_ distributed as a Docker container and
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- When the app you want to run is _only_ distributed as a Docker container and
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the maintainers adamantly refuse to support any other deployment method
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the maintainers adamantly refuse to support any other deployment method
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- (Docker does run in LXD 😉)
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- (Docker does run in LXD 😉)
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- System containers
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### System containers
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- Anything not listed above 👍
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- Anything not listed above 👍
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## Crash course to LXD
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## Crash course to LXD
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