Hello all! Just curious what y’alls typical setup is when it comes to running multiple stacks which require the same “support” containers.
What I mean is, say you want to run two services that both require a connection to a database, would you run two separate DB containers, one for each service and have them connected only to their respective DB “stacks”? Or do you prefer to run a single centralized DB server/service and have your self hosted stacks all communicate with their own databases inside the server?
I take the latter approach – a single PostgreSQL database service for all other containers to use. That allows me to concentrate memory/CPU to a single service and optimize for that. I’ve found that a single database service uses less total resources (especially memory) than running separate DB stacks for each service.
I’ve found that a single database service uses less total resources (especially memory) than running separate DB stacks for each service.
This should indeed be the expected result. Each DB server will have a set amount of overhead from the runtime before data overhead comes in. Ex (made up numbers):
storage subsystem=256MBconfig subsystem=128MBauth subsystem=280MBapi subsystem=512MBuser tables=xMB
The subsystem resource usage would be incurred by every instance of the DB server. Additionally, you have platform-level overhead, especially if you are running as VMs or containers as that requires additional resources to coordinate with the kernel, etc.
It’s very much like micro-kernels vs monoliths. On the surface a lean micro-kernel seems like it should be more performant since less is happening during kernel time but, the significant increase in operations to perform basic tasks. For example, if storage access was in userspace, an application would need to call back to the kernel to request communication, which would need to call up to the storage driver, then back… and it becomes a death of a thousand cuts. In a monolithic kernel, the application just tells the kernel that it wants to access storage, what mode, and provide either the input or a buffer receive data.
One big DB will be a single point of failure. You will not benefit from much more speed, the only thing which is “easier” is backup.
I use different DBs for different stacks. If one hangs up or messed up completly, it won’t affect others
My recommendation, if practical, is a single, potentially containerized DB server that is backed by storage that provides high availability and redundancy. This is supposing that you are using the same sort of DB (ex SQL, NoSQL, etc) and that you are targeting a smallish number of services that are on-premise.
My reasoning here is that you can treat the DB server effectively as a storage API service and run it via some orchestration service like K8S. This lets you offload your DB stability and data integrity to the FS and/or other low-level stuff that is simple to configure once and only dirty about when hardware fails. This in turn greatly reduces DB server configuration and deployment as well as treat them like livestock, not pets.
Now, if you are using a public cloud provider, my view changes slightly. Generally, I’d suggest offloading the DB to a provided service that is compatible with a FOSS alternative so that you can avoid vendor lock-in. This means that you get the HA, etc without having to worry about maintenance and configuration overhead. Just be aware of cost modeling - it’s easy to run up large bills.
Separate DB containers for each service. Easier, more secure, and less messy. The overhead impact is trivial.
- If a service supports sqlite, I often will use that option. It provides everything a self-hoster needs from a DB with basically no operational overhead.
- If I do need a proper RDBMS (because the software I’m using doesn’t support sqlite), I’m going to use…
- A single Postgres container.
- Configured with multiple logical “databases” (the container for schemas and tables), one DB for each app connecting.
I do this because I’m always memory constrained and the rdbms is generally the most memory-hungry part of any software stack. By sharing one db-process across all the apps that need it I get the most out of my db cache memory, etc. And by using multiple logical db’s, I get good separation between my apps, and they’re straightforward to migrate to a truly isolated physical DB if needed… but that’s never been needed.
That makes a lot of sense and where I’m leaning towards as well
While my homeserver still has plenty of resources to spare, I see a lot of them going towards multiple DB containers. It’s nice for “segregating” the containers, but backups are also a pain, gotta plan backups/restores for multiple DBs
Same story with an s3 (well, minio) instance running. Seems like it would make more sense to centralize DB and file operations and having different services talk to them. Then if I ever needed to move them into separate servers, it wouldn’t be as big a move.
Thanks!
