home-ops VS vector

These are great operational wins. Agreed very much that having autonomic (can fix itself) systems at your back is a massive game changer. De-crustifies the act of running things.

The other win is that there's a substantial cultural base to this way to go. Folks have been doing selfhosting for ages, but everyone has their own boutique setup some their way. A couple tools and techniques could be shared, but mostly everyone took blank slate configs & built their own system up, & added their own monitoring & operational scripts.

https://github.com/onedr0p/home-ops is a set of helm scripts and other tools that is widely widely used, and there's a lot more like it. It's a huge build out, using convention and a common platform to enable portable knowledge & sharing.

Self hosting did not have intellectual scale out at it's back, before Kubernetes came along. Docker and ansible and others have been around, but theres never been remotely the success there has been today in empowering users to setup & run complex services.

We really have clawed out of the server-hugging jungle &started building some villages. It's wonderful to see.

Going thru this repo https://github.com/onedr0p/home-ops

Take a look at my open source GitOps repo managed by Flux here: https://github.com/onedr0p/home-ops

Im fully onboard with the geneneral idea as a target.

Right now it's for early early adopters. Hosting stuff is still a painm But we are getting better at hosting stuff, finding stable patterns, paving the path. Hint, it's not doing less, it's not simpler options: it's adopting & making our own industrial scale tooling. https://github.com/onedr0p/home-ops is a great early & still strong demonstration; the up front cost od learning is high, but there's the biggest ecosystem of support you can imagine, and once you recognize the patterns, you can get into flow states, make stuff happen, with extreme leverage far beyond where humanity has ever been. Building the empowered individual is happening, and we're using stable good patterns that will mean the individual isnt so off on their own doing ops- they'll have a lot more accrued human experiene at their back, their running of services isnt as simple to understand from the start but goes much much further, is much more mature & well supported in the long run.

My Kubernetes cluster, deployments, infrastructure provisioning is all available over here on Github.

For example: https://github.com/onedr0p/home-ops/pull/4528

I'm running minio in my cluster with NFS backend just fine. You can see my deployment of it here.

job "vector" { datacenters = ["dc1"] # system job, runs on all nodes type = "system" group "vector" { count = 1 network { port "api" { to = 8686 } } ephemeral_disk { size = 500 sticky = true } task "vector" { driver = "docker" config { image = "timberio/vector:0.30.0-debian" ports = ["api"] volumes = ["/var/run/docker.sock:/var/run/docker.sock"] } env { VECTOR_CONFIG = "local/vector.toml" VECTOR_REQUIRE_HEALTHY = "false" } resources { cpu = 100 # 100 MHz memory = 100 # 100MB } # template with Vector's configuration template { destination = "local/vector.toml" change_mode = "signal" change_signal = "SIGHUP" # overriding the delimiters to [[ ]] to avoid conflicts with Vector's native templating, which also uses {{ }} left_delimiter = "[[" right_delimiter = "]]" data=<

we are doing something similar with OTEL but we are looking at using https://vector.dev/

We don't pull logs, we forward logs to a centralized logging service.

opensearch - amazon fork of Elasticsearch https://opensearch.org/docs/latestif you do this an have distributed log sources you'd use logstash for, bin off logstash and use vector (https://vector.dev/) its better out of the box for SaaS stuff.

I have done something similar in the past: you can send the logs through a centralized syslog servers (I suggest syslog-ng) and from there ingest into ELK. For parsing I am advice to use something like Vector, is a lot more faster than logstash. When you have your logs ingested correctly, you can create your own dashboard in Kibana. If this fit your requirements, no need to install nginx (unless you want to use as reverse proxy for Kibana), php and mysql.

I think there's nothing currently that combines both logging and metrics into one easy package and visualizes it, but it's also something I would love to have.

Vector[1] would work as the agent, being able to collect both logs and metrics. But the issue would then be storing it. I'm assuming the Elastic Stack might now be able to do both, but it's just to heavy to deal with in a small setup.

A couple of months ago I took a brief look at that when setting up logging for my own homelab (https://pv.wtf/posts/logging-and-the-homelab). Mostly looking at the memory usage to fit it on my synology. Quickwit[2] and Log-Store[3] both come with built in web interfaces that reduce the need for grafana, but neither of them do metrics.

- [1] https://vector.dev

Log to stdout/stderr and collect your logs with a tool like vector (vector.dev) and send it to something like Grafana Loki.

I would recommend that you run vector as a systems service so you don't have to worry about managing it. Here is a basic config to do that - https://github.com/vectordotdev/vector/blob/master/distribution/systemd/vector.service .