otomi-core
vector
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otomi-core | vector | |
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75 | 96 | |
2,136 | 16,427 | |
1.4% | 4.8% | |
9.6 | 9.9 | |
2 days ago | about 3 hours ago | |
Mustache | Rust | |
Apache License 2.0 | Mozilla Public License 2.0 |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
otomi-core
- Otomi – Self-Hosted PaaS for Kubernetes
- Self-hosted Kubernetes-based Heroku alternative
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What is a self-hosted Kubernetes-based PaaS?
An example of a self-hosted Kubernetes-based PaaS is Otomi. Install Otomi on your Kubernetes cluster, compose your platform (by activating the required capabilities) and build, deploy and expose apps in just a couple of minutes. Heroku, but Kubernetes native and running on your own cluster.
- GitHub - redkubes/otomi-core: Self-hosted PaaS for Kubernetes
- GitHub - redkubes/otomi-core: Self-hosted & Git-based PaaS for Kubernetes
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Add developer- and operations-centric tools, automation and self-service on top of Kubernetes
This video shows some of the new features of Otomi version 0.19.0 that will be released in Week 11 2023. Follow us on GitHub and be the first to try it out: https://github.com/redkubes/otomi-core
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Selfhosted PaaS? (No dokku pls)
Otomi
- Self-hosted DevOps Platform as a Service for Kubernetes
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Kubernetes is only a multi-node cluster kernel
Kubernetes is 'only' a multi-node cluster kernel. Some call it the Linux of the cloud.
And because K8s is only a kernel, there are now over 2000+ (open source) projects, all adding some extra functionality to it. Be it for observability, security, or networking. But all of these projects don't really collaborate and end-users don't ask for maturity of individual projects, they want sets/stacks of projects that integrate well.
Now every company has created some Stack with applications and configurations for Kubernetes, all trying to reinvent the wheel and spending an often shocking $ in doing so.
So here is my take:
- Let's create a new category in the Cloud Native Computing Foundation (CNCF) landscape and call it Integrated Stacks for K8s
- To be accepted, a stack needs to provide an open integration framework for other projects to add/integrate their apps
- Just like aLinux distro, each stack is ideal for some specific use case(s)
- A stack can be installed in one run, contains integrated apps that work out-of-the-box, has a (web) UI that acts as a desktop environment to provide easy and secure access to all features. Call it a new user experience for Kubernetes
Wouldn't it be great to have a list of all Kubernetes stacks available that everyone can use (and contribute to)? Just like (in the Linux analogy) you can choose between Linux Mint, Fedora, or Ubuntu.
We already created the first: https://github.com/redkubes/otomi-core
vector
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Docker Log Observability: Analyzing Container Logs in HashiCorp Nomad with Vector, Loki, and Grafana
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=<
- FLaNK AI Weekly 18 March 2024
- Vector: A high-performance observability data pipeline
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Hacks to reduce cloud spend
we are doing something similar with OTEL but we are looking at using https://vector.dev/
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About reading logs
We don't pull logs, we forward logs to a centralized logging service.
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Self hosted log paraer
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.
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creating a centralize syslog server with elastic search
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.
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Show HN: Homelab Monitoring Setup with Grafana
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
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Retaining Logs generated by service running in pod.
Log to stdout/stderr and collect your logs with a tool like vector (vector.dev) and send it to something like Grafana Loki.
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Lightweight logging on RPi?
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 .
What are some alternatives?
k3os - Purpose-built OS for Kubernetes, fully managed by Kubernetes.
graylog - Free and open log management
charts - TrueNAS SCALE Apps Catalogs & Charts
Fluentd - Fluentd: Unified Logging Layer (project under CNCF)
k8s-gitops - GitOps principles to define kubernetes cluster state via code
agent - Vendor-neutral programmable observability pipelines.
quickstart - Quickstarts to provision Kubernetes with Otomi
syslog-ng - syslog-ng is an enhanced log daemon, supporting a wide range of input and output methods: syslog, unstructured text, queueing, SQL & NoSQL.
helm-charts - Temporal Helm charts
OpenSearch - 🔎 Open source distributed and RESTful search engine.
ingress-nginx - Ingress-NGINX Controller for Kubernetes
tracing - Application level tracing for Rust.