polly
vector
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polly | vector | |
---|---|---|
1 | 96 | |
83 | 16,427 | |
- | 5.2% | |
0.0 | 9.9 | |
over 2 years ago | 6 days ago | |
CUE | Rust | |
Apache License 2.0 | Mozilla Public License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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.
polly
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Cue, an open-source data validation language
re: Grafana (i'm the author of the linked issue) - i'm quite excited, i do think there's a world of possibilities here.
Two-way sync with a git repo is one possible path, and we've talked a lot internally at GL about how to best support it. My sense is that we can do it with relatively little friction and likely will - but if you're just syncing with a git repo, there's still a lot of arbitrary, opaque repo layout decisions that still have to be made (how do you map a filesystem position for a dashboard to a position in Grafana? In a way that places the dashboards next to the systems they're intended to observe? With many teams? With many Grafana instances?) which induce new kinds of friction at scale.
Fortunately - and not mutually exclusively with the above - by building the system for schema in CUE, we've made a composable thing that we can make into larger systems. That's what we're starting to do with Polly: https://github.com/pollypkg/polly
Conveniently, my parts of a Grafanaconline talk tomorrow discusses both of these https://grafana.com/go/grafanaconline/2021/dashboards-as-cod... :D
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?
quicktype - Generate types and converters from JSON, Schema, and GraphQL
graylog - Free and open log management
cuetsy - Experimental CUE->TypeScript exporter
Fluentd - Fluentd: Unified Logging Layer (project under CNCF)
lowdefy - The config web stack for business apps - build internal tools, client portals, web apps, admin panels, dashboards, web sites, and CRUD apps with YAML or JSON.
agent - Vendor-neutral programmable observability pipelines.
cue - CUE has moved to https://github.com/cue-lang/cue
syslog-ng - syslog-ng is an enhanced log daemon, supporting a wide range of input and output methods: syslog, unstructured text, queueing, SQL & NoSQL.
aontu - Unifier
OpenSearch - 🔎 Open source distributed and RESTful search engine.
baleen - Kotlin DSL for validating data (JSON, XML, CSV, Avro)
tracing - Application level tracing for Rust.