opentelemetry-collector-co VS vector

The open telemetry collector does just that. https://github.com/open-telemetry/opentelemetry-collector-co...

If you are using the prometheus exporter, you can use the transform processor to get specific resource attributes into metric labels.

With the advantage that you get only the specific attributes you want, thus avoiding a cardinality explosion.

https://github.com/open-telemetry/opentelemetry-collector-co...

The article seems to suggest https://github.com/open-telemetry/opentelemetry-collector-co... was silently killed, yet it appears to have been merged in January, am I missing something?

OpenTelemetry is a large suite of software, that supports many use cases. I think you got what you wanted but didn't realised it!

The dedicated executable that you are after is called the OpenTelemtry Collector.

The OpenTelemetry SDK for language of choice should include many exporters, which describe the format and transport mechanism for the traces. The OpenTelemetry Collector can then use an appropriate receiver to ingest those traces.

Here is a file based receiver for the collector:

https://github.com/open-telemetry/opentelemetry-collector-co...

This arch is how the big players do it at scale (ie. datadog, new relic - the second it passes their edge it lands in a kafka queue). Also otel components lack rate limiting(1) meaning its super easy to overload your backend storage (s3).

Grafana has some posts how they softened the s3 blow with memcached(2,3).

1. https://github.com/open-telemetry/opentelemetry-collector-co...

Ah yeah the easiest way is probably using the OpenTelemetry collector to set up a process to pull your logs out of jounrnald and send them via otel logs to HyperDX (or anywhere else that speaks otel) - the docs might be a bit tricky to go around depending on your familiarity with OpenTelemetry but this is what you'd be looking for:

https://github.com/open-telemetry/opentelemetry-collector-co...

Happy to dive more into the discord too if you'd like!

Link to exact comment: https://github.com/open-telemetry/opentelemetry-collector-co...

What schema does SigNoz use with Clickhouse? The Open Telemetry Collector uses this schema https://github.com/open-telemetry/opentelemetry-collector-co... and I found out that accesing map attributes is much slower (10-50x) compared to regular columns. I expected some slow down but this is too much.

Podman does support docker API so you can use something like the OpenTelemetry Collector to fetch metrics using the docker API and forward them to prometheus.

Collector: https://github.com/open-telemetry/opentelemetry-collector-co...

Docker receiver: https://github.com/open-telemetry/opentelemetry-collector-co...

Prometheus exporters: https://github.com/open-telemetry/opentelemetry-collector-co... and https://github.com/open-telemetry/opentelemetry-collector-co...

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 .