opentelemetry-collector-co VS kind

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...

To get started, you'll need to install clusteradm and kubectl and start up three Kubernetes clusters. To simplify cluster administration, this article starts up three kind clusters with the following names and purposes:

Kind: is a tool for running local Kubernetes clusters using Docker container "nodes." It was primarily designed for testing Kubernetes itself but can also be used for local development or continuous integration.

Fortunately, just as projects like kind and Minikube enable developers to spin up a local Kubernetes environment in no time, CRC, also known as OpenShift Local and a recursive acronym for "CRC - Runs Containers", offers developers a local OpenShift environment by means of a pre-configured VM similar to how Minikube works under the hood.

I recently purchased a used Lenovo M900 Think Centre (i7 with 32GB RAM) from eBay to expand my mini-homelab, which was just a single Synology DS218+ plugged into my ISP's router (yuck!). Since I've been spending a big chunk of time at work playing around with Kubernetes, I figured that I'd put my skills to the test and run a k3s node on the new server. While I was familiar with k3s before starting this project, I'd never actually run it before, opting for tools like kind (and minikube before that) to run small test clusters for my local development work.

Features compared to https://kind.sigs.k8s.io/

Kind allows you to run a Kubernetes cluster inside Docker. This is incredibly useful for developing Helm charts, Operators, or even just testing out different k8s features in a safe way.

Check out KinD

If you're just messing around, just use kind (https://kind.sigs.k8s.io) or minikube if you want VMs (https://minikube.sigs.k8s.io). Both work on ARM-based platforms.

You can also use k3s; it's hella easy to get started with and it works great.

We'll install APIClarity into a Kubernetes cluster to test our API documentation. We're using a Kind cluster for demonstration purposes. Of course, if you have another Kubernetes cluster up and running elsewhere, all steps also work there.

yes I know there is lens, but it does not allow me to see logs of multiple pods at same time and what is even more important it is not friendly for ephemeral clusters - in my case with help of kind I am recreating whole cluster each time from scratch