examples VS prometheus

Honeycomb

I haven't used anything else, but I'll gladly shill for https://honeycomb.io.

With all of this in place I went a step further and added Opentelemetry to track the stats of how often the routine was being triggered on Honeycomb.

Events can be used in many meaningful ways. The Event subsystem of B is pretty much a co-evolution of what honeycomb.io offers, but implemented completely differently - it is on bare-metal, and hence a lot cheaper. Because of that, B never subsampled, but always kept a full low of all events anywhere, no exceptions.

It should be noted that this is a very oblique ad for http://honeycomb.io. That in no way impugns the content of the post, and in fact, it's given the content of the post that I feel compelled to point out that, ultimately, this is an ad. Because what is sales and advertising, anyway? It's just a way to get you to buy a product, and you can't do that if you've never even heard about the product. I'm not currently in the market for an observability solution (something something splunk) but if I were, I've now heard of them.

The question though, is why does money ruin everything? The naive questions of an open source zealot to a proprietary software salesperson are one thing, but since we all need money to live, why does money being part of the equation (eg if someone was getting paid to post here) ruin things? Would a "donate to open source" button be more successful if the donate text is "buy me a coffee", "buy me a beer", or "upgrade my beer from Coors light"?

https://xkcd.com/2347/ was and is true, and if we don't figure out a way to change that, I don't really see a future for open source.

Very cool to see honeycomb.io is doing that. I'm about to embark on my distributed tracing learning journey, this makes me want to try honeycomb right away.

Caveat: I work for a vendor in the O11y space (https://honeycomb.io) as a Developer Advocate, however, this advice is generic, not specific to our platform.

I spent Day 2 at the Colony Club to attend OTel Unplugged. This event was sponsored by Lightstep, Honeycomb, New Relic, Splunk, Dynatrace, Crowdstrike, and NGINX. I came into the event not knowing what to expect. I can sometimes clamp up when I’m around folks that I don’t know, but because I was helping with the event check-in, I got to say hello to a number of the attendees, which helped break the ice. And it turns out that there were a lot of names that I recognized from my work in the OTel community, and it was nice to connect in person with folks whom I’d only previously met through Slack or Zoom.

It's no surprise that my apps are mostly written using Sanic as I'm pretty involved with the project. I've been wanting to start testing honeycomb out as well, so it seemed the perfect opportunity to try out.

It's like Prometheus, but for logs. Okay it's not really to do with the Norse or Greek gods, instead Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by the open source project Prometheus. Built by Grafana Labs, Loki is designed for ease of use. Instead of indexing the contents of the logs, Loki provides a set of labels for each log stream. The latest update includes query acceleration with Bloom filters, native OTel support, Helm charts, and more. Check out the changelog for all the major changes and deprecations.

WriteRequest::timeseries is a vector (https://github.com/prometheus/prometheus/blob/main/prompb/re...) and

Developers widely use Prometheus as a system for operational monitoring and alerting for their projects. Here is a list of tools for monitoring frontend services with Prometheus.

Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.

Distributed system administrators need mechanisms and tools for monitoring individual nodes in order to analyze the system and promptly detect anomalies. Developers also need effective mechanisms for analyzing, diagnosing issues, and identifying bugs in protocol implementations. Logging, tracing, and collecting metrics are common observability techniques to allow monitoring and obtaining diagnostic information from the system; most of the explored code bases use these techniques. OpenTelemetry and Prometheus are popular open-source monitoring solutions, which are used in many of the explored code bases.

Setting up monitoring for a system, especially one involving GRPC communication, provides crucial visibility into its operations. In this guide, we walked through the steps to instrument both a GRPC server and client with Prometheus metrics, exposed those metrics via an HTTP endpoint, and visualized them using Grafana. The Docker-Compose setup simplified the deployment of both Prometheus and Grafana, ensuring a streamlined process.

Alerting and Notification: Select a tool with flexible alerting mechanisms to proactively detect anomalies or deviations from defined thresholds. Consider asking questions like "Does this tool offer customizable alerting options and support notification channels that suit our team's communication preferences?" A tool like Prometheus provides robust alerting capabilities.

Prometheus

Prometheus is an open-source monitoring and alerting toolkit. It is designed to monitor highly dynamic containerized systems, making it an excellent choice for monitoring Docker containers and Kubernetes clusters.

wget https://github.com/prometheus/prometheus/releases/download/v2.46.0/prometheus-2.46.0.linux-amd64.tar.gz