prom-client VS Grafana

However, for this tutorial, the Prom-client package will be used as it has user-friendly documentation, a large user base and strong community support. Here is a link to its documentation and npm page.

prom-client

This approach will work as long as you don’t need to run multiple instances of the application in cluster mode. For collecting metrics in cluster mode, prom-client provides a good example with metric aggregation. But what if you’re running the application through the process manager PM2, where you don’t have access to the running cluster?

You would need to build a custom endpoint if it's a custom application that Prometheus can scrape but there are many libraries for that like prom-client for NodeJS or prometheus-net for C#. The list of client libraries can be found here.

For node, try this: https://github.com/siimon/prom-client

The metric itself is process_start_time_seconds (from the prom-client NodeJS package), which returns the timestamp in seconds corresponding to the start time of the process.

Consumer lag will quickly show any functional or technical issue with your event stream. By using the code examples from this blogpost, you can avoid having to dive into the SDKs yourself. Of course, you can adopt the metric collection to send the metric to the logs or to another metrics system like prometheus, datadog, or open telemetry.

There is a node client library for backend dev.

Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.

To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.

Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.

Prometheus: Open-source monitoring system. Often used together with Grafana.

Grafana

Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.

So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:

In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana: