k6 VS Grafana

I know this is about Desktop HTTP testing but has anyone experimented with command-line HTTP testing?

I recall having a good experience with https://github.com/grafana/k6 some eons ago.

It's geared towards writing load testing in JS but it also allows you to check HTTP body, headers, etc.

K6' usage - pretty friggin robust - is here https://github.com/grafana/k6/tree/master/js

k6 allows you to build performant load tests that take a fraction of the resources legacy load-testing tools require. The tests are written in an easy-to-follow JavaScript form and can be extended with a number of extensions. The tests execute via a Go-JavaScript compiler so they take a minimal amount of resources when being executed, allowing the scaling of load tests with fewer resources.

I’d use K6 for this. It’s been optimised for this purpose. https://github.com/grafana/k6

k6

k6 0.38.1 is a minor patch. To view all the new features, check out k6 0.38.0 tag. Following are the noteworthy features in 0.38.0.

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:

Robin switched to the Grafana dashboard tab, and sure enough, the 5xx volume on web service was rising. It had not hit the critical alert thresholds yet, but customers had already started noticing.