Closed t-sorger closed 1 month ago
We certify that generative AI, incl. ChatGPT has not been used to write this feedback. Using generative AI without permission is considered academic misconduct.
We'd like to start by thanking Tom Sorger and Marco Campione for the opportunity to provide feedback on their executable tutorial.
The tutorial is well-structured and consistently highlights your current process throughout the tutorial with a roadmap picture at the bottom. It also consistently highlights button names to make them easier to see within the text. Where possibly the tutorial makes use of Killerconda-specific functionality like clicking on a command in the tutorial description automatically executes the command in the shell next to it. In addition, the various tutorial pages are easy to follow because they are written in easy language, with short sentences, and use enumerations instead of a full paragraph of text wherever possible. This allows you to easily keep track of where you are currently at within the tutorial.
The tutorial clearly motivates why it matters for DevOps and also chooses data as an example that could be produced by a DevOps code-building pipeline. The tutorial starts from the very beginning where Splunk hasn't even started yet and walks us through the process of getting data into the system, creating an easy visualization, a more complex visualization, and the configuration of alerts. Content-wise this is a good selection of topics that are covered in the right sequence. And especially the complex visualization dashboard shows a great illustration of the chosen demo data.
We really loved that you guys didn’t have one but three easter eggs, hidden in the message. It was tough to find them but we managed.
The tutorial is mainly structured in a way that tells the student “Do this and then do that”. It often doesn’t cover why we are doing this. We would have liked a bit more guidance in “Step 5 - Modifying The Dashboard”. It’s a great idea to just let the student explore Splunk a bit more on their own, but we would have liked a pointer in a certain direction. For example by giving them an exercise like: “We just saw that our data entails information about whether a software build job succeeded or failed. Try to create a new dashboard that visualizes this information and displays how many percent of jobs fail and how many succeed”. In the next step, your own complex dashboard would then show off a way of how this exercise can be solved and can introduce various other good visualizations in addition (like the ones you already decided to include).
In the very beginning, it would have been cool to have a (short) introduction to what Splunk actually is, as the tutorial starts with motivating why Splunk dashboards matter. We would suggest adding this link: What Splunk Does. This would add a valuable read for the user.
While still describing well what the tutorial will cover, the “What You’ll Learn” section is hyping up the content of the tutorial a bit too much :) For example, we are executing a script that somewhere along its execution spins up a Docker container for us. We’d rather have a walkthrough of the process of setting up/ installing Splunk in a Docker container. This would let the user learn how to set up Splunk on their own device without being tempted to copy your script.
On step 6 – 'A more complex demo dashboard,' we ran into some confusion with step 8. A simple hint, like adding parentheses to say 'open a new tab,' would have probably saved us a bit of time (or at least for one of us, maybe a few 'aha' moments along the way ;) ).
The tutorial is visually appealing, and the content is well thought out. It’s very educational, starting with a simple demo and progressively adding more advanced features, making it an effective way to learn. Great work, and thank you for helping us dive deeper into Splunk!
https://www.splunk.com/en_us/blog/learn/what-splunk-does.html
Assignment Proposal
Title
Setting Up a Dashboard using Splunk
Names and KTH ID
Deadline
Category
Description
In this executable tutorial, we will guide the user through running Splunk. We will add a data source and create a dashboard to visualize data using the new Splunk Dashboard Studio. The data source will be set up to dynamically grow in size and change its data over time, showcasing Splunk's real-time capabilities. Finally, we will configure an alert to trigger when a specific data threshold is met.
The executable tutorial can be found on Killercoda or GitHub.
Relevance
"Having good dashboards is essential in DevOps" (see here).