Exploring Targets
Visualizing and Interacting with Your Targets
After you’ve installed the Steadybit Agent, you can see all discovered targets in the “Explorer” tab.
Targets are the discovered infrastructure components that you could potentially use in your experiments.
In this lesson, we will explain how you can view and interact with your targets in Steadybit to verify redundancies and control the blast radius of experiments.
Viewing Targets with Testing Environments
If you’ve already installed the relevant agents and extensions on your networks, then your targets and their respective metadata will be discovered by Steadybit automatically.
You can navigate to the “Explorer” tab in the platform to see the “Landscape” view of your targets. Customize your view by:
- Selecting a particular testing environment you’ve already defined
- Adding a filter to drill down on specific targets
- Grouping components based on a certain attribute
- Change the size or color of targets based on attributes
There are pre-configured views in Steadybit for common use cases, like viewing a Kubernetes cluster. If you want to keep a particular view in the Explorer, you can easily label and save that view for future use.
The goal of this Explorer feature is to enable you to learn more about your systems through an interactive visual map you can customize as you go.
Grouping and Filtering Targets
As you’re exploring your targets, it may be helpful to narrow your view or categorize your targets with groups. To make these adjustments, you can add filters and groupings using the Query UI we mentioned during the lesson on Testing Environments. Select attributes and AND logic to adjust your parameters. Similarly, you can use the Steadybit query language to set these up if you need more flexibility.
For example, you could decide to group your targets by the Kubernetes cluster name, followed by the namespace, and then by the workload owner.
Next, you could set specific colors based on the host name for a given resource to see if any deployments are only running on a single node versus multiple nodes.
If you wanted to filter for these single node resources instead of using a color label, you could specify that the ‘host.hostname’ attribute, which is also added to the Kubernetes deployment, should exist only once. Manuel explains this approach fully in the video above.
Verifying System Redundancies
Just by reviewing your targets, you can start to see reliability gaps. For example, if you see that a given resource is running on a single node, that could be a risk. By interacting with groups, filters, and attributes; you can determine if you have redundancies in place or if you need to make adjustments to distribute the risk across multiple nodes.
If you have AWS targets, you’ll have access to pre-built views to help with this type of analysis. You can see views that identify which Kubernetes workload resources are running in which AWS availability zones, or check whether all containers across your Kubernetes clusters are using the same container runtime when you’re currently migrating to a new one.
This visualization of your environments can enable you to quickly identify reliability weaknesses and start making improvements even before your first experiment run.
Lesson Summary
The Steadybit Explorer is a critical tool for learning about your systems proactively. From groups and filters to color labels and saved views, you can customize your targets in any way you want. Next, we’ll discuss how toggling on Reliability Advice while in this tab can reveal common configuration issues and suggest initial experiments to run.
