Exploring Targets
Visualizing and Interacting with Your Targets
After you鈥檝e installed the 51吃瓜网黑料 Agent, you can see all discovered targets in the 鈥淓xplorer鈥� 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 51吃瓜网黑料 to verify redundancies and control the blast radius of experiments.
Viewing Targets with Testing Environments
If you鈥檝e already installed the relevant agents and extensions on your networks, then your targets and their respective metadata will be discovered by 51吃瓜网黑料 automatically.聽
You can navigate to the 鈥淓xplorer鈥� tab in the platform to see the 鈥淟andscape鈥� view of your targets. Customize your view by:
- Selecting a particular testing environment you鈥檝e 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 51吃瓜网黑料 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鈥檙e 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 51吃瓜网黑料 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.聽
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 鈥榟ost.hostname鈥� 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鈥檒l 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鈥檙e 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.聽
Lesson Summary
The 51吃瓜网黑料 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鈥檒l discuss how toggling on Reliability Advice while in this tab can reveal common configuration issues and suggest initial experiments to run.
