XLabs

Docker Is Not Running

If a local lab says Docker is not running, open Docker Desktop manually and wait until it is fully started.

Then run a simple Docker test from your terminal before reopening XLabs. This matters because Docker CLI and Docker daemon are different things: the command can exist even when the engine is not running.

Open Docker Desktop.

Wait until Docker reports it is running.

Run: docker run --rm hello-world

Restart the XLabs app and try the lab again.

XLabs App Not Detected

If the browser cannot detect the XLabs app, make sure the app is open and your firewall, VPN, or endpoint security is not blocking localhost connections.

Restarting the app after Docker is running fixes many local startup issues.

Confirm the XLabs app is open.

Confirm Docker Desktop is running.

Restart the XLabs app after Docker is ready.

Check whether VPN, proxy, firewall, or endpoint security is blocking localhost connections.

Lab Starts But The Environment Fails

If a lab starts but the terminal environment fails, the setup script may not have completed or Docker may have run out of available resources.

Restart Docker Desktop, close old lab sessions, and try again. If the lab uses Kubernetes or multiple containers, the first run can take longer because Docker may need to prepare images and networks.

Lab Access Issues

If a lab says hub access is required, your account may not be part of the live hub that contains that lab.

Normal learners should only see usable labs and challenges from live hubs they can access. If something looks wrong, refresh your hub membership or contact the hub owner.

Leftover Containers Or Networks

If a previous local lab failed halfway, old Docker containers or networks may remain on your machine.

Use the cleanup option in XLabs when available. If cleanup is not available, restart Docker Desktop and try again.

Leftover resources are more common after interrupted dual-terminal labs, Kubernetes labs, or failed local setup attempts.

When To Use Cloud Execution

If you are on a work laptop, restricted network, temporary device, or machine where Docker cannot run reliably, use cloud execution when it is available.

Cloud execution is useful for getting unstuck, but local execution is still valuable for regular practice because it teaches you how tools behave on your own machine.