High Availability & Automation
Bring together configuration automation and availability engineering in a challenge-only course focused on Ansible, load balancing, failover, and operational validation. This project tests whether you can move from configuring single services to delivering resilient service behavior across multiple nodes.
Why It Matters
Reliable infrastructure is not only about getting a service running once. Teams also need repeatable deployment, balanced traffic, and failure handling when a node disappears. This project helps you connect automation and high-availability thinking into a more realistic service delivery workflow.
What You Will Learn
- Use automation to deploy and standardize service configuration across hosts.
- Configure a load-balancing layer that distributes traffic intentionally.
- Implement failover behavior so service access survives a node-level problem.
- Validate high-availability behavior through explicit testing instead of assumption.
- Work independently through challenge-only tasks that combine multiple infrastructure layers.
- Integrate Ansible, HAProxy, and Keepalived skills into one operational pattern.
Course Roadmap
The project begins with Ansible web deployment, where repeatable configuration becomes the foundation for the rest of the environment. It then moves to load balancer configuration, placing HAProxy in front of the service nodes to distribute traffic.
Next, you complete a high-availability cluster challenge that brings failover design into the stack. The project ends with an automated failover test, reinforcing that resilient infrastructure must be verified under failure conditions rather than trusted on paper.
Who This Course Is For
This course is for learners who have completed the automation and high-availability modules and want a challenge-only review centered on resilient service delivery.
Outcomes
By the end of this course, you will be able to connect automation, traffic distribution, and failover into a more complete high-availability workflow and validate that the resulting service behaves as intended under disruption.
