Reduced manual recovery effort and improved operational confidence for cloud infrastructure incidents.
Automated VM Recovery System
Designing a Java-based recovery system for cloud infrastructure using OpenStack APIs
Designed backend recovery logic for cloud VMs so operators could restore critical workloads faster during incidents.
Owned recovery target selection, priority rules, OpenStack API integration, and incident-state visibility.
Enterprise Cloud Platform
Why this matters
Automated recovery logic for 50+ cloud VMs
Priority-based handling for critical workloads
OpenStack API integration for production operations
Visual Evidence
What to show hereRecovery orchestration signal flow
This project is strongest when shown as a simple incident-to-recovery pipeline: detection, prioritization, API execution, and operator visibility.
Replace this panel with a screenshot, diagram, or product crop when you have one. For now it acts as a guided visual placeholder.
Replace this panel with a screenshot, diagram, or product crop when you have one. For now it acts as a guided visual placeholder.
Replace this panel with a screenshot, diagram, or product crop when you have one. For now it acts as a guided visual placeholder.
1. Context
- Korean cloud platform company serving enterprise and government-focused private cloud environments.
- The product area was operational stability: keeping VM services recoverable during incidents without slowing operators down.
2. Problem
When VM failures occurred, manual recovery was slow and operationally risky. Operators needed a way to recover important VMs first, track recovery status, and reduce repeated manual work during infrastructure incidents.
3. Constraints
- Recovery behavior had to minimize impact on already running workloads.
- The system needed to integrate cleanly with OpenStack APIs.
- Priority rules had to reflect VM criticality.
- Failures needed logging and retry handling.
- Operators had to understand system state during an incident.
4. Solution
- Selected recovery targets based on incident context and recovery eligibility.
- Applied priority-based processing so critical VMs were handled first.
- Integrated recovery actions with OpenStack APIs.
- Tracked recovery status and exposed logs for operational visibility.
- Added error handling paths to reduce repeated manual work.
5. Architecture / Flow
Failure detected or recovery requested
This is the trigger or incoming operational event.
Recovery target selected
This stage moves the workflow toward a reliable production result.
Priority rule applied
This stage moves the workflow toward a reliable production result.
OpenStack API call executed
This stage moves the workflow toward a reliable production result.
Recovery status updated
This stage moves the workflow toward a reliable production result.
Logs stored
This stage moves the workflow toward a reliable production result.
Operator reviews result
This is the observable outcome for operators or users.
6. Trade-offs
| Option | Pros | Cons | Decision |
|---|---|---|---|
| Fully automated recovery | Fastest response time during incidents | Higher risk of incorrect recovery actions | Chose partial automation with operator visibility and confirmation considerations |
| Manual recovery only | Operationally conservative | Slow and repetitive under pressure | Automated the repetitive path to improve reliability |
| Simple sequential recovery | Easy to implement | Important VMs could wait too long | Used priority-based recovery rules |
| Complex rule engine | Flexible over time | High initial complexity | Started with core rules that solved the immediate operational problem |