Self-Healing Applications
AI-Powered Auto-Resolution Demo
Experience the Future of AIOps
This live demo showcases how AI agents automatically detect and resolve application issues using Elastic Observability, OpenTelemetry, and Tines automation.
How It Works
- Trigger an Issue - Click a scenario button to simulate a common production problem
- AI Detection - Tines queries the Elastic MCP endpoint every 5 minutes
- Intelligent Analysis - Elastic O11Y Copilot analyzes traces, metrics, and logs
- Auto-Resolution - Tines executes the AI-suggested fix automatically
- Verification - System confirms the issue is resolved
Available Scenarios
🧠Memory Leak
Simulate a gradual memory increase that degrades performance over time.
Detection: High memory usage + increased latency
Resolution: Service restart + cache clearing
🔌Connection Pool Exhausted
Overwhelm the database connection pool with concurrent requests.
Detection: Connection timeout errors
Resolution: Pool expansion + idle connection cleanup
⚡Rate Limit Exceeded
Generate rapid API calls that exceed rate limits.
Detection: 429 HTTP errors
Resolution: Exponential backoff implementation
🔗Dependency Failure
Simulate an external service becoming unavailable.
Detection: 503 errors + circuit breaker trips
Resolution: Fallback to cached data
Technologies Used
Elastic Observability
Trace, metric, and log collection
OpenTelemetry
Standardized instrumentation
Elastic O11Y Copilot
AI-powered analysis via MCP
Tines
Workflow automation
ES|QL
Custom observability queries
MCP Protocol
AI agent integration