Remediation Engine
Intelligent, safe, and automatic issue resolution at scale
The Remediation Process
Autonoma's remediation engine transforms predictions into safe, validated fixes. Every remediation goes through multiple safety checks and can be instantly rolled back if any issues are detected.
Fix Generation
Based on the prediction, Autonoma generates one or more potential fixes using AI models trained on your codebase and industry best practices.
// Example: Memory leak fix generation
{
"issue": "Event listener not removed on unmount",
"fixes": [
{
"confidence": 0.98,
"type": "add_cleanup",
"description": "Add componentWillUnmount cleanup",
"patch": {
"file": "UserProfile.js",
"line": 45,
"operation": "insert",
"code": "componentWillUnmount() {\n window.removeEventListener('resize', this.handleResize);\n}"
}
},
{
"confidence": 0.85,
"type": "use_hook",
"description": "Convert to useEffect with cleanup",
"patch": {
"file": "UserProfile.js",
"operation": "replace",
"from": "componentDidMount",
"to": "useEffect with cleanup"
}
}
]
}
Multi-Stage Validation
Every fix goes through comprehensive validation before being applied:
Static Analysis
Syntax validation, type checking, linting, security scanning
Test Execution
Unit tests, integration tests, regression tests, smoke tests
Impact Analysis
Dependency check, performance impact, side effect detection
Simulation
Dry-run in sandbox, behavior verification, rollback testing
Safe Application
Fixes are applied with comprehensive safety measures:
Atomic Operations
All changes are atomic - either fully applied or fully rolled back
Version Control Integration
Changes committed with detailed messages and rollback references
Real-time Monitoring
Continuous monitoring during and after application
Post-Fix Verification
After application, Autonoma verifies the fix resolved the issue without side effects:
Types of Remediations
Code Fixes
Direct code modifications to fix bugs and issues:
- •Memory leak cleanup
- •Null reference protection
- •Race condition resolution
- •Security vulnerability patches
- •Performance optimizations
Configuration Adjustments
Optimize settings and configurations:
- •Database connection pools
- •Cache settings
- •Rate limits
- •Resource allocations
- •Timeout values
Infrastructure Scaling
Automatic infrastructure adjustments:
- •Auto-scaling triggers
- •Load balancer updates
- •CDN cache invalidation
- •Database index creation
- •Container resource limits
Dependency Management
Safe dependency updates and patches:
- •Security patches
- •Bug fix updates
- •Compatibility fixes
- •License compliance
- •Version pinning
Safety Mechanisms
Instant Rollback System
Every change can be instantly rolled back if issues are detected:
// Rollback triggers
{
"automatic_triggers": {
"error_rate_increase": "> 1%",
"response_time_degradation": "> 50%",
"memory_spike": "> 20%",
"cpu_spike": "> 30%",
"failed_health_checks": "> 2"
},
"rollback_time": "< 1 second",
"data_preservation": true,
"notification": "immediate"
}
Gradual Rollout
Critical fixes can be rolled out gradually to minimize risk:
Circuit Breaker Pattern
Prevents cascading failures by stopping remediations when issues are detected:
Normal operation
Fixes paused
Testing recovery
Real-World Remediation Examples
Database Connection Pool Exhaustion
Problem Detected
Connection pool will be exhausted in 45 minutes at current rate
Automatic Fix Applied
Increased pool size from 50 to 100, optimized connection timeout
Code Changes
// config/database.yml
production:
adapter: postgresql
pool: <%= ENV.fetch("DB_POOL") { 5 } %>
- timeout: 5000
+ pool: <%= ENV.fetch("DB_POOL") { 100 } %>
+ timeout: 3000
+ idle_timeout: 600
+ checkout_timeout: 5
Memory Leak in React Component
Problem Detected
Memory usage increasing 50MB/hour due to event listener leak
Automatic Fix Applied
Added cleanup function to remove event listeners on unmount
Code Changes
// components/Dashboard.jsx
useEffect(() => {
const handleScroll = () => setScrollY(window.scrollY);
window.addEventListener('scroll', handleScroll);
+ return () => {
+ window.removeEventListener('scroll', handleScroll);
+ };
}, []);
SQL Injection Vulnerability
Problem Detected
Unsanitized user input in SQL query construction
Automatic Fix Applied
Converted to parameterized query with input validation
Code Changes
// api/users.py
def search_users(name):
- query = f"SELECT * FROM users WHERE name LIKE '%{name}%'"
- return db.execute(query)
+ query = "SELECT * FROM users WHERE name LIKE ?"
+ return db.execute(query, [f"%{name}%"])
Remediation Metrics
Success Rate
Last 30 days
Avg Fix Time
Code generation
Rollback Rate
Safety working
Availability
Always protecting
Impact Summary
Issues Prevented
47,293
Downtime Avoided
1,247 hours
Revenue Saved
$2.4M
Developer Hours Saved
8,420
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