Detect Issues Before
Your Users Do
Watch Tower uses AI-powered anomaly detection to automatically identify performance issues, error spikes, and latency problems, delivering actionable insights and root cause analysis in real-time.
87%
Faster Issue Detection
24/7
Automated Monitoring
60%
Reduced MTTR
Zero
Configuration Required
Anomaly Detection That Actually Works
Unlike traditional threshold-based monitoring that creates false positives, Watch Tower uses machine learning to detect only real anomalies.
Dynamic Baseline Learning
Establishes intelligent baselines by analyzing 6+ weeks of historical data across latency, throughput, and error rates. Automatically adapts to traffic patterns and seasonal variations, eliminating manual threshold tuning.
Automated Root Cause Analysis
Analyzes service dependencies, distributed traces, and infrastructure metrics (CPU, memory, disk) to identify the actual root cause, not just symptoms. Distinguishes between dependency failures, resource exhaustion, and infrastructure issues.
Multi-Signal Impact Analysis
Correlates anomalies across latency, throughput, and failure rates to calculate the real scope of degradation. Shows which specific services, endpoints, and user segments are experiencing issues, not just vague "performance problems."
Bucket Pattern
Evaluates billions of data points in real-time across multiple time windows. Catches severe log anomalies (10+ minutes duration with significant increases) and APM degradation before user complaints arrive.
Contextual Investigation Insights
Surfaces tag-based patterns in query results to highlight outliers like a specific database shard, geographic region, or API version causing disproportionate errors. Provides suggested next steps and relevant monitors to activate.
Full-Stack Telemetry Coverage
Unified detection across APM traces, infrastructure metrics, and log streams. Single alert shows the complete picture: which microservice failed, what infrastructure resource was exhausted, and which logs captured the error, no tool-switching required.
How Watch Tower Works?
From detection to resolution, Watch Tower streamlines your incident response workflow
Trace Issues to Root Cause
Watch Tower connects the dots across your services, infrastructure, and logs. When an issue occurs, it shows you the exact service that failed first and why, not just that something is wrong.
- Service dependency graph shows the failure path
- Distributed traces pinpoint where latency started
- Infrastructure metrics reveal what resource was exhausted
- One view instead of jumping between tools
Find patterns you've seen before
Watch Tower keeps 6 months of detected anomalies organized by service and severity. If the same issue keeps happening, you'll spot it and fix it once and for all.
- Browse all detected anomalies with full context
- Filter by service, status, and time range
- One click to see the full incident details
- Track resolution from detection to close
Alert on what actually matters
Watch Tower builds baselines from your real traffic patterns, not arbitrary numbers. It adapts to peak hours, weekly cycles, and seasonal changes, so it only alerts when something genuinely abnormal happens.
- Baseline bounds adjust automatically over time
- Accounts for traffic patterns and seasonality
- 80% fewer false alarms than static thresholds
- Learns continuously as your app evolves
Comprehensive Anomaly Detection
Watch Tower monitors every layer of your application stack
APM Anomalies
CriticalDetect performance degradation in your applications before they impact users
- Latency spikes and slowdowns on specific transactions
- Error rate increases across services and endpoints
- Throughput drops indicating potential bottlenecks
- Failure patterns in distributed service calls
Log Anomalies
ImportantSurface critical issues hidden in high-volume log data
- Severe error log patterns lasting 10+ minutes
- Significant increases in error rates with low noise
- Unusual log volume spikes across services
- Critical status changes in system components
Infrastructure Issues
WarningCatch resource exhaustion before it causes outages
- CPU, memory, and disk usage anomalies
- Network throughput degradation
- Container and pod health deterioration
- Database connection pool exhaustion
Automatic Baseline Learning
IntelligentEstablishes baselines without manual configuration
- Learns from historical data patterns automatically
- Adapts to traffic variations and seasonality
- Continuous baseline refinement
- Zero-touch setup and optimization
Real Business Impact
What Engineering Teams Actually Achieve?
Watch Tower doesn't just detect anomalies, it fundamentally changes how teams operate during incidents
Cut MTTR by 60% on Average
Stop spending hours correlating metrics, logs, and traces manually. Watch Tower's RCA shows you the exhausted database connection pool, the failing dependency, or the resource bottleneck in seconds, not hours. Teams report going from 2-hour investigations to 15-minute fixes.
Eliminate Alert Fatigue
No more waking up at 3 AM for false positives. Watch Tower learns your traffic patterns (including daily cycles, weekend dips, and promotional spikes) to alert only on genuine anomalies. Teams reduce alert volume by 80% while catching 100% of critical issues.
Know Exactly Who's Affected
Impact Analysis tells you if 5 users or 5,000 are experiencing the issue, which geographic regions are affected, and whether it's isolated to specific API versions or customer segments. Prioritize fixes based on actual business impact, not just metric severity.
Detect Performance Issues Instantly
Watch Tower detects when your application's performance degrades, error rates spike, or infrastructure resources become exhausted. Get alerted within the analysis bucket window, preventing major incidents before they impact your users.
Reduce Mean Time To Detection
Watch Tower analyzes application behavior continuously within its analysis windows, catching issues as soon as they occur. By reducing detection latency and providing immediate RCA, teams can respond to incidents faster and prevent user-facing impact.
Zero Operational Overhead
No ML models to train, no baselines to configure, no thresholds to tune. Watch Tower works out of the box on day one. Requires only 24 hours minimum data (optimal with 6 weeks) and automatically improves as it learns your application patterns.