Predictive Analysis
NeuBird doesn't just react to incidents — it helps you see them coming. Ask about risk, degradation trends, or capacity limits, and NeuBird queries your telemetry to identify what's most likely to page you next.
What you can ask
Degradation forecasting:
> Based on current trends, what services are at risk of degrading in the next 24 hours?
NeuBird checks latency percentiles, error rate trajectories, resource saturation, traffic growth, and dependency health to tell you where capacity runs out first.
Blast radius analysis:
> If the primary RDS instance goes down, what's the blast radius?
NeuBird traces service dependencies, checks which services depend on the database, and maps the failure cascade.
Risk assessment:
> What's quietly degrading that could page me tonight?
NeuBird looks for silent signals — slowly climbing memory usage, connection pool exhaustion, disk fill rates, error rates that are elevated but not yet alarming.
How it works
Predictive analysis uses the same agentic investigation engine as reactive investigations. The difference is the question — instead of asking "what happened?", you're asking "what's about to happen?"
NeuBird:
- Queries current metrics and compares against historical baselines
- Identifies trends that are moving in the wrong direction
- Projects when thresholds will be breached at current rates
- Cross-references with recent changes (deploys, config changes) that could be contributing
- Ranks risks by severity and time-to-impact
Example scenarios
| Question | What NeuBird checks |
|---|---|
| "What services are at risk in the next 24h?" | Latency trends, error rates, resource saturation, capacity headroom |
| "What happens if Redis goes down?" | Service dependency map, connection counts, failover configuration |
| "Are there any capacity cliffs approaching?" | Disk fill rates, connection pool usage, memory trends, ACU utilization |
| "What's the riskiest thing in production right now?" | Combines all signals — incidents, alarms, metrics, recent changes |