01
Scope the investigation
Identify the affected service, parse the alert context, and determine which data sources are relevant, metrics, logs, traces, deployment history, configuration changes, related tickets, and runbooks.
Incident Investigation
From alert to evidence-backed root cause in minutes
Hyground investigates incidents the moment they fire, pulling logs, metrics, traces, recent deployments, configuration changes, and prior incident patterns in parallel, and returns structured findings with a likely cause, affected services, supporting evidence, and recommended next actions.
The same incident. A different experience.
Good incident response is fast, evidence-driven, documented, and not dependent on one person knowing where to look. Hyground makes that the default.
How Automated Investigation Works
When an alert fires, Hyground begins investigating immediately. It follows a structured reasoning process across all connected data sources, logs, metrics, traces, changes, tickets, documentation, and prior incident patterns, simultaneously.
02
Collect evidence in parallel
Hyground queries logs, metrics, traces, recent changes, open tickets, and prior incident patterns simultaneously, building a cross-stack evidence set, not checking sources one by one.
03
Correlate and reason
A spike in errors starting at 14:32. A deployment at 14:28. A similar pattern from an incident three months ago. Hyground connects findings across sources and identifies the most likely cause.
04
Return structured findings
Delivers a likely root cause, affected services, supporting evidence, and recommended next actions. Every query executed, every finding collected, and every reasoning step is visible and auditable.
Real Investigation Scenarios
Every scenario below represents an actual pattern Hyground investigates, from the 3am page to the silent failure nobody caught.
The 3am Database Slowdown
Checkout latency spikes across all regions. Hyground pulls logs, query metrics, and deployment history, traces the cause to a new database query introduced in the payment-service deployment three hours earlier. Evidence and rollback recommendation delivered before the on-call engineer finishes reading the alert.
3 min
to evidence-backed root cause
The Mystery Memory Leak
A service is consuming memory at twice its normal rate. Hyground collects memory metrics, correlates the growth curve against recent deploys, config changes, and traffic patterns, identifies the commit that changed the connection pool size and returns the evidence chain.
< 10 min
from alert to diagnosis
The Config Change That Wasn't
Three services go red within 90 seconds of each other on a Tuesday afternoon. Hyground investigates across all three service boundaries, collects change logs, and identifies that all three share a feature flag that was silently flipped during a routine release.
1 session
spans all three services
The On-Call Handover
Engineer finishing a shift shares their open Hyground session with the incoming team. The handover is not a set of notes, it is a live investigation with collected evidence and reasoning that the next engineer continues from exactly where it was left.
0 context lost
across shifts
Want to go deeper?
The building blocks behind every investigation
Skills and scheduling let you codify how your best responders work, and run that work the moment an alert fires.
Skills
Define repeatable investigation playbooks that any engineer can execute with a single prompt, codifying how your best responders work.
Scheduling & Triggers
Auto-trigger investigations from PagerDuty alerts, or schedule nightly pre-checks that catch problems before they become incidents.
See it investigate your own infrastructure
Book a demo and we'll run an actual incident investigation against your stack. Prometheus, Loki, Datadog, or whatever you run.
See Hyground in action
Check out our sandbox or schedule a demo with our team and experience sovereign AI for DevOps firsthand.