Production Debugging with Full Context
Stop context-switching between four tools to figure out what broke.
The context-switching problem
A production incident rarely announces its cause. An engineer typically starts from a single alert or a vague symptom — elevated error rate, a slow endpoint, a spike in support tickets — and has to reconstruct what happened across separate tools: a log viewer, a tracing tool, an error tracker, a session-replay tool, and a deploy history, none of which share context with each other. The investigation time isn't spent understanding the incident; it's spent finding and assembling the evidence to understand it.
What "full context" actually means
Modulis correlates the signals around a production issue into one investigation, automatically, instead of leaving that correlation to the engineer:
Logs
Application and system-level events and error output.
Traces
The full request path across every service it touched.
Errors
Exception details, stack traces, and error frequency.
Session context
What the affected user was doing when it broke.
Git & deployment context
What changed recently, and by whom.
From alert to root cause
Once those signals are correlated, AI-assisted analysis reviews them alongside recent Git and deployment history to propose a root cause and a PR-ready fix — which the engineer reviews before it ships. The result is that the investigation starts from a working hypothesis instead of a blank dashboard.
Where this runs
Modulis deploys inside your own cloud account (BYOC), so the telemetry it correlates — and, with your own model key (BYOK), the AI analysis of it — never leaves infrastructure you control. Full context doesn't have to mean sending more of your data to a third party.
Related reading
See full-context debugging on your own stack
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