Evidence collection
Bring relevant logs, metrics, deployment events, and runbook context into one investigation view.
CloudLink solution
Assisted Incident Diagnostics
Use automation to organize evidence while engineers make decisions.
The operational problem
During an incident, useful evidence is spread across logs, metrics, deploy history, and team knowledge, slowing the formation of a testable hypothesis.
How CloudLink approaches it
CloudLink can use automation to summarize and correlate authorized operational data. Engineers review the output, verify evidence, and retain control over any production change.
What the engagement can cover
Hypothesis support
Organize possible causes and the evidence that supports or contradicts each one.
Human review
Require an engineer to review suggested next steps before production action.
Knowledge capture
Turn verified incident learning into runbooks and follow-up work.
A clear delivery path
Agree which data sources may be used.
Gather relevant operational evidence.
Engineers test hypotheses against the systems and data.
Capture verified findings and next steps.
Questions before you start
Does automation make production changes?
Production changes require human review and the authority agreed with your team.
Which data is needed?
The source set depends on the incident and may include authorized logs, metrics, deployment metadata, and runbooks.
Is generated output treated as fact?
No. Generated summaries and hypotheses must be checked against source evidence by an engineer.
Discuss Assisted Incident Diagnostics
Share your environment, priorities, and decision timeline.
Contact CloudLinkEvidence-led reviewScope confirmed firstTechnical next steps
Scope confirmed in writing Clear project boundaries Recommendations tied to evidence