Diagnosing Root Cause Across Services, Infrastructure, and Recent Change
A platform team's mean time to diagnosis is dominated by the search for what changed, across deployments, configuration, and infrastructure.
Run on Sutradhar · IT Operations Automation
The challenge
Change data lives in deployment pipelines, configuration systems, and cloud audit logs that are never correlated.
Engineers reconstruct a timeline by hand under incident pressure.
The same class of incident is re-diagnosed from scratch each time it recurs.
How Sutradhar solves it
Timeline Reconstruction
Deployments, configuration changes, infrastructure events, and alerts are assembled into one ordered timeline automatically.
Change Correlation
Changes are correlated against the onset of symptoms to produce ranked candidate causes.
Hypothesis Testing
Candidate causes are tested against available telemetry rather than presented as a list to read.
Prior Incident Matching
Similar past incidents and their resolutions are surfaced alongside the current diagnosis.
Diagnosis Handover
The engineer receives a reasoned diagnosis with its supporting evidence, not a dashboard.
The outcome
Incident timelines assembled automatically rather than reconstructed under pressure.
Candidate causes ranked and tested rather than listed.
Recurring incident classes resolved against prior diagnosis instead of from scratch.
Representative scenario: a modelled industry situation showing how this accelerator applies. Figures are projections, not a named client result.
Capabilities used
Every accelerator is assembled from the same capability layer, so a workflow you adopt here shares its foundation with the rest of the portfolio.
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Bring us the version of this that you actually have.
Every engagement is fixed-scope and outcome-guaranteed. The scoping conversation starts with your systems, not with a template.