Synthesis
AuraScore 87/100

Distributed Incident Root Cause and Telemetry Synthesis

Synthesize multi-service telemetry, timelines, and crash logs into a comprehensive distributed system incident post-mortem analysis.

Use this template following major production outages or multi-service degradations. It helps SREs and architects synthesize fragmented log streams, traces, and metrics into a unified post-mortem and structural hardening plan.

Template

Role: Principal Site Reliability Engineer with fifteen years of experience analyzing complex distributed system failures and cascading outages.

Context

  • Incident Timeline: {{incident_timeline}}
  • Aggregated Telemetry Logs: {{service_telemetry_logs}}
  • Impacted Subsystems: {{impacted_subsystems}}
  • Live Remediation Actions: {{remediation_actions_taken}}
  • SLA and Performance Metrics: {{sla_breach_metrics}}
  • Suspected Contributing Factors: {{contributing_factors}}

Task

Synthesize raw telemetry logs, incident timelines, and multi-service traces into an exhaustive post-incident root cause analysis to identify underlying systemic triggers, blast radius dynamics, and structural architectural vulnerabilities.

Method

  1. Normalize disparate timestamps across {{service_telemetry_logs}} and {{incident_timeline}} to reconstruct the precise sequence of distributed state transitions.
  2. Map cross-service dependency chains across {{impacted_subsystems}} to trace the propagation path of initial upstream faults.
  3. Correlate traffic spikes and resource starvation markers with {{sla_breach_metrics}} to pinpoint latency degradation thresholds.
  4. Dissect {{contributing_factors}} to differentiate immediate triggers from latent architectural defects like missing backpressure or circuit breakers.
  5. Evaluate the efficacy and latency of {{remediation_actions_taken}} during the live incident window.
  6. Synthesize failure patterns into systemic categories including concurrency deadlocks, network partitions, and resource exhaustion.
  7. Formulate high-leverage defensive hardening recommendations spanning code changes, observability gaps, and topology adjustments.

Constraints

  • MUST correlate all findings directly with concrete log events or metrics provided in {{service_telemetry_logs}}.
  • MUST distinguish clearly between primary root causes, secondary triggers, and aggravating environmental conditions.
  • MUST NOT suggest superficial hotfixes without addressing underlying system architecture resilience.
  • Limit technical jargon to standard distributed systems terminology.
  • Ensure all remediation proposals map directly to identified failure modes.

Output format

  1. Executive Incident Overview (150-200 words summarizing trigger, duration, and blast radius)
  2. Chronological Failure Propagation Vector (table format: Timestamp, Subsystem, State Change, Cascading Impact)
  3. Systemic Root Cause Synthesis (3 distinct subsections: Primary Mechanism, Latent System Flaws, Blast Radius Analysis)
  4. Actionable Architectural Hardening Matrix (prioritized list with Owner, Severity, and Verification Method)

Self-review

  • Did I verify that every failure step maps to an entry in {{service_telemetry_logs}}?
  • Are primary root causes clearly demarcated from compounding symptoms?
  • Are the hardening recommendations targeted at architectural resilience rather than just temporary patches?
AuraScore breakdown
87/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification14/14 · Strong

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

research-analysis
research-synthesis
software-engineering-debugging
sre
post-mortem
distributed-systems