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Every incident your team resolves makes CloudThinker smarter. Incident Memory automatically captures lessons from completed investigations and applies them when similar incidents occur in the future.

How It Works

1

Investigation Completes

When an RCA investigation identifies a root cause, CloudThinker automatically extracts key learnings — the problem, root cause, remediation steps, affected services, and confidence level.
2

Memory Stored

CloudThinker automatically stores these learnings for future use.
3

New Incident Occurs

When a new incident triggers an RCA investigation, CloudThinker searches for similar past incidents across your workspace.
4

Knowledge Applied

Relevant past investigations are provided to the AI agent as context, helping it focus on the most likely causes and skip dead ends.

What Gets Captured

Each completed investigation automatically saves:
InformationExample
Root Cause”Connection pool exhaustion due to leaked database connections”
Remediation StepsPrioritized actions the AI recommended
Affected ServicesServices involved in the incident
SeverityIncident severity level
ConfidenceHow certain the AI was about the root cause

Recall Indicator

When an investigation uses knowledge from past incidents, you’ll see a badge on the RCA results:
Informed by N similar incidents
This tells you the AI referenced prior investigations to guide its analysis. Hover over the badge for details.

When Memory Helps Most

Recurring Issues

Database connection problems, memory leaks, deployment regressions — patterns that repeat get diagnosed faster each time.

Similar Root Causes

A CPU spike in Service A caused by a config change? Next time a CPU spike hits Service B, the AI knows to check configurations first.

Team Knowledge Retention

When engineers leave or rotate, their debugging insights stay in the system.

Faster Resolution

Instead of starting from scratch, the AI begins with informed hypotheses based on what worked before.

How It Improves Over Time

Incident Memory gets smarter as your team uses CloudThinker:
  • Reinforcement — When the same root cause appears across multiple incidents, that pattern is strengthened and prioritized in future searches
  • Supersession — Re-investigating an incident replaces the old memory with updated findings, keeping knowledge current
  • Deduplication — Identical findings are automatically merged rather than duplicated

Configuration

Incident Memory is enabled by default when your workspace has the memory feature active. No additional setup is needed.
Incident Memory only captures learnings from RCA investigations that reach a conclusion (root cause identified, false alarm, or not found). Cancelled or failed investigations are not stored.

Best Practices

  • Provide detailed incident descriptions — richer context helps the AI find better matches from past incidents
  • Run RCA to completion — investigations that reach a disposition contribute the most useful memories
  • Connect your topology — incidents with mapped affected services produce more precise future matches
  • Re-investigate when needed — running a second RCA on the same incident updates the memory with better findings