Memories
Memories are reusable learnings drawn from past incidents. Once captured, they're recalled automatically when a relevant incident recurs, so a problem your team has seen before is resolved quickly rather than re-investigated from scratch. This directly lowers mean time to resolve (MTTR).
Memories are one of the ways Autoheal applies continuous learning.
How memories are captured
Memories are learned automatically; you don't write them. Autoheal derives them from real signals in your investigations:
- Accepted root causes. A confirmed diagnosis becomes reusable knowledge for similar incidents.
- Your guidance during investigations. Direction you give mid-investigation is carried forward.
- Hard-won discoveries. A non-obvious cause that took significant effort to find is worth keeping so the next occurrence is quick.
Your role is to review and approve what's captured, not to author it. To write reusable procedures yourself, use runbooks and skills in the Production Context Graph.
Memory lifecycle
Each memory moves through a set of states, and you stay in control of which ones are in use.
| State | Meaning |
|---|---|
| Pending | A candidate memory has been learned and is waiting for your review. |
| Applied | You approved it. The memory is now recalled and applied automatically in relevant future investigations. |
| Consolidated | You folded an applied memory into a runbook. It stays visible (marked as consolidated), and the runbook carries the knowledge forward. |
| Dismissed | You declined the memory. It won't be used. |
| Superseded | A newer memory replaced this one during deduplication, so the earlier version is archived automatically. |
Pending memories are the only ones that need your attention. Everything else has been approved, declined, or consolidated away.
Related
- Continuous Learning: how Autoheal learns and applies that learning
- Proactive actions: improvements surfaced to reduce MTTD or prevent incidents
- Production Context Graph: author and curate context yourself