Auto Healer: Runtime Remediation With Human Approval and Validated Recovery
Author: Ashwin Kondapalli, Founder & CTO, LoopIQ
Updated: October 8, 2026
It is 3:40 a.m. Error rates on the order service have tripled. The on-call engineer is paged, opens four dashboards, scrolls two log streams, and starts guessing: a deploy from yesterday? A dependency? A config drift? Forty minutes later they find a connection-pool setting that was changed in the last release. The fix takes two minutes. The diagnosis took the rest of the night—and the incident record says little about why the fix was safe.
Auto Healer is LoopIQ's autonomous remediation agent. It detects software and operational failures at runtime, diagnoses root cause, applies corrective action with human approval, and validates recovery. For critical security incidents, it can perform preemptive containment to limit impact before remediation begins.
Status: Auto Healer is live in LoopIQ's own development environment, where we are battle-testing it against LoopIQ's own infrastructure and codebases. Customer availability is expected in roughly two weeks (as of October 7, 2026). Pricing, deployment models, and supported cloud environments will be announced soon on loopiq.com.
This is the Auto Healer deep dive in a three-part series. Overview: Autonomous Implementation and Remediation: How LoopIQ Governs I2D and Auto Healer. Companion: Intent-to-Deploy (I2D).
What is Auto Healer?
Auto Healer is an autonomous remediation agent: it closes the loop from a runtime failure signal to a validated recovery, keeping a human approval in front of corrective action.
The lifecycle:
Detect — recognize a software or operational failure at runtime.
Diagnose — identify the likely root cause.
Approve — a human approves the proposed corrective action.
Remediate — apply the approved corrective action.
Validate — confirm recovery against the original failure signal.
For critical security incidents, a containment step can come before remediation to limit impact while diagnosis and approval proceed.
Why runtime remediation needs a human approval step
Runtime is where mistakes are most expensive. An autonomous agent that both diagnoses and changes live systems without approval has three problems:
Confidence is not correctness. A plausible diagnosis can still be wrong, and a wrong fix can widen an outage.
Accountability needs a person. Change governance, incident review, and audit all ask who decided. "The agent decided" is not an answer most organizations can defend.
Fixes carry side effects. Rolling back a config, restarting a service, or scaling a pool can affect other teams and customers.
Auto Healer keeps the fast parts autonomous—detection, diagnosis, preparing the fix, validating recovery—and puts an accountable human on the decision to apply corrective action. That is how autonomous remediation fits inside change and release governance instead of around it.
A practical method: detect, diagnose, approve, remediate, validate
Use this method for any remediation workflow, agent-driven or not.
Detect: define the failure signal precisely
Record the signal, threshold, affected service, and time window. A precise signal is what recovery will be validated against later. Vague detection ("things look slow") produces vague recovery claims.
Diagnose: connect the failure to a change or condition
Good diagnosis names a cause and the evidence for it: a recent change, a configuration drift, a dependency failure, a capacity condition. Where the failure traces to a recent change, link it to the originating work item and deployment record—this is where an I2D evidence trail pays off. For blockers surfacing before release rather than at runtime, Helix is the investigation path.
Approve: one named decision, with the evidence in front of the approver
The approver should see the signal, diagnosis, proposed action, expected effect, and rollback option. Approval is recorded with who, when, and what was approved.
Remediate: apply exactly what was approved
The corrective action should match the approval. If the plan changes, it goes back for approval.
Validate: recovery against the original signal
Recovery is confirmed when the original failure signal returns to its expected range for a defined window—not when the fix command succeeds. If validation fails, the incident stays open with an owner.
Record: turn the incident into evidence
The detect → diagnose → approve → remediate → validate chain becomes evidence for incident review and the next release decision. Follow-on work (a durable fix, a test that would have caught it) should become owned tasks—see From Evidence Gap to Remediation Story and Tasks.
What is preemptive containment for security incidents?
Preemptive containment is a narrow, impact-limiting action taken for a critical security incident before full remediation begins. Its purpose is to stop exposure from widening while root cause and the corrective fix are worked out.
Containment differs from remediation:
When: Containment: Critical security incidents, before remediation begins. Remediation: After diagnosis, for the root cause.
Goal: Containment: Limit impact and blast radius. Remediation: Fix the cause and restore normal operation.
Scope: Containment: Narrow and temporary by design. Remediation: Targeted at root cause.
Follow-up: Containment: Diagnose → approve → remediate → validate. Remediation: Validate recovery; record evidence.
Containment does not replace the approval path for remediation; it buys time for it. Security findings and the decisions made about them belong in release evidence—see Security Findings as Release Evidence: Freshness, Exceptions, and Decisions.
How this works in LoopIQ
LoopIQ connects delivery work, testing, AI agents, and operational signals so teams can assess release readiness, control changes, and preserve the evidence behind their decisions. Auto Healer adds autonomous runtime remediation to that model.
Prerequisites (expected at customer availability): a LoopIQ team context; operational signals connected for the services in scope; named approvers for corrective action; incident and change paths your organization already uses. Supported deployment models and cloud environments will be announced on loopiq.com—we are not listing them until they are published.
Sequence (conceptual):
Detect — Auto Healer detects a software or operational failure at runtime.
Contain (critical security incidents only) — Auto Healer can perform preemptive containment to limit impact.
Diagnose — Auto Healer identifies root cause, linking to related changes and work where available.
Approve — A human approves the corrective action.
Remediate — Auto Healer applies the approved action.
Validate — Auto Healer validates recovery.
Evidence — The record is available for incident review and release readiness, including the Release Compliance Dossier.
Approvals and outputs: Corrective action requires human approval. A validated recovery is operational evidence; it does not certify a release. Release certification in LoopIQ is an internal governance record for readiness and audit review—not regulatory certification. Agent actions should be auditable under the same principles as BYOA Governance: Permissions, Approvals, and Audit Trails.
Where we are: Auto Healer is live in LoopIQ's development environment, battle-tested on LoopIQ's own infrastructure and codebases. Customer availability is expected in roughly two weeks (as of October 7, 2026).
Pricing: Auto Healer pricing, deployment models, and supported clouds will be announced soon on loopiq.com. The LoopIQ platform is $4.99 per user per month (Analytics add-on separate).
Proof asset: illustrative remediation record
Label: Illustrative demo data. Not a customer incident; not a measured LoopIQ outcome. Timestamps are CT.
Incident A — operational failure (standard path)
03:40 · Detect (Auto Healer): order-service 5xx rate above threshold for 5 min
03:43 · Diagnose (Auto Healer): DB connection-pool max reduced in last deploy (linked to change ORD-77)
03:45 · Propose (Auto Healer): Restore pool max to prior value; rollback option recorded
03:52 · Approve (On-call lead): Approved restore; reason noted
03:53 · Remediate (Auto Healer): Applied approved config value
04:08 · Validate (Auto Healer): 5xx rate back within expected range for 15 min
09:30 · Follow-up (Service owner): Task: add pool-size check to release validation
Incident B — critical security incident (containment first)
14:02 · Detect (Auto Healer): Anomalous access pattern on exposed admin endpoint
14:03 · Contain (Auto Healer): Preemptive containment: endpoint access restricted to limit impact
14:10 · Diagnose (Auto Healer): Misconfigured route exposing endpoint (linked change recorded)
14:18 · Approve (Security lead): Approved route correction
14:20 · Remediate (Auto Healer): Applied approved route fix
14:40 · Validate (Auto Healer): Endpoint no longer reachable externally; access pattern normal
Next day · Evidence (Security / release): Finding, containment, and decision recorded for release review
In both cases a person approved the corrective change, and recovery was validated against the signal that started the incident.
What Auto Healer is not
Not generally available today. Live in LoopIQ's own development environment; customer availability expected in roughly two weeks.
Not unsupervised production change. Corrective action is applied with human approval.
Not a reason to skip root-cause follow-up. A validated recovery still deserves owned follow-on work.
Not release authorization or regulatory certification. Recovery evidence informs decisions; release certification is not regulatory certification.
Not incident-free or maintenance-free operations. Autonomous remediation shortens the loop; it does not guarantee outcomes.
Not priced in this post. Pricing, deployment models, and supported clouds will be announced on loopiq.com.
FAQ: quick answers
What is an autonomous remediation agent?
An agent that detects runtime failures, diagnoses root cause, applies corrective action, and validates recovery. LoopIQ's Auto Healer applies corrective action with human approval.
Does Auto Healer fix production without approval?
No. Corrective action requires human approval. For critical security incidents, it can perform preemptive containment to limit impact before remediation begins.
What is the difference between containment and remediation?
Containment limits impact during a critical security incident; remediation fixes the root cause. Containment comes first when needed; remediation follows the approval path.
How does Auto Healer validate recovery?
By confirming the original failure signal returns to its expected range—not just that the fix was applied.
When can customers use Auto Healer?
Customer availability is expected in roughly two weeks (as of October 7, 2026). It is live today in LoopIQ's own development environment.
See governed runtime remediation
CTA: See runtime remediation with human approval in LoopIQ.
Book a time: https://meet.brevo.com/ashwin-kondapalli
Further reading: Series overview: I2D + Auto Healer · I2D deep dive · Security Findings as Release Evidence · Helix and Release Blockers · Evidence Gap to Remediation Story · BYOA Governance · LoopIQ on LinkedIn
General information for engineering, SRE, security, and compliance leaders. Not legal, audit, or regulatory advice. Product status as of October 7, 2026.