Endpoint aiops

Endpoint AIops

Disclaimer: Community-maintained open-source project, not affiliated with, endorsed by, or sponsored by any endpoint-management vendor. Product and trademark names belong to their owners. Source at github.com/AIops-tools/Endpoint-AIops under the MIT license.

Governed managed-endpoint operations — 13 MCP tools, every one wrapped with the bundled @governed_tool harness: a local unified audit log under ~/.endpoint-aiops/, token/runaway budget guard, undo-token recording, and descriptive risk tiers. The management-server API key is stored encrypted (~/.endpoint-aiops/secrets.enc, Fernet + scrypt) — never plaintext on disk.

Standalone: the governance harness is bundled in the package (endpoint_aiops.governance) — endpoint-aiops has no external skill-family dependency. The test suite is mock-based; a live management server has not yet been exercised (see docs/VERIFICATION.md).

What This Skill Does

Category	Tools	Count	Read or Write
Overview	fleet health overview	1	1 read
Inventory	endpoint list, get, health score	3	3 read
Sessions	session list, login-storm analysis	2	2 read
Drift	drift report, patch status, patch compliance	3	3 read
Remediation	assign profile (high)	1	1 write
	reboot (medium)	1	1 write

The analysis tools (login_storm_analysis, drift_report, patch_status, patch_compliance, endpoint_health_score) accept injected records for pure/offline analysis; endpoint_health_score and patch_compliance are injected-only, the others also pull live from a configured target.

Quick Install

uv tool install endpoint-aiops
endpoint-aiops init       # interactive wizard: connection + encrypted API key
endpoint-aiops doctor

When to Use This Skill

• Triage a fleet (overview): online/offline counts, stale endpoints, agent/patch spread
• Rank the fleet by risk (endpoint_health_score): a composite 0-100 per-endpoint score, worst first, with every deduction cited
• Diagnose a morning login storm (session storm / login_storm_analysis) and find the slowest login/boot contributors
• Find endpoints drifted from the fleet baseline (drift report) or behind on patches (drift patch)
• Assign a config profile to an endpoint (reversible) or reboot one (dry-run + double-confirm)

Do NOT use when the target is OT/industrial equipment (use industrial-aiops), a hypervisor, a storage appliance, a backup product, a container cluster, or a network device.

Related Skills — Skill Routing

If the user wants…	Use
Managed-endpoint fleet: login storms, drift, profiles	endpoint-aiops (this skill)
OT / industrial edge (Modbus, OPC-UA, PLC, PROFINET)	the industrial-aiops line
Hypervisor VM lifecycle (power, snapshot, migrate)	a hypervisor ops skill
Container/cluster lifecycle	a cluster ops skill

Common Workflows

"Nobody can log in this morning" — diagnose the 9am login storm

1. endpoint-aiops overview → is this fleet-wide (offline/stale counts spiking) or confined to logins?
2. endpoint-aiops session storm --since-hours 12 --window-s 300 --min-concurrent 10 → storm episodes with peak concurrency and distinct users/endpoints, plus slowestByLogin / slowestByBoot
3. endpoint-aiops session list --since-hours 12 → inspect the raw sessions behind a suspicious episode (confirm the timestamps, don't trust the summary alone)
4. endpoint-aiops drift report → cross-check the laggards; a stray agent version or divergent profile is a common cause of slow logins
5. Failure branch: if session storm reports no episodes but users still complain, widen the window (--window-s 900) and lower --min-concurrent before concluding there is no storm; if the CLI errors on connectivity, run endpoint-aiops doctor first — the analysis is only as good as the session feed.

Bring a drifted endpoint back to the fleet baseline (reversible)

1. endpoint-aiops drift report → the drifted endpoints and exactly which fields deviate from the fleet-majority baseline
2. endpoint-aiops endpoint get <id> → confirm you are about to change the right device and note its current profile
3. endpoint-aiops endpoint assign-profile <id> <profile-id> --dry-run → preview the exact POST /endpoints/<id>/profile call, changes nothing
4. endpoint-aiops endpoint assign-profile <id> <profile-id> → double confirmation; high risk. The prior profile is captured and an inverse reassign undo descriptor is recorded
5. Failure branch: if the endpoint misbehaves on the new profile, endpoint-aiops undo list then endpoint-aiops undo apply <id> restores the captured prior profile (not a guess); re-run drift report to confirm the fleet picture.

Patch-compliance sweep before a maintenance window

1. endpoint-aiops drift patch --target-patch 2024-06 → distribution of patch levels plus the endpoints behind the target
2. endpoint-aiops endpoint list → resolve the behind-target ids to hostnames/owners for the change ticket
3. endpoint-aiops overview → check how many of those are currently offline (an offline endpoint will not take the patch)
4. Reboot a stuck endpoint that has staged its patch: endpoint-aiops endpoint reboot <id> --dry-run, then without --dry-run (double confirmation)
5. Failure branch: endpoint_reboot is medium risk and declares no undo — a reboot has no safe inverse. If the endpoint does not come back, the audit record in ~/.endpoint-aiops/audit.db holds its prior online state for the incident write-up; recovery is out-of-band (console/PXE), not via this tool.

Offline post-incident analysis (no live server)

1. Export the incident's session and endpoint records from the management server into JSON
2. Call the analysis tools with injected records — login_storm_analysis(sessions=[...]), drift_report(endpoints=[...]), patch_compliance(endpoints=[...]), endpoint_health_score(endpoints=[...]) — no connection or credentials required
3. endpoint_health_score returns a composite 0-100 per endpoint, worst first, with every deduction cited — use it to rank the remediation queue
4. Failure branch: if a tool rejects the injected records, the export is missing fields the analysis needs (e.g. session start/login-duration, or endpoint patch level) — re-export rather than hand-patching the data, so the numbers stay traceable to the source.

Governance & Safety

The skill delivers reads and writes and records them; it does not decide whether a write is permitted. That is your agent's judgement, or the permission of the account you connect it with (a management-console account or API token scoped to a read-only role — writes then fail at the server). There is no read-only switch, policy file, or approval gate.

• Audit is the guarantee, and it is not bypassable. Every operation — MCP and CLI alike — is logged to ~/.endpoint-aiops/audit.db (relocatable via ENDPOINT_AIOPS_HOME): params, result, status, duration, and the risk tier. The CLI writes the same row the MCP path does.
• ENDPOINT_AUDIT_APPROVED_BY / ENDPOINT_AUDIT_RATIONALE are optional annotations recorded on the audit row (who/why); they are never required and never block.
• Runaway guard — a safety backstop, not authorization: the same call looped in a tight window trips a circuit breaker. Disable with ENDPOINT_RUNAWAY_MAX=0.
• Writes support --dry-run / dry_run=True and double confirmation at the CLI.
• Reversible writes fetch the real before-state and record an inverse descriptor (endpoint_assign_profile→restore prior profile); the reboot (no safe inverse) records only the before-state.

References

• references/capabilities.md — full tool + field reference
• references/cli-reference.md — CLI command reference
• references/setup-guide.md — onboarding, credentials, and connectivity