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Do not treat an AI-generated root cause as proof. Treat it as a hypothesis, stop any consequential automated change, and verify the claim against independent network evidence. The reliability of the diagnosis depends on the agent’s time window, telemetry, resource access, permissions, and ability to observe the complete path between the affected endpoints.
This process helps answer the operational questions that matter during an outage: Why is the network down? Is this a DNS issue, firewall rule, or route problem? What evidence did the agent use? Can a proposed network change be rolled back safely?
1. Pause risky automation and preserve the incident window
If the recommendation would alter production routing, firewall policy, security-group rules, access controls, DNS, or workload state, pause execution while you verify the diagnosis. Preserve the telemetry and configuration state that describe the failure. Follow your incident commander and change-control procedure; the exact mechanism for pausing an agent differs by product and organization.
Do not disable useful observation merely because you have stopped remediation. Keep collecting logs, metrics, traces, flow records, route state, VPN or private-link health, and configuration-change history. Record the time at which the agent produced its recommendation and the incident interval it claims to have analyzed. A diagnosis that examines 10 minutes after the outage began may miss the event that caused it.
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Microsoft’s incident-response guidance recommends starting with a Review autonomy level, so an operator can inspect a proposed action before it runs. AWS guidance similarly calls for explicit human approval for specified production transit-gateway route and Direct Connect changes. Security-group or firewall changes should include a recommendation and a rollback command rather than being applied without review.
2. Make the agent show its work
Ask for an evidence-oriented investigation, not a more confident paragraph. Require the agent to answer each question below and preserve the response in the incident record.
- Which source and destination endpoints, regions, accounts, subscriptions, services, and protocols were investigated?
- What exact start and end times were used, including the time zone?
- Which logs, metrics, traces, flow records, resource APIs, configuration histories, and runbooks were consulted?
- What observation directly supports the proposed root cause?
- Which data sources were unavailable, denied by permissions, empty, delayed, or not queried?
- Which competing explanations were tested, and what result would have falsified the leading explanation?
- What is the smallest reversible action being recommended, and what is the rollback procedure?
Microsoft’s SRE Agent investigation guidance describes results that include a root cause, supporting evidence, a recommended fix, and a checkpoint identifying the sources already used or the next source needed. Its deeper investigation workflow creates multiple hypotheses, tests them iteratively, and records invalid hypotheses. If an agent cannot provide equivalent detail, downgrade its answer to an unverified lead.
3. Determine whether the investigation is complete
Compare the claimed evidence with the incident timeline and the raw systems that produced it. Check whether every affected component was visible to the agent and whether its role could read the relevant subscription, account, region, cluster, virtual network, gateway, firewall, and workload data. A successful API call to one resource does not prove that the agent could inspect the entire traffic path.
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Look for gaps such as missing flow logs, a metrics outage during the event, delayed log ingestion, a connector that could not reach a private endpoint, or a policy that blocked the agent from querying a critical system. Microsoft documents the limitation plainly: If a critical data source is unreachable, the investigation is incomplete, and the agent reports this condition.
An answer based on partial visibility is not a confirmed root cause.
Also interpret an agent’s network audit narrowly. Azure SRE Agent documentation says its network audit covers the agent’s egress-policy decisions; it does not represent every runtime, connector, platform, firewall, DNS, proxy, or service event. Treat an apparently clean audit as evidence about that audit’s scope, not as proof that the production path was healthy.
Use a completeness record
| Item | What to record | Why it matters |
|---|---|---|
| Incident window | Start, end, time zone, and any known clock skew | Prevents evidence from a different period being treated as causal |
| Path | Source, destination, protocol, port, DNS name, region, and intermediary hops | Defines what must actually be tested |
| Agent access | Roles, subscriptions or accounts, reachable APIs, and denied requests | Shows whether the agent could see the relevant components |
| Data freshness | Ingestion delay, retention, sampling, and missing intervals | Separates absence of evidence from evidence of absence |
| Alternatives | Hypotheses considered, tests run, and results | Reduces premature commitment to one explanation |
4. Reproduce the symptom with an independent test
Use a diagnostic method that does not depend on the agent’s reasoning or the same unverified data interpretation. Azure Network Watcher Connection troubleshoot can test TCP or ICMP reachability and report reachability status, latency, hops, failed probes, and configuration problems. Depending on the path, it can identify DNS resolution failures, missing or misconfigured routes, network-security-group restrictions, guest-firewall blocks, socket errors, and a destination service that is not listening on the requested port.
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Make the independent test match the failure
- Use the same source identity or network location that experienced the outage. A test from an administrator’s workstation may take a different route and bypass the failing control.
- Use the same destination name, resolved address, protocol, and port. Testing ICMP does not establish that a TCP application port is reachable.
- Run the test during the affected interval when possible, or compare current output with retained evidence from that interval.
- Capture the complete result, including hops, latency, probe failures, DNS answers, route selections, and policy findings.
- Repeat from the opposite direction or from a second approved vantage point when asymmetric routing is possible.
A test that succeeds now does not disprove a failure that ended earlier. It tells you that the path is currently functioning; correlate it with historical telemetry and configuration changes.
5. Test the actual path, not just the named symptom
A symptom rarely identifies a unique cause. AWS network-operations guidance uses a TCP timeout as an example: the same timeout can result from a missing transit-gateway return route, VPN instability, a network ACL gap, or a firewall rule. The correct response is to inspect the path and the time interval, not to accept the agent’s most fluent explanation.
For a timeout or connection refusal, check these layers
| Layer | Verification questions | Evidence that narrows the cause |
|---|---|---|
| Name resolution | Did the name resolve? To which addresses? Were answers consistent across resolvers? | Resolver logs, authoritative responses, client-side resolution, and split-horizon configuration |
| Forward route | Did the source have a route to the selected destination address? | Effective routes, route-table changes, next-hop health, and hop-by-hop probes |
| Return route | Could replies return through the expected gateway, VPN, or transit device? | Reverse-path route inspection, asymmetric-flow records, and gateway state |
| Policy controls | Did an ACL, security group, network-security group, or firewall allow the protocol and port? | Effective rules, deny logs, policy versions, and change history |
| Tunnel or private connection | Was the VPN, Direct Connect, peering, or private endpoint established and stable? | Tunnel state, negotiation events, packet loss, BGP status, and provider alarms |
| Destination host | Was the host healthy and listening on the requested port? | Service status, socket/listener data, host firewall logs, and application health checks |
Use correlated signals rather than the agent’s confidence wording. For example, a firewall deny at the same minute as failed probes supports a policy hypothesis; a healthy policy combined with a missing return route points elsewhere. A route change recorded after the first failures cannot explain their onset unless clocks or event ordering show otherwise.
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6. Compare the agent’s conclusion against competing hypotheses
Place the agent’s claim beside at least one plausible alternative. This prevents confirmation bias when the proposed fix sounds familiar.
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- Evidence coverage: Did the conclusion use raw logs and configuration state, or only a high-level alert?
- Path coverage: Does it include DNS, the selected address, protocol, port, forward route, return route, and destination listener?
- Independence: Did a separate probe or data source reproduce the observation?
- Uncertainty: Are missing sources, permission limits, sampling, and unresolved hypotheses explicit?
- Scope: Does the diagnostic support this resource type, region, and product version? Is any feature still preview?
- Risk: Would the recommended action affect production, and can it be reversed quickly?
Ask the agent to state what would falsify its leading explanation. If it cannot name a disconfirming observation, it is producing a narrative rather than a testable diagnosis.
7. Mitigate only after a fault is supported
Choose the smallest bounded change that addresses the first confirmed fault. Before changing anything, capture the effective route or policy, save the relevant configuration version, define the rollback action, and identify the human approver. Ensure the person approving the change understands its blast radius and the verification criterion.
For a route or Direct Connect change, obtain the explicit production approval required by your organization and provider guidance. For a security-group or firewall recommendation, require both the proposed rule and a tested rollback command. Do not accept an instruction to remove broad controls permanently when a narrowly scoped, time-limited exception can test the hypothesis.
Verify after the change
- Repeat the same source-to-destination test with the same protocol and port.
- Confirm that the expected route, policy decision, or tunnel state changed and that unrelated paths did not.
- Check application-level success, not just ping or a transport handshake.
- Watch error rate, latency, retransmits, and dependent services for a defined observation period.
- If the fault is not corrected or the blast radius grows, execute the rollback and return to hypothesis testing.
8. Close the loop and improve the next investigation
Maintain a concise audit trail. Record the original agent output, the incident window, every data source consulted, inaccessible sources, independent test results, hypotheses confirmed or ruled out, the approving person, the pre-change state, the rollback plan, and the post-change result. This record is useful even when the agent was correct because it shows why the change was safe.
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After service is stable, identify why the misdiagnosis occurred. Was a permission missing? Did the agent lack flow logs, route history, or a private-endpoint connector? Was the test run from the wrong vantage point? Did a preview diagnostic omit a needed resource type? Correct the underlying coverage or instruction, then validate the improvement against the facts of this incident.
AWS recommends structured, version-controlled diagnostic procedures, explicit investigation layers, and an instruction to stop at the first confirmed fault. Treat those as vendor recommendations to adapt to your approved runbooks, not as a guarantee that any agent will diagnose accurately. Keep human review for consequential actions until your own evidence demonstrates that a narrower autonomy level is safe.
Practical incident checklist
- Pause unapproved route, firewall, DNS, access-control, and workload changes.
- Preserve logs, metrics, traces, flow records, effective configuration, and change history.
- Write down the source, destination, protocol, port, regions, and exact incident window.
- Request the agent’s evidence, data sources, missing sources, alternatives, and falsification test.
- Check permissions, connector reachability, ingestion delays, retention, and preview-feature scope.
- Run an independent connectivity test and capture its full output.
- Inspect DNS, forward and return routes, tunnels, ACLs, security groups, firewalls, and the destination listener.
- Compare at least one competing hypothesis with correlated time-stamped evidence.
- Obtain human approval, record pre-change state, and prepare a rollback before mitigation.
- Repeat the end-to-end test after the change and document the result.
Bottom line
An AI network agent can accelerate investigation, but its diagnosis is only as strong as the evidence and access behind it. Require a transparent evidence trail, prove the complete path with an independent test, and keep production changes reversible and human-approved until the named fault is confirmed.
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