Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The frequent locking of user jsmith's Active Directory account might be due to an incorrect or outdated password being cached on the user's system, or due to a service or application using a cached old password. Ensure that the user's password is being re-used across applications and services, which could lead to inconsistent authentication states causing lockouts. Implement or ensure consistent password policies are in place across all systems the user interacts with, including Windows, Outlook, Teams, and the shared network drive, enforcing that passwords are never reused. Use tools like the Microsoft Account Lockout Status tool to monitor and adjust lockout policies, ensuring they align with acceptable lockout thresholds. Check if any services or applications are using cached old passwords, and configure them to adhere to the active authentication state for better security and consistency. Ensure that the Windows Event Log is being reviewed for the correct lockout status of user jsmith, and that bad password attempts are counted correctly and the lockout policy is set appropriately to avoid an overly aggressive lockout mechanism that is causing frequent lockouts. Escalate support if the behavior persists or if suspicious activity is detected beyond simple lockout frequency issues.", "cited_artifacts": ["KB-00008"], "confidence": 0.6, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The recurring account lockout for user jsmith could be due to a combination of password policies and Kerberos clock skew. Password policies configured in Active Directory (like password complexity, lockout duration, and lockout threshold) enforce account locking when certain criteria are met, such as consecutive unsuccessful login attempts. Since jsmith’s account gets locked every 10-15 minutes, it’s possible that the password lockout duration in the AD policy is too short. Additionally, checking if the Kerberos clock skew is causing the account lockout is essential. Kerberos timestamp synchronization problems between domain controllers could lead to account lockouts. Ensure the Kerberos time synchronization between domain controllers is maintained and check the event logs for any related error codes. Escalation is not necessary as the context provided can resolve the primary issue of AD account lockout frequency issues.", "cited_artifacts": ["KB-00008"], "confidence": 0.6, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The frequent account lockout of user jsmith could be due to an expired password, account lockout threshold, or password caching on devices. Passwords in AD must expire regularly, typically every 90 days, as per Security Policy. Ensure that the account lockout threshold is set correctly, ideally higher than the frequency of lockouts, e.g., 30 attempts before locking an account, and lockout duration, such as a maximum of 10 minutes. Also, check if the account lockout counter is reset for user jsmith, possibly by event logs showing password expires or by diagnostic tools like 'LockoutStatus.exe' to identify misconfiguration or malicious password caching by systems or applications. Verify the group policies to ensure appropriate lockout settings and check for local user account configurations that might be overly restrictive in lockout settings. Escalate if the ticket remains unresolved, indicating potential misconfiguration of AD settings or broader system configurations affecting account lockout policies.", "cited_artifacts": ["KB-00001", "KB-00008"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "User jsmith's AD account keeps getting locked due to frequent password changes and insecure configuration settings. Users are required to change their passwords every 90 days, and if done improperly, they can lock out their accounts. The account should be unlocked using the command `Unlock-ADAccount -Identity <username>` in the AD cmdlet. However, jsmith's frequent password changes may be causing the account to lock. To prevent this, users should be instructed to set up a longer password policy, set up a password policy lockout threshold to prevent the account from locking too frequently, and ensure consistent password reuse. Escalate to technical support if the account continues to lock out as the issue may require further investigation such as checking for service principal name dependencies or Kerberos settings.", "cited_artifacts": ["KB-00008"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "User jsmith is experiencing repeated account lockouts due to frequent bad password attempts by the account lockout policy set by AD. The account lockout status can be checked using the PowerShell command `Get-ADUser <username> -Properties LockedOut,BadLogonCount,LastBadPasswordAttempt` to identify if the account is locked and how many attempts have led to the lockout. If the account is locked, it can be unlocked with `Unlock-ADAccount -Identity <username>`, and the bad logon count can be reset with `Set-ADAccountPassword -Identity <username> -Reset` to clear all bad password attempts and re-enable the account. Ensure that the account lockout policies are correctly configured, and the lockout duration and threshold for bad password attempts are set appropriately to avoid unintended lockouts. Escalate if the ticket persists despite correct policy settings or if the issue is related to factors other than lockout policy, such as network misconfiguration or service account password issues, which might require an escalated support case based on the actual symptoms detailed in the provided KB articles.", "cited_artifacts": ["KB-00008"], "confidence": 0.6, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The account lockout issue for user jsmith could be due to the account being locked out due to consecutive failed logon attempts (BadLogonCount) and it being locked out after the lockout duration configured in the domain's security policy. The lockout duration can be adjusted in the Active Directory Users and Computers or via PowerShell with the 'Set-ADDefaultDomainPasswordPolicy' cmdlet to prevent frequent lockouts. Additionally, ensure that there are no applications or services that are improperly handling password caching and causing the account to lock out, as this could be due to an application using a cached old password. Check for cached credentials, lockout thresholds, and ensure that the account lockout policies are correctly configured to allow for automatic unlock attempts or manually via the 'Unlock-ADAccount' cmdlet in PowerShell after checking the specific reasons for the lockout through the Event Log and other AD tools. Escalate this ticket only if the account lockout is consistently occurring despite these policies and adjustments.", "cited_artifacts": ["KB-00008"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The CrashLoopBackOff issue in the orders-service and connection pool exhaustion in the fulfillment-service could be due to the Kubernetes pod's configuration causing resource limits to be hit too often. The crash loop may be caused by insufficient memory limits set in the pod specification, leading to OOMKilled events, which Kubernetes tries to restart the pod. Ensure the `resources.limits.memory` is appropriately set and the `limits.cpu` is reasonable for the workload. Additionally, check that there are no memory leaks within the application, as this could lead to repeated crashes. For the database connection issues, ensure that the connection pool exhaustion is not a result of insufficient pool size configured for the driver. The Prometheus metric `hikaricp_connections_max` should be properly configured to allow enough active connections based on the number of expected concurrent connections from services like fulfillment-service. Escalation might be necessary if this fails, as the pod spec could be misconfigured, the liveness and readiness probes are incorrectly set, or there’s an actual issue with the Kubernetes scheduler or resource management that isn’t evident from pod metrics alone. Escalate=true should be avoided if there’s a clear misconfiguration or the environment isn’t managed by Kubernetes, such as a non-Kubernetes deployment or self-contained application in Docker. Escalate=false would indicate the ticket is well-suited to resolve with the given information.", "cited_artifacts": ["KB-00001", "KB-00016", "KB-00017"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The CrashLoopBackOff and database connection errors in the orders-service and fulfillment-service might be due to an improperly configured resource limits in the Kubernetes deployment YAML file, leading to pods being killed by the kubelet for resource exhaustion, even when the pods exit correctly after an initial run. The configmap or secrets referenced in the deployment YAML might also be missing, causing the services to fail during startup. Additionally, the application’s liveness and readiness probes might be set to timeout too quickly, leading to pod restarts, even when the pod is ready to handle traffic. The orders-service and fulfillment-service both need their resource limits and image pull secrets properly specified in their Kubernetes deployment YAML files to ensure they don’t crash due to resource limitations or missing dependencies. Escalate to the team responsible for the deployment YAML if they need further assistance with configuration settings, or validate the Kubernetes manifests for resource limits and secret references.", "cited_artifacts": ["KB-00017"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The CrashLoopBackOff in orders-service and connection pool exhaustion in fulfillment-service could be due to resource constraints such as insufficient memory for containers, which results in containers being killed immediately by the orchestrator before they have a chance to reach a stable state. This can be checked by ensuring that the resource requests and limits specified in the Kubernetes Pod specification match the actual resource usage and that the machine the pods are running on has the required resources. In cases of OOMKilled, increasing the resource limits or resolving memory leaks can resolve the issue. Additionally, if missing secrets or bad config are causing issues, Kubernetes events can indicate these and should be corrected by ensuring the correct Secrets and ConfigMaps are present and correctly referenced in the Pod specification. Escalation to a dedicated operations team is not indicated based on the provided context as Kubernetes resource misconfiguration can often be resolved internally, but a detailed investigation into service and machine-level configurations and logs is recommended.", "cited_artifacts": ["KB-00017"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The CrashLoopBackOff in the orders-service pods could be due to an incorrect limit specified in the service’s resource requests and limits in the Kubernetes deployment YAML, leading to the container running out of memory and crashing. Ensure that the specified resource limits in the deployment YAML are correct and that the memory limit is set appropriately without causing the pod to crash due to OOMKilled (Out of Memory Killed). Check the events and logs in the pod to identify the root cause. Ensure the LivenessProbe is correctly set to avoid false positives that could prevent the application from restarting properly. Also, ensure the database connection pool exhaustion in the fulfillment-service is correctly configured to handle the traffic. It could be that the connection pool in the database service is exhausted due to too many long-running queries or unclosed ResultSets, which can be identified by checking the database side metrics and thread dumps, and configuring the connection pool size appropriately. Escalate to DBA or DevOps if the issue persists despite correct configuration, as the application and service layers may be interacting with the database in ways not expected in the microservices architecture setup. Escalate if the CrashLoopBackOff continues as the application is repeatedly failing to start up, possibly due to misconfigured resources or health checks within the deployment manifest, Kubernetes manifest files.", "cited_artifacts": ["KB-00001", "KB-00016", "KB-00017"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The CrashLoopBackOff in orders-service pods and the connection pool timeouts in fulfillment-service are likely due to either configuration mismatch with the underlying Kubernetes service account permissions or improper resource limits. In Kubernetes, if the service account used by the pods lacks the necessary permissions to access the database or other required resources, it can result in Pods restarting indefinitely in a CrashLoopBackOff state. Similarly, resource limits might not be set correctly for the containers, leading to exhaustion of system resources such as CPU or memory, causing the service to time out and restart. Check the service account's RBAC permissions in the orders-service deployment to ensure it has the necessary roles to connect to the database. Additionally, adjust the resource requests and limits defined in the deployment YAML of orders-service to match the available resources. Ensure the service account has the appropriate roles such as db-sqladmin, service-apiserver, and node-agent to access the database and other services. Escalate to a devops engineer if the pods continue to crash even after adjusting the service account permissions and resource limits in the YAML deployment manifest.", "cited_artifacts": ["KB-00001", "KB-00016", "KB-00017"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The crash loop backoff issues in the orders-service pods could be due to resource limitations, incorrect pod configuration, or misconfigured liveness probes. For resource limitations, the memory limits specified in the pod's YAML definition might be insufficient for the application to run without crashing. For incorrect configuration, lack of necessary secrets or ConfigMap references can cause the pod to crash since they are referenced within the container’s environment. Misconfigured liveness probes can fail repeatedly due to short or overly aggressive interval checks, leading the Kubernetes controller to automatically restart the pod. Escalate the issue if the orders-service and fulfillment-service still have connection errors, indicating a problem with the database or network configuration, or if resource limits are the primary cause of crashes, which can be identified by reviewing the application logs for OOMKilled errors or other runtime failures. Escalate=false."}, "cited_artifacts": ["KB-00016", "KB-00017"], "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The CrashLoopBackOff issue with the orders-service pods and the connection pool exhaustion in the fulfillment-service could be related to either configuration issues in Kubernetes or resource limits set too low. For CrashLoopBackOff, the Kubernetes API endpoint events need to be closely examined to identify the root cause, such as memory leaks, improper resource limits set for the containers, or misconfigured liveness/readiness probes which lead to restarts. For connection pool exhaustion, the connection metrics in the Prometheus/Grafana dashboard should be monitored to check if the number of active connections is hitting the maximum set in the application’s pool configuration (e.g., maxTotal connections in HikariCP). Escalate to Operations if there are no clear Kubernetes or application configuration issues as these services are not showing signs of poor connectivity to the databases from the context provided, and ensuring that the volumes used by the services in Kubernetes are mounted correctly and are bound to the expected DB server addresses and ports. Escalate to escalation if the pods are still crashing and scaling out does not help, or if the logs indicate persistent errors or misconfigurations in the application settings that prevent normal operations.", "cited_artifacts": ["KB-00016", "KB-00017"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The CrashLoopBackOff in the orders-service pods and connection pool exhaustion in the fulfillment-service are likely due to memory constraints or misconfigurations. In the orders-service, the `resources.limits.memory` may be too low causing the containers to be terminated with an OOMKilled exit code during startup, leading to the CrashLoopBackOff. In the fulfillment-service, connection pool exhaustion could be due to the `hikaricp_connections_max` setting being too low, causing the connection pool to fill up and become unavailable. For the CrashLoopBackOff, increasing the memory limit in the pod's deployment YAML to a more appropriate value and setting `resources.limits.memory` to a reasonable amount should resolve the issue. For the connection pool exhaustion, increasing the `max` value for `hikaricp_connections_max` in the application's configuration should enable the pool to handle more requests concurrently. Escalate this to a system administrator if immediate resolution is needed, and escalate to the development team to review and fix any misconfigurations in the application YAML or database configuration that could be causing the issues.", "cited_artifacts": ["KB-00016", "KB-00017"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The rollback of the catalog-service v3.5.0 deployment needs to be handled carefully due to the DB schema migration, which adds the risk of service instability. Since the rollback has to be done within 15 minutes as specified in the Application Deployment Rollback Procedure in KB-00020, executing a DB migration rollback requires ensuring the `/db/migrations/V<x>__down` script is present in the database to reverse the schema changes. This script is responsible for rolling back the migration operations, similar to a Kubernetes rollback but specific to the database environment. If such a rollback script exists, it should be used with caution and monitored closely to avoid data loss or corruption during the rollback process. Escalation is not required as the procedures and risks for rollback are clearly outlined in the provided KB-00020 and DB migration rollback documentation.", "cited_artifacts": ["KB-00020"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "To rollback a deployment that included DB schema migration and resulted in instability, follow the Application Deployment Rollback Procedure detailed in KB-00020. Since the rollback of DB migrations is manual and specific to the database schema, it should be handled through a script that undoes the changes made by the migration scripts. Use the rollback command listed for each type of deployment, especially for database migrations as noted in the KB article, which points to checking `/db/migrations/` for a corresponding `V<n>__down` migration script that undoes the migration changes. This rollback should be attempted within 15 minutes of the bad deployment to maintain the SLA. Escalation may be required if the rollback script is complex or database-specific, necessitating DBA intervention.", "cited_artifacts": ["KB-00020"], "confidence": 0.6, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "To rollback the catalog-service v3.5.0 deployment that included a DB migration that led to service instability, you need to perform a database migration rollback by identifying the corresponding migration script in the `/db/migrations/` directory, typically denoted with a prefix `V<n>__down` for rollback operations. Use the `V<n>__down` script to revert the changes made by the previous migration V38 that added the two tables. Ensure the rollback script matches the changes made during the migration to avoid further errors. Consult the documentation provided in KB-00020 for more details on rolling back the deployment, including the specific commands and steps for reverting the database changes. Escalate to DBA if the rollback script is not available or if manual intervention is required to correct the database schema mismatch.", "cited_artifacts": ["KB-00020"], "confidence": 0.6, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "Rollback of the catalog-service v3.5.0 deployment requires careful consideration of the impact on existing DB schema as the schema migration V38 involves adding two tables, which can be challenging. Given the need for DB migration rollback, immediate intervention by a database administrator (DBA) is essential. The DBA should consult the rollback procedures outlined in KB-00020, specifically focusing on the database migration rollback part, where the DBA needs to check for a corresponding 'V<n>__down' migration script in the migrations directory to revert the changes made by V38. Escalate the request to DBA for immediate rollback as DB migrations can lead to data inconsistencies or service instability without proper rollback mechanisms.", "cited_artifacts": ["KB-00020"], "confidence": 0.6, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The unstable behavior of the catalog-service v3.5.0 deployment with DB schema migration requires immediate intervention by a database administrator (DBA) to safely roll back the database changes. This involves reverting the schema modifications made in migration version V38, ensuring no data loss and maintaining consistency across the database and application layers. Escalate to DBA for detailed rollback procedures, as documented in KB-00012 for schema migration rollback and KB-00020 for application deployment rollback procedures, with specific focus on the database migration component detailed in KB-00020. Escalate is necessary due to the complexity of database schema migrations and the potential for data corruption if not handled correctly.", "cited_artifacts": ["KB-00020"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The rollback of catalog-service v3.5.0 after encountering instability following a database schema migration can be executed by reverting the database schema changes to the previous version within the rollback window of 15 minutes. Refer to the Application Deployment Rollback Procedure in KB-00009 for detailed instructions. This includes restoring the database schema from the desired revision in the migrations history directory specified as `/db/migrations/V<n>__down.` Ensure the rollback is handled promptly to minimize downtime for dependent services.", "cited_artifacts": ["KB-00009"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The deployment rollback for the catalog-service v3.5.0 which included a DB migration that added two tables is necessary, but it is crucial to ensure the rollback does not disrupt the existing database schema. Since the rollback is only required within 15 minutes of a bad deployment according to the application deployment rollback procedure outlined in KB-00009, the rollback should be executed swiftly. This involves using the rollback commands specific to the deployment method, in this case, the Kubernetes/Helm rollback procedure (if the service was deployed using Helm) or the VM-based rollback procedure (if the service was a traditional legacy VM deployment). For the DB migration rollback, one would need to revert the last applied migration steps, but since only the last migration step is mentioned in the rollback history (`/db/migrations/V<last_migration_number>__down`), the rollback should logically step back to the previous migration version (assuming a versioned migration strategy) and then re-run the rollback commands provided by the migration scripts. Escalate the rollback process to a DBA for full intervention if the rollback scripts provided in the migration package or in the rollback procedure of KB-00009 are not accessible or fail to restore the schema properly. Escalate to DBA is indicated because the rollback to the original schema may involve complex SQL commands that a DBA can handle better.", "cited_artifacts": ["KB-00009"], "confidence": 0.5, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The rollback of catalog-service v3.5.0 which included a DB migration V38 that added two tables requires careful handling to maintain service stability. According to the Application Deployment Rollback Procedure in KB-00020, for rollback of Kubernetes/Helm deployments, use the command `helm rollback <release-name> 0` for the fastest rollback. If it involves a database migration, check if there’s a corresponding `V<n>__down` migration script in `/db/migrations/` to reverse the changes. Ensure that the rollback is executed within the specified 15-minute window to minimize impact. Escalation might be required if the rollback procedure is not following this guide or if the migration rollback is complicated due to changes in schema or data integrity. Escalate if additional information is needed.", "cited_artifacts": ["KB-00020"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The executive user David Chen is locked out due to a bad password count of 12, and his MFA is dependent on his phone. As he has lost his phone with the MFA app, the MFA reset should be handled through Okta’s Admin Console with video verification. In Okta’s Admin Console, search for David Chen and select his profile, then go to More Actions > Reset Multifactor Authentication. Follow Okta’s procedure to reset MFA, ensuring that each service is notified to re-enroll and maintaining proper video verification to ensure user identity. For account unlock, the user must be explicitly locked due to excessive failed login attempts exceeding the lockout threshold (12 failed attempts). To unlock David Chen’s AD account, the IT administrator should use the PowerShell command `Unlock-ADAccount -Identity DavidChen` to unlock the account and then reset the password using `Set-ADAccountPassword -Identity DavidChen -NewPassword (ConvertTo-SecureString 'desired-password' -AsPlainText -Force) -Reset`. Ensure there are no downstream services relying on the locked account that could be negatively impacted during these operations. Escalate this to a higher support level if the services dependent on the account continue to be inaccessible beyond the 15-minute critical window and the IT team is unable to resolve the dependency issues due to authorization or service provider policies not being addressed promptly.", "cited_artifacts": ["KB-00011"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "Executive user David Chen is locked out due to an excessively high 'BadLogonCount' (12) and is locked out of all systems. To resolve this, an IT admin should use the PowerShell command `Unlock-ADAccount -Identity DavidChen` to unlock his AD account, thus resolving the lockout issue. For MFA reset, as David Chen lost his phone, he can follow Okta’s IT admin procedure by navigating to the Okta Admin Console, searching for the user (David Chen), clicking ‘More Actions,’ selecting ‘Reset Multifactor,’ confirming the reset, and verifying the user identity via video call or badge scan before resetting MFA to ensure it is not hijacked. Escalation is not required as this solution is directly addressable from the provided KB-00011 artifacts.", "cited_artifacts": ["KB-00011"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "Executive David Chen’s AD account lockout can be resolved by the IT admin via a reset of the Multi-Factor Authentication (MFA) settings, bypassing the self-service process. First, the admin should reset Okta or Google Workspace MFA through the respective admin consoles, making sure to follow the video verification and session management steps to mitigate hijacking risks, ensuring the user is not in an active session that could be compromised. For the MFA reset, execute the Okta process by searching for the user, clicking the 'More Actions' > 'Reset Multifactor,' confirming the reset, and ensuring the user receives and verifies the activation email to re-enroll. For Google Workspace, use the command `gam update user <email> is2svEnrolled false` to disable two-step verification temporarily, and then direct the user to re-enable it at myaccount.google.com/signinoptions/two-step-verification. Escalate to escalate the ticket if there are ongoing issues with the account lockout or MFA reset, as this procedure may not be handled correctly by the users and could lead to further delays. Escalate=false.", "cited_artifacts": ["KB-00011"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "David Chen’s AD account lockout can be resolved by the IT admin verifying identity via video call and unlocking the account using the appropriate PowerShell command: `Unlock-ADAccount -Identity DavidChen`. For the MFA reset, an IT admin should reset Okta MFA for David Chen using the Okta Admin Console by searching the user in People and clicking ‘More Actions > Reset Multifactor’. This process ensures the user is re-enrolled but not during an active session to prevent potential hijacking. Escalate to the security team if the account lockout is due to unusual or repeated failed login attempts exceeding the threshold set by security policies, or if other factors indicative of a larger security breach are present. Escalate is false as we have a concrete procedure to follow.", "cited_artifacts": ["KB-00011"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "David Chen’s AD account lockout can be unlocked by an IT admin via PowerShell, using the `Unlock-ADAccount -Identity <username>` command, where the username is David Chen. However, the urgent need to reset his MFA and unlock his account requires escalation. The credentials reset for MFA must be done via the Okta admin console, which involves resetting the MFA for the user within the Okta Admin Console, under People, navigating to the user’s profile, and selecting the ‘Reset Multifactor’ option. Ensure that all services that are dependent on MFA are properly configured to accept the new credentials, including any applications or systems the user interacts with, to prevent the risk of session hijacking. Escalation to a higher IT support or security team is necessary as the user is executive, and system interruptions could be critical for business continuity. Escalate the request to a triage meeting if the initial steps do not resolve the issue swiftly.", "cited_artifacts": ["KB-00011"], "confidence": 0.6, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "David Chen is locked out due to a bad password count of 12 in his Active Directory account, which is not directly resolvable by changing the password or MFA settings for the account itself, as AD account lockout is a system-level state that cannot be unlocked through an AD user account change. However, IT admins can reset the MFA app for David Chen by resetting the MFA authentication status in Okta admin console, which will force him to re-enroll in a new app. This can be done via the Okta Admin Console under the ‘People’ section, selecting the user, and using the ‘Reset Multifactor’ function to unlock the account while bypassing his locked AD account. Ensure that the administrator logs in with the appropriate credentials and verifies David Chen’s identity via video call or badge scan before proceeding. Escalate to an Okta support ticket to ensure proper access is restored, as resetting the MFA without unlocking the AD account does not affect the AD lockout status; only unlocks the MFA app for logging in.", "cited_artifacts": ["KB-00011"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "David Chen is locked out of his AD account due to a bad password count of 12, which requires unlocking his account via the PowerShell command `Unlock-ADAccount -Identity DavidChen` or through the Azure Portal with administrative privileges to reset the lockout state and unlock the account. For the MFA reset, since David has lost his phone, the Okta Admin Console must be accessed to reset the MFA with the Okta MFA reset process. This involves navigating to the Okta Admin Console, searching for the user David Chen, and using the user’s verified video call for identity verification to reset MFA settings, bypassing the need for a phone. Ensure all sessions for David Chen are terminated before attempting the MFA reset to prevent hijacking of his account. Escalation is unlikely as the steps are well-documented within the KB-00011 artifact.", "cited_artifacts": ["KB-00011"], "confidence": 0.6, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The executive user David Chen is locked out of all systems due to an excessively high bad password count on his AD account. His MFA setup was likely bypassed when he lost his phone, leading to the account lockout. To resolve this urgently within 15 minutes, an IT admin must first unlock his AD account by running the command `Unlock-ADAccount -Identity DavidChen` in PowerShell, as the account lockout status is `True`. However, for the account to remain usable, the bad password count needs to be reset. Admins cannot reset this count via the AD interface directly; it requires the intervention of a service account with appropriate permissions, such as unlocking the account and then re-enabling the account password to reset the count back to zero while ensuring no active sessions can hijack the account. Escalate this ticket to a higher security level if the service account does not have the necessary permissions or if the bad password count is higher than a configurable threshold (which is not specified in the provided KB-00008), as manually resetting the bad password count directly without locking the account first may result in ongoing lockouts and account issues. Escalate to a security team if escalation to the service account fails, indicating a broader security issue.", "cited_artifacts": ["KB-00008"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The Kafka consumer group lag spike on the recommendations topic could be due to load imbalance or insufficient consumer group concurrency settings, causing messages to accumulate in the topic backlog. Increase the number of consumers or set the `min.insync.replicas` parameter to a lower value to ensure message acknowledgments with fewer replicas, thereby reducing lag. Escalate to Kafka cluster monitoring tools to check the consumer group rebalancing status and ensure the partitions are being consumed evenly by the consumers. Escalate to the team if the issue persists, indicating potential misconfiguration of Kafka configurations or application errors in committing offsets, leading to message retention in the topic even after processing. Escalate if the system environment changes affecting consumer group performance, like changes in network latency, CPU load, or memory fragmentation impacting the Rust application. Escalate to kafka cluster management tools if there’s a cluster misconfiguration or data skew, where some partitions receive fewer messages, while others accumulate backlog leading to lag issues. Escalate to telemetry monitoring systems if the lag increases even without a change in the consumer group or Kafka settings, pointing to an underlying issue with the topic itself, such as having too few partitions for the load or uneven consumer consumption rates.", "cited_artifacts": ["KB-00001"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The Kafka consumer group lag spike in the recommendation topic could be due to issues with consumer rebalancing, leader election timeouts, or insufficient consumer group offsets being processed by the Kafka brokers. Check if there are any leader election timeouts for the consumer group, which could indicate that the Kafka brokers are not able to handle the load and hence not reassigning partitions correctly. Ensure that the consumer group is set up to process offsets out of order and that the Kafka brokers are configured to handle high throughput and low latency. Escalate to operational support if the issue persists despite these configurations and if there are no runbooks available for such issues. Escalate: true", "cited_artifacts": ["KB-00001"], "confidence": 0.1, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The high lag in the Kafka consumer group recommendation-consumer can be attributed to message processing delays or throttling within the consumer application or Kafka cluster. For the Kafka cluster, ensure the batch size and linger time settings are appropriately configured to balance throughput and latency. For the consumer application, debug logs should be examined for any throttling messages indicating message buffer overflow or max rate limit reached. Ensure that the Kafka consumer application is correctly set to consume from the leader replica in the topic partition for efficient consumption and to maintain message offsets correctly. Escalate to operations support if the lag continues to grow despite these adjustments, indicating potential deeper issues such as resource contention, network instability, or resource exhaustion on the consumer side, which necessitate a more detailed review and remediation.”, "cited_artifacts": ["KB-00001"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The Kafka consumer group lag spike on the recommendations topic in the Rust consumer application is likely due to inefficient message consumption or batch processing, leading to large lag. Ensure the consumer application reads messages in a timely manner and does not drop messages due to processing delays. Additionally, check the producer side to ensure it is not overwhelming the Kafka topic with too many messages too quickly, which can cause lag spikes. Tools like Kafka Tools or the Kafka consumer application logs can reveal processing delays or exceptions. Escalate to DevOps if the lag is not resolved by optimizing the consumer application and producer load. Escalate to Kafka cluster management if the lag is severe across the entire topic and production is impacted. Escalate to Broker Side Tools if there are issues with the Kafka broker that are not being handled effectively. Escalate if Kafka version incompatibility or misconfiguration of configuration parameters (e.g., batch.size, linger.ms, max.poll.interval.ms) is causing the lag. Escalate to third-party integrations if the Rust consumer application is part of a larger microservices architecture and message handling delays in one service are impacting the consumption of messages by the Kafka consumer. Escalate if the producer load on the recommendation topic is significantly higher than the consumer load, causing buffer overflow and lag. Escalate with KSQL or Flink for complex message consumption patterns that the Kafka consumer cannot handle efficiently. Escalate if the producer and consumer are not configured to handle transient partitions and rebalancing events properly, leading to load imbalances across partitions and increased lag spikes. Escalate if there is no runbook, and escalation steps are not available to follow due to misconfiguration or lack of proper tooling.", "cited_artifacts": ["KB-00001"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The Kafka consumer group lag spike for the recommendation topic could be due to improper configuration of the Kafka Consumer group ID or its initial position within the topics. Ensure that the consumer group is correctly configured and that it is not attempting to consume messages out of order. Additionally, check that the topic's partition count matches the number of partitions in the consumer group to prevent duplicate messages and lag. Escalate to a Kafka expert if the issues persist as they may involve complex configurations of offsets, rebalancing strategies, or schema migrations that the current consumer code does not handle properly, or underlying system errors not captured in this runbook.", "cited_artifacts": ["KB-00001"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The Kafka consumer group lag spike on the recommendations topic could indicate issues with partition assignment or rebalancing within the consumer group. The custom Rust application might not be correctly handling rebalance events, leading to group rebalances causing increased lag. Additionally, a potential mismatch in the number of partitions across the topics in the consumer group can cause uneven distribution, leading to consumers being overwhelmed by the number of messages. Ensure that the consumer group rebalance strategy in the Kafka configuration (e.g., `auto.offset.reset='latest'` or `group.instance.id` is set appropriately) and that the number of partitions in each topic matches the number of consumers in the group. Escalate to more detailed Kafka documentation or community forums if these general configurations are set correctly but lag persists. Escalate to operations teams if there's no change in behavior despite adjustments, as it could indicate underlying software issues like message reordering or deadlocks within the custom Rust application.", "cited_artifacts": ["KB-00001"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The 4.2M message lag spike in the Kafka consumer group recommendation-consumer could indicate issues with message acknowledgment in the producer side or consumer group's assignment strategy. Ensure that producers are configured to send ACKs at the appropriate level (at-least-once or at-most-once semantics) and that the Kafka consumer group rebalances the partitions correctly among consumers. Use the Kafka CLI commands like `kafka-consumer-groups.sh` to check the group offsets and ensure the lag is being actively processed rather than stalling due to an imbalance in consumer distribution. Check if there are duplicate consumer instances or excessive group sessions active. Escalate to a runbook writer if Kafka version changes or complex configurations lead to difficulty resolving.", "cited_artifacts": ["KB-00001"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The Kafka consumer group lag spike on the recommendation topic could be due to the consumer group attempting to process messages beyond the offset at which the producer stopped writing, causing the lag to accumulate over time. This issue might stem from network latency or a misbehaving producer not committing offsets properly or aborting sessions prematurely, leading to messages being reprocessed by the consumer group. Ensure the consumer group rebalancing is optimized and configured correctly to manage large topic partitions, and check if the producer application is correctly committing offsets and handling partition assignments. Escalate to Kafka support if the issue persists as it could indicate deeper misconfiguration or misbehavior of the Kafka broker or the consumer application itself. Escalate to escalation for further investigation if the system has been stable previously and the consumer group lag increases unexpectedly, as it could be a symptom of broker resource exhaustion or offsets being stuck, which Kafka itself cannot resolve without consumer intervention or broker reinitialization. Escalate with details if network routing or producer behavior is changing, leading to increased lag as consumer group topics are partitioned unevenly or producers are not properly managing their offsets or sessions. Escalate with escalate=true if no relevant runbook or root cause is identified after checking these configurations and logs.", "cited_artifacts": ["KB-00001"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "User Michael Torres can reset his MFA by using the Okta MFA reset method. First, log into Okta’s Admin Console, find Michael Torres in the People section, and select him to activate the Reset Multifactor Authentication process under the More Actions dropdown. Okta will send a verification code via email that the user needs to use to reset their MFA. The reset does not necessitate a new phone but does require a new authentication method for user re-enrollment, such as an app downloaded on a new device. Escalation is not required as the solution is directly provided in the KB-00011 artifact.", "cited_artifacts": ["KB-00011"], "confidence": 0.6, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "Michael Torres needs his Google Authenticator for multi-factor authentication (MFA) reset as he has lost his phone. IT admins can reset the MFA for Michael by initiating the Okta MFA reset process via the Okta Admin Console. Follow the steps: in Okta Admin Console > Directory > People > Search for Michael Torres, click on Michael’s account, select ‘More Actions’ and then ‘Reset Multifactor Authentication’. Admins should be present to verify Michael’s identity via a video call or badge scan before proceeding with the reset. The Okta reset procedure can be achieved by clicking on the reset link sent to Michael’s email address and he can re-enroll his MFA in Google Authenticator from myaccount.google.com/signinoptions/two-step-verification. Ensure that Michael’s old session keys are not used for unauthorized access and that there are no active sessions on the new enrolled MFA device to prevent hijacking. Escalate if services are still inaccessible post reset due to issues like clock skew or other backend configurations.", "cited_artifacts": ["KB-00011"], "confidence": 0.6, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "Michael Torres is locked out of MFA due to losing his phone with the Google Authenticator app. This can be resolved by resetting the MFA for the user through Okta, as resetting in Azure AD or Entra MFA does not directly reset the MFA app enrollment on the user's device. Follow the Okta MFA reset procedure in the Okta Admin Console, where IT admin actions include searching the directory for Michael Torres, resetting the multifactor authentication through the 'More Actions' > Reset Multifactor option, and confirming the reset by providing an activation link to the user to re-enroll their MFA in their Google account at myaccount.google.com/signinoptions/two-step-verification. Escalate to the IT support team if the Google Authenticator reset fails or if user sessions are not properly terminated to prevent hijacking, as stated in the Okta MFA reset procedure under 'Current Sessions' where IT should terminate all sessions to ensure security. Escalate to escalate because self-recovery of MFA via backup codes is not possible if the user’s backup codes are lost. Escalate is recommended if the user still cannot log in after reset due to account lockouts, or if the user reports issues with the recovery link timing out or being blocked due to Google’s account lockout policies; escalate to the IT team for assistance in handling account lockouts and review of IT security policies and Okta settings to ensure they comply with corporate security requirements.", "cited_artifacts": ["KB-00011"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "Michael Torres should reset his MFA through Okta Admin Console by navigating to Directory > People > Searching for user Michael Torres, selecting the user, and using the ‘More Actions’ > Reset Multifactor option in Okta. This action requires verifying Michael’s identity via a video call or badge scan, thus ensuring security. The Okta reset procedure includes clicking on the user, selecting more actions, and then initiating the MFA reset feature. Upon successful reset, Okta sends an activation email to the user, which must be re-confirmed and re-enrolled on the Google Authenticator app. Escalation is not necessary as the solution is outlined in the provided Okta MFA reset procedure for Google Workspace, citing KB-00011.", "cited_artifacts": ["KB-00011"], "confidence": 0.6, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "Michael Torres can reset his MFA by using the Okta Admin Console. Go to the People section and search for Michael Torres. Click on Michael Torres and then select More Actions > Reset Multifactor. Confirm the reset and Michael will receive an activation email with a recovery code. He should then use this recovery code to re-enroll in the Google Authenticator app on a new device. Escalation to the IT security team is advised if no recovery codes are available and no other methods are implemented in the Okta settings, such as Google backup codes stored securely or Azure AD re-registration steps, due to potential loss of session data and risk of account hijacking. Escalate to the escalation ticket if insufficient steps are covered in Okta settings or if there is evidence of ongoing system-wide MFA misconfiguration and password resetting issues.", "cited_artifacts": ["KB-00011"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "Michael Torres needs to reset his MFA through Okta for the Google Authenticator app because the user is locked out due to losing the phone with the authenticator app. This can be done by an IT admin in the Okta Admin Console by searching for the user, clicking on more actions, and then selecting the 'Reset Multifactor' option. Since the user has been verified in person with a badge, the MFA can be reset without undue risk of unauthorized access as per Okta’s MFA reset procedure. Escalate to a higher ticket escalation if the user has active sessions that could be hijacked or if there are issues with the authentication methods configured between Okta and the applications the user accesses, such as incorrect Audience or ACS URL mismatch settings. Escalate to escalate is false for this issue as the primary ticket requires resetting MFA in Okta with verified user identity.", "cited_artifacts": ["KB-00011"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "Michael Torres’s account being locked out due to the lost phone with the Google Authenticator MFA setup can be resolved by the IT administrator using the Okta MFA reset procedure. The administrator can navigate to the Okta Admin Console, under the ‘Directory’ section, search for Michael Torres by entering his email, and reset his MFA by selecting ‘More Actions > Reset Multifactor’. This action will initiate an email reset process for his authenticator app, allowing him to re-enroll and regain access with the backup codes stored on his alternative phone or secure storage method. Escalate is not necessary as the solution is directly provided in the ‘MFA Reset and Account Unlock Procedure’ within KB-00011, which states this exact process for IT admins to handle such scenarios.", "cited_artifacts": ["KB-00011"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "Michael Torres needs to reset his MFA because he lost his phone with the Google Authenticator app installed for two-factor authentication (MFA). The MFA reset for Google Workspace can be done via the command `gam update user michael.lopez is2svEnrolled false`, which disables the MFA for the user. The admin should then notify Michael to re-enroll Google Authenticator on a new phone or device. Escalate to escalate indicates insufficient context to fully resolve this ticket, but given it is a straightforward reset and no escalation is clearly required here, the ticket should be closed with a confirmation of the reset command provided. Escalate: False.", "cited_artifacts": ["KB-00011"], "confidence": 0.4, "escalate": false}}
```