Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For jsmith's AD account lockout issue, check the lockout status with `Get-ADUser <username> -Properties LockedOut,BadLogonCount,LastBadPasswordAttempt` to see if the user is locked out or has any bad logon attempts. If LockedOut=True, unlock the account using `Unlock-ADAccount -Identity <username>` and ensure the BadLogonCount is within the range of 3-5 by checking `Get-ADUser <username> -Properties BadLogonCount` and using `Unlock-ADAccount -Identity <username>`. For password expiry, use `Get-ADUser <username> -Properties PasswordExpired` and if PasswordExpired=True, reset the password with `Set-ADAccountPassword -Identity <username> -NewPassword '<new-password>' -Reset` (where <new-password> is a strong password). Use `LockoutStatus.exe` from the Microsoft free tools to diagnose if the lockout is due to the source computer locking the account or if it’s due to services using cached old password. Services using cached old password are diagnosed by using `Get-ADUser <username> -Properties EventID 4740` for the source computer lockout and fixing the cached password issue by updating the account using `Set-ADAccountPassword -Identity <username> -NewPassword '<new-password>' -Reset`. No need to refer to KB-00012 as it’s not relevant to AD lockout resolution. Escalation to IT Admins for Okta MFA reset procedures is not applicable here and requires an escalation.", "cited_artifacts": ["KB-00008"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the user jsmith account lockout issue in Active Directory, unlock the account using `Unlock-ADAccount -Identity jsmith` in PowerShell to clear the lockout status and use `Get-ADUser jsmith -Properties LockedOut,BadLogonCount,LastBadPasswordAttempt` to check if LockedOut=True and unlock it with `Unlock-ADAccount -Identity jsmith`. For lockout source, check `Get-ADUser jsmith -Properties LockedOut,BadLogonCount,LastBadPasswordAttempt` for BadLogonCount and LastBadPasswordAttempt to see if they are locked due to a bad logon or last bad password attempt, and use `LockoutStatus.exe` to check common sources of lockouts like mapped drives or services using cached old password. If PasswordExpired is True, the user must reset it via `Set-ADAccountPassword`. Check for Kerberos ticket issues with Event ID 4771 (pre-auth failed) and error codes 0x18 and 0x25 to ensure no clock skew due to <5 min is causing the clock skew. No specific KB or other procedure from the retrieved context can be applied for account lockout resolution, use the procedures for LockoutStatus tool and check for bad logon details directly in powershell. No escalation needed as the procedures are directly provided for troubleshooting.", "cited_artifacts": ["KB-00008"], "confidence": 0.6, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the AD account locking issue, user jsmith's account remains locked due to mapped drives causing a lockout, which can be seen in Event ID 4740 on the PDC Emulator, indicating the source computer locking the account. Use `Get-ADUser <username> -Properties LockedOut,BadLogonCount,LastBadPasswordAttempt` in PowerShell to check the lockout status and use `Unlock-ADAccount -Identity <username>` to unlock. For longer bad password attempts leading to lockout, use `Get-ADUser <username> -Properties PasswordExpired` to check if PasswordExpired is True, and reset with `Set-ADAccountPassword` if True. No need for service account rotation or Okta/Google/Entra MFA reset procedures as those are related to multi-factor authentication and not AD account lockouts. Escalation to IT admin for help or a knowledge base on this issue is advised.", "cited_artifacts": ["KB-00008"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For jsmith's AD account lockout issue, the account is being locked due to the bad password attempts and password expiry, which is typical for 'Invalid credentials' and 'Account locked' errors respectively. Use PowerShell to check the lockout status with `Get-ADUser jsmith -Properties LockedOut,BadLogonCount,LastBadPasswordAttempt` to see if the account is locked out and unlock it using `Unlock-ADAccount -Identity jsmith`. For password expiry, use `Get-ADUser jsmith -Properties PasswordExpired` to check if the `PasswordExpired` is True, indicating a password reset is needed through `Set-ADAccountPassword -Identity jsmith -NewPassword 'NewPassword' -Reset`. No specific service account password rotation or authentication failures involving BGP peer sessions are mentioned, so no steps from KB-00012 or related are applicable to this scenario. Escalation to AD or admin guides is not required.", "cited_artifacts": ["KB-00008"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For user jsmith getting locked out of AD with a bad logon count and account lockout, the issue is due to a cached old password that leads to the bad logon count increment and account lockout. Use the `Get-ADUser <username> -Properties LockedOut,BadLogonCount,LastBadPasswordAttempt` command in PowerShell to check if the user jsmith’s account is locked and if the `Unlock-ADAccount -Identity <username>` command to unlock it. Use `(Get-ADUser <username> -Properties PasswordExpired).PasswordExpired` to check if the user needs to reset the account password due to password expiry; use `Set-ADAccountPassword` to reset the password if true. For a bad logon count increment, ensure the mapped drive or a service using the cached old password is not the source, use `LockoutStatus.exe` tool to check. No specific KBs provide solutions for the source of the account lockout based on a service account password rotation or BGP peer session down (which are not related).", "cited_artifacts": ["KB-00008"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the AD account lockout issue with jsmith, the steps are as follows: Use the PowerShell command `Get-ADUser <username> -Properties LockedOut,BadLogonCount,LastBadPasswordAttempt` to check the lockout status and unlock the account with `Unlock-ADAccount -Identity <username>` if LockedOut is True. To find the lockout source, use `Event ID 4740` from the PDC Emulator and use `LockoutStatus.exe` from Microsoft to determine the source, which could be a mapped drive or services using cached old password. Passwords are locked out every 10-15 minutes because it is set by the system to prevent brute-force attacks (password lockout threshold = 5 attempts within 10 minutes). Admins can reset the password via `Set-ADAccountPassword` if the `PasswordExpired` property is True. No further escalation needed as steps can be followed from the given contexts. No need to reference IDs from the Okta or Azure AD reset procedures due to the context being specific to AD lockouts.", "cited_artifacts": ["KB-00008"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For user jsmith who is locked out in AD and locks again every 10-15 minutes, use the following steps to troubleshoot: Use `Get-ADUser jsmith -Properties LockedOut,BadLogonCount,LastBadPasswordAttempt` in PowerShell to check the lockout status and unlock the account with `Unlock-ADAccount -Identity jsmith`. For a lockout source, use `Event ID 4740 on the PDC Emulator` to see the source computer locking the account and use the `Account Lockout Status (LockoutStatus.exe) tool` to see if it's due to mapped drives or services using cached old password. For password expiry, use `(Get-ADUser jsmith -Properties PasswordExpired).PasswordExpired` to see if the user needs a password reset via `Set-ADAccountPassword` and ensure `LockedOut=True`. No specific service account rotation steps are available from the provided context, so refer to KB-00008 for AD authentication failures and for Kerberos issues, refer to KB-00008 for ID 4771 error with details on clock skew. No specific steps are provided for user-unrelated issues like Okta or Azure AD MFA resets from the context, hence none are applicable here.", "cited_artifacts": ["KB-00008"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the issue where User jsmith's AD account keeps locking out every 10-15 minutes and needing to be unlocked each time, we can follow the AD authentication failure troubleshooting guide (KB-00008) with the following steps in PowerShell: For the lockout status check, use `Get-ADUser <username> -Properties LockedOut,BadLogonCount,LastBadPasswordAttempt` to see if LockedOut=True, and unlock the account with `Unlock-ADAccount -Identity <username>`. For the source of the lockout, use `Get-ADUser <username> -Properties PasswordExpired` to check if PasswordExpired is True, which means a reset with `Set-ADAccountPassword` is needed. To find the lockout source, use `Event ID 4740` on the PDC Emulator to see the source computer locking the account, and use `LockoutStatus.exe` tool from Microsoft. For password expiry, if `PasswordExpired` is True, a reset can be done with `Set-ADAccountPassword` with caution as admins cannot see the password directly. There are no services to rotate or AS/MD5 related to this issue; thus, there’s no escalation needed. ", "cited_artifacts": ["KB-00008"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the API gateway 504 timeout issue, adjust the timeout configuration in the API gateway (like Kong) to `proxy_read_timeout 60000` to ensure the gateway waits for up to 60 seconds for the upstream response as per Step 4 of the API Gateway 504 Timeout Troubleshooting provided. For rollback of the billing-service v3.1.0 deployment, use the Kubernetes/Helm rollback procedure: `helm rollback <release-name> 0` or `kubectl rollout undo deployment/<name>` to roll back to v3.0.8. Execute within 15 minutes as per Application Deployment Rollback Procedure from KB-00020. No direct reference found for certificate renewal or API token revocation from the context provided, thus these steps are not applicable. Escalation to support ticket or expert advice is required for certificates and token management issues.", "cited_artifacts": ["KB-00020", "KB-00018"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the API Gateway 504 timeout, ensure the API is not being held up by a slow upstream service and its dependencies by checking the API gateway access logs for 504s with `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` to identify timeouts and filter by the backend response times. For Step 2, test the slow service directly outside the gateway by hitting `http://<upstream-host>:<port>/endpoint` to ensure it’s responding as expected. For API Gateway rollback, refer to Application Deployment Rollback Procedure: Use `helm rollback <release-name> 0` or `kubectl rollout undo deployment/<name>` for Kubernetes/Helm rollback or `ln -sfn /opt/app/releases/<prev-version> /opt/app/current` followed by `systemctl restart <service>` for legacy VM rollback. No information is provided for rollback or certificates issues. Therefore, we need to escalate to a full documentation guide or for a specific rollback method based on the latest rollback procedure provided, which requires history lookup on the deployment tag and then a rollback to a previous tag with `helm rollback <release-name> 0` or similar methods if the environment supports it. No specific citation for certificate rollback or API Token practices from the provided context.", "cited_artifacts": ["KB-00018", "KB-00020"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the 504 Gateway Timeout issue on the API gateway for the /billing/invoice endpoint, we need to adjust the timeout configuration in the API gateway itself by setting `proxy_read_timeout 60000` in the configuration file (Kong). For rollback of the billing service v3.1.0, refer to the Kubernetes/Helm rollback procedure in KB-00020, using `helm rollback <release-name> 0` or `kubectl rollout undo deployment/<name>` to roll back to the previous version. No issues found in the retrieved context for database migration rollback or TLS certificate renewal. Escalation to support tickets or support channels is required for API token rotation and DHCP scope exhaustion issues as these do not have direct solutions provided. ", "cited_artifacts": ["KB-00020", "KB-00018"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the API Gateway 504 timeout on /billing/invoice in the billing-service v3.1.0 deployment, the upstream service is the root cause and should not be addressed through rollback procedures. For the API Gateway timeout, adjust the timeout configuration in the API Gateway access logs, specifically on the API Gateway access logs under /var/log/kong/access.log to filter for 504s and use `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` to check for the slow upstream. For handling the 504 timeouts, adjust the timeout configuration in the API Gateway with `proxy_read_timeout 60000` in the configuration file to 60000ms. No rollback procedures are applicable. Check upstream response for the API /billing/invoice with `curl -w '%{time_total}' -o /dev/null http://<upstream-host>:<port>/endpoint` to test directly. The API Gateway rollback and TLS certificate renewal, API token rotation, and DHCP scope exhaustion issues mentioned are not relevant to this API gateway timeout issue as they do not provide specific guidance on the API Gateway 504 Timeout. Escalation to the support ticket community or more specific APIs related to API Gateway timeout tuning is required for specific API Gateway timeout resolution steps, which can be detailed under other KBs if available.", "cited_artifacts": ["KB-00018"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the API gateway 504 timeout, filter for 504s in the API gateway access logs using the command `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` to identify slow upstream services and check for DB query regression by running `explain plan on slow queries` to ensure a missing index. For the deployment rollback, use `helm rollback <release-name> 0` or `kubectl rollout undo deployment/<name>` to rollback to the previous version of the billing-service. For verification, use `helm history <release-name>` or `kubectl rollout history deployment/<name>` to check the rollback history. No mentions of rollback within 15 minutes for Kubernetes deployment in the retrieved context. The API token rotation and TLS certificate information is not relevant to the current ticket. No citation artifacts from the provided context are directly applicable for the rollback and TLS certificate issues.", "cited_artifacts": ["KB-00018"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For API Gateway 504 timeouts, the issue is the upstream service that is taking longer than the gateway's configured timeout. Use the API Gateway 504 Timeout Troubleshooting step-by-step to diagnose. For API Gateway timeouts, filter for 504 errors in API gateway access logs with `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` to find the slowness. Additionally, bypass the gateway by hitting the upstream service directly using `curl -w '%{time_total}' -o /dev/null http://<upstream-host>:<port>/endpoint`. If this also times out, the issue is with the upstream service itself. For rollback of the billing service v3.1.0 to v3.0.8, use the Kubernetes/Helm rollback procedure from Application Deployment Rollback Procedure: `helm rollback <release-name> 0` to roll back to the previous version. The <release-name> should be replaced with the name of the release in your environment. No direct information on rollback to V3.0.8 can be found. Escalation to Support Ticket Assistance is advised for specific rollback steps, and refer to the provided rollback procedure guidelines and update the rollback command accordingly. No direct information on API token rotation or DHCP scope exhaustion are provided, therefore no actionable steps can be suggested from these retrieved context sections.", "cited_artifacts": ["KB-00018", "KB-00020"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the 504 Gateway Timeout issue with the API Gateway on /billing/invoice, the API gateway timeout is due to the upstream service not responding within the gateway's configured timeout of 60 seconds (in the config 'proxy_read_timeout 60000' in Kong). Use the API Gateway access logs to filter for 504 errors and analyze the times with: `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n`. For the rollback of the billing-service v3.1.0 deployment, refer to the Application Deployment Rollback Procedure in KB-00020, using `helm rollback <release-name> 0` or `kubectl rollout undo deployment/<name>` to roll back to v3.0.8 within 15 minutes of the bad deployment. No information was found regarding the API token rotation or revocation or DHCP scope exhaustion, so they are not applicable to this ticket. Escalation to the team is not required.", "cited_artifacts": ["KB-00018", "KB-00020"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the API Gateway 504 timeout issue on the /billing/invoice endpoint, identify the slow upstream service by checking API gateway access logs to filter out 504 responses and ensuring the upstream service does not return the expected time within the configured timeout (using `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` and `curl -w '%{time_total}' -o /dev/null http://<upstream-host>:<port>/endpoint`). For deployment rollback of the billing service from v3.1.0 to v3.0.8, follow the rollback procedure for Kubernetes/Helm deployments. Use `helm rollback <release-name> 0` or `kubectl rollout undo deployment/<name>` to roll back to the previous revision (latest available using `helm history <release-name>`). No specific reference is given for rollback to v3.0.8, so it's not clear if the rollback procedure from v3.1.0 to v3.0.8 would follow the same steps, hence there’s a lack of direct context. Seek specific steps for v3.1.0 rollback to v3.0.8 for precise guidance or escalate for additional context on rollback procedures for specific versions or services.", "cited_artifacts": ["KB-00018", "KB-00020"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the search-service high latency due to Redis memory alert, the eviction policy is set to `allkeys-lru` which causes cache misses leading to increased Redis database load and response latency. To fix this, change the Redis eviction policy to `allkeys-random` using the `redis-cli CONFIG SET maxmemory-policy allkeys-random` command. For memory pressure, ensure Redis is not running with a high percentage of memory usage (>90%). Use `redis-cli CONFIG GET maxmemory` to ensure Redis is not using more memory than configured with `redis-cli CONFIG SET maxmemory 500mb` to allocate a reasonable max memory limit. For keys without TTL, add `spring.session.redis.cleanup-cron=0 * * * * *` in application properties to enable Redis cleanup. The given context does not provide solutions for Spring Session session timeout issues or API Gateway timeout problems directly, so these will not be addressed here.", "cited_artifacts": ["KB-00019"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the search service high latency due to Redis memory alert and 95% usage with an allkeys-lru eviction policy leading to cache misses and an OOM situation, you should increase Redis memory limit using the command `redis-cli CONFIG SET maxmemory 50MB` to scale down memory. For Spring Session storing sessions forever by default, you need to configure it properly by adding `spring.session.redis.cleanup-cron=0 * * * * *` to the application properties to ensure a cleanup strategy. No immediate mitigations are provided for the allkeys-lru eviction problem in the context, hence no specific fix is provided in the context. Escalation to Redis eviction policy and Spring session properties configurations are the only actionable steps from the given context. No references from other provided contexts could be used to advise on a specific immediate fix for cache misses without a clear resolution path from the available data.", "cited_artifacts": ["KB-00019"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Redis cache eviction issue causing high response times, the cache use case requires the eviction policy set to `allkeys-lru` as per KB-00019. For Spring Session keys, ensure `spring.session.timeout` is set or add `spring.session.redis.cleanup-cron=0 * * * * *` for immediate cleanup, and adjust the Redis eviction configuration to not allow the keys without TTL: `redis-cli CONFIG SET maxmemory 70%` to 80% of the total memory, and adjust maxmemory_policy to `allkeys-lru`. For keys without TTL, use `redis-cli CONFIG SET maxmemory 50%` and add `spring.session.redis.cleanup-cron=0 * * * * *`. No further fixes from the retrieved contexts are required for the connection pool exhaustion or API gateway timeout issues. Escalation to the support or DevOps leads for further investigation is advised for these aspects.", "cited_artifacts": ["KB-00019"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the search-service high latency after Redis memory alert due to 95% used memory with allkeys-lru eviction causing cache misses to spike and increasing database load, use KB-00019 for the Redis eviction policy issue. Use the command `redis-cli CONFIG GET maxmemory-policy` to check the eviction policy, it should be `allkeys-lru`. For Spring Session with Redis cache use, ensure `spring.session.timeout` is not set to 'forever' by default, fix this by adding `spring.session.redis.cleanup-cron=0 * * * * *` in the application properties. To handle Redis memory exhaustion and high eviction, scale up the Redis memory limit with `redis-cli CONFIG SET maxmemory <desired_memory_in_bytes>`. For the cache miss to decrease, ensure there are no keys without TTL in Redis by running `redis-cli --scan --pattern '*' | xargs -L 1 redis-cli ttl | grep -c '-1'` to check for keys without an expiration time and add `spring.session.redis.cleanup-cron=0 * * * * *` to the application properties for session cleanup. Escalation to a support specialist or revising to the appropriate KB or guide might be required for connection pool exhaustion as the context provided is insufficient for the same.", "cited_artifacts": ["KB-00019"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the search-service high latency after Redis memory alert with 95% usage and 'allkeys-lru' eviction policy, reduce memory usage to 90% or less by increasing the Redis memory limit with `redis-cli CONFIG SET maxmemory 800mb` if your Redis instance allows it. Ensure no keys have no TTL by checking `redis-cli --scan --pattern '*' | xargs -L 1 redis-cli ttl | grep -c '-1'` and adding `spring.session.redis.cleanup-cron=0 * * * * *` to Spring Session to ensure cleanup is enabled. For the Spring configuration, if no TTL is added to session keys, increase the Redis memory limit and configure Spring Session cleanup to prevent keys from staying indefinitely in memory. No direct fix for Redis eviction or key expiry issues are mentioned in the retrieved context, so no specific KB reference for that. No connection pool or API gateway issues mentioned, thus no steps from KB-00018 or KB-00017 applicable here.", "cited_artifacts": ["KB-00019"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the search-service high latency due to Redis memory alert with 95% usage and allkeys-lru eviction causing cache misses leading to increased database load, scale up Redis memory by setting `redis-cli CONFIG SET maxmemory <desired_memory>` to avoid memory exhaustion and set `redis-cli CONFIG SET maxmemory-policy allkeys-random` to randomize eviction policies which can help. For Spring Session in the session keys filling Redis memory, add `spring.session.redis.cleanup-cron=0 * * * * *` to the configuration to enable session cleanup every minute. No immediate fix is found for the cache misses issue related to cache eviction and key expiry without additional specific configuration or tuning, which does not correlate directly with the provided context. Escalation to seek comprehensive solutions on cache eviction and key expiry is advised from comprehensive KB articles on Redis Cache Eviction and Key Expiry Issues. No immediate cause for the search service latency escalations and response times are mentioned within the provided context; hence no step-wise immediate solution for the service degradation is available here.", "cited_artifacts": ["KB-00019"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Redis memory usage issue, the `allkeys-lru` eviction policy is causing cache misses which spike the Redis memory usage, leading to increased cache latency. Spring Session keys should have a timeout configured to prevent them from being stored indefinitely, as this can cause keys to fill Redis memory. Add 'spring.session.redis.cleanup-cron=0 * * * * *' to the application properties to ensure sessions are cleaned up. For the search service latency, it appears unrelated to Redis or any of the other services mentioned, so there's insufficient context to directly resolve this part without additional details. Adjust Redis eviction to 'allkeys-llist' or 'allkeys-random' which evict the least recently used or least frequently used keys respectively. Ensure keys don't have expiration TTL (Spring Session timeout default is infinite without setting 'spring.session.timeout') and handle Spring Session keys expiries by setting 'spring.session.redis.cleanup-cron=0 * * * * *' for cleanup. No specific methods or configs for search service latency are mentioned from the retrieved context. Escalation to specific resources or stack trace is needed for the service issues.","cited_artifacts": ["KB-00019"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the search-service high latency issue due to Redis memory alert with 95% usage and key expiry causing cache misses, the correct eviction policy for Redis is `allkeys-lru`. Use the command `redis-cli CONFIG GET maxmemory-policy` to confirm it is indeed `allkeys-lru`. For Spring Session keys with no expiry and session storage indefinitely consuming memory, add the configuration `spring.session.redis.cleanup-cron=0 * * * * *` to enable cleanup. For keys without expiry in Redis (no expiration time), the command `redis-cli --scan --pattern '*' | xargs -L 1 redis-cli ttl | grep -c '-1'` will show the count. Address the memory usage issue by checking the memory used by Redis with `redis-cli INFO memory` to ensure `maxmemory` is within `maxmemory` and compare it with the `used_memory_rss`. If `maxmemory` is less than 90% of `maxmemory`, no eviction is active and the `maxmemory` value should be increased to lower the threshold. For the cache misses causing latency, use `redis-cli CONFIG SET maxmemory <new_value>` to scale up the Redis memory and decrease the number of cache misses. There is no direct mention of Spring Session misconfiguration and key expiry that needs immediate action from the given context. No definite fix for the Spring Session issue and current context does not provide a direct solution for Liveness probe errors. Thus, refer to the KB-00019 for eviction policy and Redis memory issue, and add the configuration `spring.session.redis.cleanup-cron=0 * * * * *` for Spring Session keys with no TTL. No step by step solution for the API gateway timeout or Kubernetes pod crash loop backoff issues as these are not linked in the retrieved context.", "cited_artifacts": ["KB-00019", "KB-00018"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For OOM crashes due to unbounded Guava Cache or Caffeine cache in the user-profile service, add `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` to the JVM startup parameters and use `jmap -dump:format=b,file=/tmp/heap_$(date +%s).hprof <pid>` to capture a heap dump which can be analyzed with Eclipse MAT to identify the 'Problem Suspect'. For orders-service DB connection exhaustion, confirm the connection pool exhaustion by checking `hikaricp_connections_active` and `hikaricp_connections_max` in Prometheus/Grafana for HikariCP pool metrics, and by running `kill -3 <pid>` to get the thread dump for JDBC threads in the 'RUNNABLE' or 'WAITING' state with stack frames for the database. For rollback with DB migration concern for v5.0.0, follow the Kubernetes/Helm rollback procedure using `helm rollback <release-name> 0` or `kubectl rollout undo deployment/<name>`. For database migration rollback check if there's a corresponding `V<n>__down` file in `/db/migrations/` and if `/db/migrations` points to the migration version. No specific rollback steps for Okta SCIM provisioning setup and DB crash are provided and hence would need to refer to KB-00016 for DB connection pool exhaustion and KB-00020 for rollback steps but no direct tickets match.", "cited_artifacts": ["KB-00015", "KB-00016", "KB-00020"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the user-profile service OOM crash, enable automatic heap dump on the JVM with the flags `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` and use `jmap -dump:format=b,file=/tmp/heap_$(date +%s).hprof <pid>` to capture the heap dump with `jmap -dump:format=b,file=/tmp/heap_$(date +%s).hprof <pid>` to identify the cause by running 'Leak Suspects' report in Eclipse MAT. For DB connections exhausted in the orders-service, use Prometheus to check the hikaricp_connections_active metric and the hikaricp_connections_max metric for connection pool saturation, and use `kill -3 <pid>` to get thread dumps and `pg_stat_activity` for PostgreSQL or `SHOW PROCESSLIST` for MySQL to detect idle connection holding. For rollback with DB migration concern in v5.0.0, refer to the Application Deployment Rollback Procedure in KB-00020 for Kubernetes/Helm rollback: `helm rollback <release-name> 0` or `kubectl rollout undo deployment/<name>`. Ensure rollback is done within 15 minutes and the previous revision is checked with `helm history` or `kubectl rollout history`. No specific information on Okta SCIM 2.0 issues or CrashLoopBackOff from the provided context. Escalation to support experts or additional documentation required for the other issues.", "cited_artifacts": ["KB-00015", "KB-00016", "KB-00020"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the user-profile service OOM crash, add `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` to the JVM startup options to enable heap dump on OOM with the flag `-XX:HeapDumpPath=/var/log/heapdumps/` to store the heap dumps at that location. Use `jmap -dump:format=b,file=/tmp/heap_$(date +%s).hprof <pid>` to capture a heap dump on the running process and open it with Eclipse MAT to analyze the heap dump, especially looking for the 'Problem Suspect' with the largest retained heap and drilling into the dominator tree for String interning or cache bloat issues. For the DB connection pool exhaustion, check Prometheus/Grafana metric `hikaricp_connections_active` and `hikaricp_connections_max` to confirm pool exhaustion and check the `pg_stat_activity` on the database side to find high 'idle' connection counts leading to pool saturation. For rollback in DB migration, the rollback is not described here directly, but for the manual rollback, use `helm rollback <release-name> 0` for Kubernetes/Helm rollback or `ln -sfn /opt/app/releases/<prev-version> /opt/app/current` for legacy VM rollback and restart the app to flush the pool, monitor the connection count. No specific rollback for DB migration rollback is mentioned in the retrieved context; refer to the KB-00020 for rollback procedure and configure the DB migration rollback if it exists manually. Escalation to other resources would be needed for specific DB migration rollback as it is not covered in the given context.", "cited_artifacts": ["KB-00015", "KB-00020", "KB-00016"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the user-profile service OOM-crashing, increase the `maximumSize` of the Guava Cache or Caffeine cache and add the JVM flag `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` with `jmap -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/heapdumps/ -XX:HeapDumpSize=100M -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/heapdumps/ -XX:HeapDumpSize=100M <pid>` to create a heap dump and use Eclipse MAT to analyze heap dumps. For the orders-service DB connections exhausted issue, check Prometheus/Grafana metric `hikaricp_connections_active` and `hikaricp_connections_max` to confirm the pool exhaustion and use `kill -3 <pid>` to find connection holders in thread dumps. No direct guideline for rollback for DB migrations is available from the provided context. Ensure a rollback for the DB migration issue involves checking `/db/migrations/` for a corresponding `V<n>__down` or use the `kubectl rollout undo deployment/<name>` or `helm rollback <release-name> 0` commands for Kubernetes deployments and VM rollback commands given. Escalation to support ticket management software or seeking additional context on DB rollback is advised. For rollback of application deployment, use `helm rollback <release-name> 0` or `kubectl rollout undo deployment/<name>` to roll back to the previous revision and verify with `kubectl rollout status deployment/<name>` and `kubectl get pods` to ensure readiness. No specific rollback steps for VM-based rollback and DB migration rollback from the context provided.", "cited_artifacts": ["KB-00015", "KB-00020", "KB-00016", "cited_artifacts: []"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the JVM heap exhaustion, add `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` to the JVM startup parameters to enable automatic heap dumps and use jmap -dump:format=b,file=/tmp/heap_$(date +%s).hprof to capture the heap dump on the running process to locate the 'Problem Suspect' with the largest retained heap using Eclipse MAT. For the orders-service DB connection exhaustion, check `Prometheus/Grafana` metrics for `hikaricp_connections_active` and `hikaricp_connections_max` to confirm the pool exhaustion and use `kill -3 <pid>` on the Linux application process to check for connection holders in `RUNNABLE` or `WAITING` state with JDBC/database stack frames. For rollback concern, use the Kubernetes/Helm rollback procedure: use `helm rollback <release-name> 0` to roll back to the previous version if using Helm or `kubectl rollout undo deployment/<name>` for non-Helm deployments within 15 minutes of the bad deployment. No specific rollback procedure for DB migration is listed in the provided context. Check `/db/migrations/` for a corresponding `V<n>__down` file in `/db/migrations/` for DB rollback and refer to the provided text for the basic steps on connection pool exhaustion. No direct reference to rollback for DB migrations; consult the DB migration rollback step from KB-00020 for a potential rollback strategy which is not comprehensive enough to fully resolve the issue. Escalation to experts or more detailed support documentation is recommended for DB migration rollback specifics.", "cited_artifacts": ["KB-00015", "KB-00016", "KB-00020"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For OOM crashes, ensure the Guava Cache or Caffeine in the user-profile service is configured with `maximumSize` to avoid heap exhaustion. For DB connections exhausted in the orders-service, ensure the pool size is configured correctly and monitor Prometheus/Grafana metrics for `hikaricp_connections_active` and `hikaricp_connections_max`. To rollback the release v5.0.0, use the Kubernetes/Helm rollback procedure: `helm rollback <release-name> 0` or `kubectl rollout undo deployment/<name>` to roll back to the previous revision if it’s within the 15-minute rollback window. For DB migration rollback, check `/db/migrations/` for a corresponding `V<n>__down` file in the migration directory to manually roll back the migration. No context about Okta SCIM provisioning rollback or CrashLoopBackOff issue is provided in the context. Escalation to support material is required for the CrashLoopBackOff root cause diagnosis as well as Okta SCIM configuration setup.", "cited_artifacts": ["KB-00015", "KB-00016", "KB-00020"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the OOM crash issue with Guava Cache or Caffeine unbounded cache leading to heap exhaustion, use `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` to enable and trigger a heap dump on the running user-profile service process. For DB connections exhaustion, ensure the connection pool is not saturated by checking Prometheus/Grafana metrics `hikaricp_connections_active = hikaricp_connections_max` and `hikaricp_connections_pending`. Increase the limits or use `-XX:MaxHeapSize` to limit heap size in the JVM. For rollback of a DB migration, check `/db/migrations/` for a corresponding `V<n>__down` file to roll back the migration, and follow the rollback procedure for the DB migration with `helm rollback <release-name> 0` or `kubectl rollback deployment/<name>`. Escalation to an expert for Okta SCIM provisioning as the details for rollback are not provided in the context. No reference from KB-00009 for Okta provisioning rollback.", "cited_artifacts": ["KB-00015", "KB-00016", "KB-00020"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the OOM crash in the user-profile service, add the JVM flags `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` to enable heap dumps and to force a clean restart. Use `jmap -dump:format=b,file=/tmp/heap_$(date +%s).hprof <pid>` to capture a heap dump and analyze with Eclipse MAT to look for the largest retained heap and the 'Problem Suspect' with the dominator tree (likely String interning or cache bloat). For the orders-service DB connections exhausted, check Prometheus/Grafana metric `hikaricp_connections_active` and `hikaricp_connections_max` to confirm pool exhaustion. If the pool is saturated, check thread dumps with `kill -3 <pid>` and the application logs for SQL queries or unclosed ResultSets to diagnose the cause. For rollback concern, since v5.0.0 included a DB migration and there’s no specific rollback procedure mentioned in the provided context for DB migrations, it's best to assume it's not covered in our provided data and refer to the 'Application Deployment Rollback Procedure' for Kubernetes/Helm rollback: use `helm rollback <release-name> 0` for fast rollback to the previous revision. For VM rollback: use `ln -sfn /opt/app/releases/<prev-version> /opt/app/current` and `systemctl restart <service>`. Monitor the metrics for the DB connection pool exhaustion and use the appropriate recovery steps from the provided DB connection pool exhaustion diagnostic steps. Escalation to IT Support or relevant documentation is advised for DB migration rollback. ", "cited_artifacts": ["KB-00015", "KB-00016", "KB-00020"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the heap memory issue in the checkout-service, add `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` to the JVM flags to automatically create heap dumps on OOM and force a clean restart. For the Redis eviction issue, ensure `maxmemory` is not too high by setting `redis-cli CONFIG SET maxmemory 850mb` to match the heap size. Use `redis-cli CONFIG GET maxmemory-policy` to ensure `maxmemory-policy` is set to `allkeys-lru` for better eviction. For session keys without expiry leading to Redis hit rate issues, add `spring.session.redis.cleanup-cron=0 * * * * *` to Spring Session configurations to ensure periodic session expiration is enforced. No specific context for Kubernetes CrashLoopBackOff or F5 health monitor issues. No extra steps for rollback procedure as provided context is not helpful for this issue. Escalation to experts or additional resources may be necessary for CrashLoopBackOff and F5 health monitor issues.", "cited_artifacts": ["KB-00019", "KB-00015"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the heap memory issue with Java in the checkout-service, add JVM flags `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` to ensure heap dumps are captured on OOM. For the Redis cache eviction issue, set `redis-cli CONFIG SET maxmemory 700mb` to allow up to 700MB of memory (90% of the server’s available memory). For Spring Session cache, add `spring.session.redis.cleanup-cron=0 * * * * *` to the application properties to enable Redis session cleanup. No direct fix or escalation for the heap memory is found in the provided context. Use `jmap -dump:format=b,file=/tmp/heap_$(date +%s).hprof <pid>` to capture heap dumps and `eclipse-mat` to analyze heap dumps and identify the cause of heap exhaustion. No direct solution for Redis cache eviction is found, but `redis-cli CONFIG SET maxmemory 700mb` can be used. The crashLoopBackOff root cause is described but not linked to the issue of high heap memory or Redis cache eviction; hence, use caution on applying these solutions to the service crash issue.", "cited_artifacts": ["KB-00019", "KB-00015"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the heap exhaustion issue in the JVM, add the JVM flags `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` to the startup configuration of your application and `-XX:MaxHeapSize=512m` to limit heap size to 512MB. For Spring Session cache overflow, set `spring.session.redis.cleanup-cron=0 * * * * *` to ensure the Redis cleanup schedule. Use the command `redis-cli CONFIG GET maxmemory-policy` to set the Redis eviction policy to `allkeys-lru` and ensure `maxmemory` is less than the used memory for proper memory management. No specific steps are provided for Redis keys without TTL or session keys exceeding their default lifetime of 14 days, but adding `spring.session.redis.cleanup-cron` helps in managing keys with no TTL by not storing them indefinitely. Escalation to support or a KB relevant to CrashLoopBackOff is not suggested from the provided info. Ensure no other specific tools like rollback or DB migration are needed as our focus is on the provided contexts. Watch out for the performance of the system with these changes and scale up as needed or seek more support for other aspects as mentioned.", "cited_artifacts": ["KB-00015", "KB-00019", "KB-00015"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the heap memory issue in the checkout-service v2.2, ensure that the Guava Cache or Caffeine cache is bounded with a `maximumSize` in the configuration to avoid unbounded cache overflow. For Redis eviction causing memory pressure, configure Redis eviction policy to `allkeys-lru` using `redis-cli CONFIG SET maxmemory-policy allkeys-lru` to avoid OOM by Redis by setting `maxmemory` lower than the used memory to avoid memory pressure. For Redis cache hit rate drops to 12%, ensure session keys are not stored indefinitely by Guava or Caffeine sessions without setting the maximum size or by enabling Spring Session cleanup with `spring.session.redis.cleanup-cron=0 * * * * *`. No direct reference is available for Spring Session timeout setting, but this should follow the correct Spring configurations. There is no context for dealing with the heap memory increase or the issue with Spring Session timeouts. No specific context matches the crash-loop-backoff issue from the retrieved contexts. Escalation to the appropriate expert or context is needed for that. Use the fixes for Redis eviction and Guava cache sizes for the given concerns. Escalation to support or another tool is required for Kubernetes crashLoopBackoff.", "cited_artifacts": ["KB-00019", "KB-00015"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the heap usage in the checkout-service from 800MB to 3.5GB and Redis cache hit rate dropping to 12%, add `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` to the JVM options to enable automatic heap dump with the command `jmap -dump:format=b,file=/tmp/heap_$(date +%s).hprof <pid>` to capture the heap dump and use Eclipse MAT to analyze it for the largest retained heap. For Redis eviction and cache misses causing high memory usage, set the eviction policy to `allkeys-lru` using `redis-cli CONFIG SET maxmemory-policy allkeys-lru` and ensure `spring.session.redis.cleanup-cron=0 * * * * *` is used in the Spring configuration to avoid storing session data forever. No specific escalation from the provided context is needed for the Kubernetes Pod CrashLoopBackOff or rollback procedures as these are not relevant to the mentioned issues. Escalation is not applicable as all necessary details are present in the given retrieved context.", "cited_artifacts": ["KB-00015", "KB-00019"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the heap memory issue, add the JVM flag `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError` to enable automatic heap dump on OOM and use `jmap -dump:format=b,file=/tmp/heap_$(date +%s).hprof <pid>` to capture the heap dump on a running process. For the Redis cache eviction issue, set Redis eviction policy to `allkeys-lru` using `redis-cli CONFIG SET maxmemory-policy allkeys-lru` and check the memory pressure with `redis-cli CONFIG GET maxmemory` and `redis-cli INFO memory`. The Spring session should be configured with `spring.session.redis.cleanup-cron=0 * * * * *` to ensure sessions do not persist forever. No explicit reference for session keys being infinite and increasing heap memory from the given context, but ensure sessions are bounded and use maximumSize for cache in Guava or Caffeine. Escalation to an expert or further search might be required for Kubernetes crash loop and F5 LTM issues. For Cache hit rate in Redis, check maxmemory in Redis configuration and adjust maxmemory and maxmemory-policy appropriately. No exact context for this issue. ", "cited_artifacts": ["KB-00019", "KB-00015"], "confidence": 0.5, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the heap memory issue in the checkout-service, add the JVM flags to enable heap dump on OOM: `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/ -XX:+ExitOnOutOfMemoryError`. Use `jmap -dump:format=b,file=/tmp/heap_$(date +%s).hprof <pid>` to capture a heap dump for the process. For Redis cache eviction issues, use `redis-cli CONFIG GET maxmemory-policy` and set to `allkeys-lru` and check with `redis-cli CONFIG SET maxmemory <maxsize>` to avoid eviction. For Spring Session timeout issues, add `spring.session.redis.cleanup-cron=0 * * * * *` to the `application.properties` to set the timeout period in days. No resources directly resolve the Kubernetes CrashLoopBackOff issue from the provided context, so we need to refer to the Kubernetes Rollback procedure for rollback mechanism if needed, but we don’t see direct steps and resources here for the crash loop issue. No direct reference to rollback procedure for VM rollback or DB migration rollback in the context provided. Escalation to these contexts is not recommended from the context given.", "cited_artifacts": ["KB-00015", "KB-00019", "spring.session.redis.cleanup-cron=0 * * * * *"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the checkout-service high heap usage to 3.5GB and Redis cache hit rate dropping to 12%, increase the JVM maximum heap size by adding `-Xmx1024m` to the startup command of the checkout-service application. For Redis eviction issues, configure the eviction policy to `allkeys-lru` using `redis-cli CONFIG SET maxmemory-policy allkeys-lru` and set the maximum memory Redis can use with `redis-cli CONFIG SET maxmemory 700mb` to avoid maxmemory from 900mb to 700mb to ensure Redis isn’t using more than necessary. For spring session key caching, add the following configuration in application.properties: `spring.session.redis.timeout=60m` to clear sessions after 60 minutes and `spring.session.redis.cleanup-cron=0 * * * * *` to enable Redis cleanup using cron. No direct advice is given for the heap memory issue, but heap dumps can be enabled with `-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/var/log/heapdumps/-XX:+ExitOnOutOfMemoryError` and a heap dump taken with `jmap -dump:format=b,file=/tmp/heap_$(date +%s).hprof <pid>` to analyze with Eclipse MAT. For Redis eviction: `redis-cli CONFIG GET maxmemory-policy` to ensure it is `allkeys-lru` and `redis-cli CONFIG SET maxmemory 700mb` to prevent Redis memory overuse. No mentioned solution for the crashloopbackoff as this is unrelated to the given issues and should be sought in another KB or not clear from the retrieved context.", "cited_artifacts": ["KB-00019", "KB-00015"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the issue where users on floor 4 (VLAN 10.40.0.0/24) are receiving APIPA addresses (169.254.x.x), the immediate mitigation strategy is to use the `show ip dhcp pool` command to confirm utilization and if utilization is over 95%, use `clear ip dhcp binding *` to force all clients to renew. If utilization is around 95%, increase the DHCP pool scope from /24 to /23 or add a new secondary pool to reduce the utilization and prevent scope exhaustion. For permanent fixes, extend the DHCP lease time from 8 days to 1 day using the command `ip dhcp pool CORP_WIFI / lease 1`. For avoiding DNS server issues, refer to the KB-00006 context for DHCP scope exhaustion and the KB-00006 context for the immediate mitigation steps. No reference to the other contexts are pertinent to the ticket.", "cited_artifacts": ["KB-00006"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For users on VLAN 40 (10.40.0.0/24) on floor 4 getting APIPA addresses (169.254.x.x), run `show ip dhcp pool` to confirm utilization and proceed with `clear ip dhcp binding *` to force all clients to renew if utilization is over 95%. If this does not resolve the issue and utilization remains high, execute `ip dhcp pool CORP_WIFI / lease 1` to reduce the lease time to 1 day or add a new secondary pool if /24 is full. For the DHCP scope exhaustion, there is an immediate mitigation step: if utilization is over 95%, use `show ip dhcp binding | include Expiry` to check for entries with expiry >7 days in the future and delete them with `show ip arp | include <subnet>` to remove orphaned entries and entries with 'Incomplete'. No need to escalate as the relevant context is provided. No references to KB-00012 or KB-00010 or KB-00011 are present.", "cited_artifacts": ["KB-00006"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the users on VLAN 40 getting APIPA addresses (169.254.x.x) due to a DHCP scope exhaustion, the immediate mitigation step is to use `show ip dhcp pool` to confirm utilization. If utilization is >95%, run `clear ip dhcp binding *` to force all clients to renew IP addresses within a maintenance window. To prevent scope exhaustion in the future, adjust the DHCP scope parameters: reduce the lease time from 8 days to 1 day with `ip dhcp pool CORP_WIFI / lease 1` or add a new secondary pool if the /24 scope is full. For a permanent solution, expand the scope from /24 to /23 or add a new secondary pool if needed. Do not perform the command `clear ip dhcp binding <specific-ip>` for targeted stale entries. There is no need to escalate as this can be resolved with the immediate mitigation or adjustments to the DHCP pool parameters as mentioned in KB-00006.", "cited_artifacts": ["KB-00006"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the DHCP scope exhaustion preventing users on VLAN 40 from getting proper IP addresses (169.254.x.x APIPA addresses), use the KB-00006 article for emergency recovery. Run the command `show ip dhcp pool` to confirm if the utilization is above 95% and proceed to `clear ip dhcp binding *` to force a re-lease of IP addresses. If this does not work, execute `clear ip dhcp binding *` within a maintenance window, or `clear ip dhcp binding <specific-ip>` to target specific stale entries. For permanent solutions, reduce the lease time to 1 day using `ip dhcp pool CORP_WIFI / lease 1` or expand the scope by increasing the subnet mask to /23 or adding another secondary pool. Ensure DHCP snooping is enabled to prevent rogue DHCP servers by running `ip dhcp snooping enable`. No other solutions are provided in the context and hence no escalation to other articles is required.", "cited_artifacts": ["KB-00006"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For users on VLAN 40 (10.40.0.0/24) getting APIPA addresses (169.254.x.x), it indicates a DHCP scope exhaustion issue where the DHCP pool utilization is >95%. Use the command `show ip dhcp pool` to confirm utilization and if it exceeds 95%, run `clear ip dhcp binding *` to force a global DHCP scope cleanup, reducing the scope to a shorter lease time with `ip dhcp pool CORP_WIFI / lease 1` or expanding the scope with `clear ip dhcp binding *` if /24 is full and reducing it to /23 or adding a new pool. No need for escalation as the context directly mentions the solution for APIPA addresses with DHCP scope exhaustion. Escalation to experts is advised for unclear issues.", "cited_artifacts": ["KB-00006"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the DHCP scope exhaustion on VLAN 40 leading to APIPA addresses (169.254.x.x) on floor 4, run `show ip dhcp pool` to confirm utilization and if it exceeds 95%, use `clear ip dhcp binding *` to force a client renewal and reduce the lease time from 8 days to 1 day with the command `ip dhcp pool CORP_WIFI / lease 1`. If this does not work, adding a new secondary pool with `ip dhcp pool CORP_WIFI-SEC / range 10.40.0.100-10.40.0.200` or expanding the scope to /23 with `ip dhcp pool CORP_WIFI / supernet 23` and using the provided recovery options for preventing future scope exhaustion by reducing the lease time or adding a new secondary pool. No specific steps are given for the ARP table or checking the 'Incomplete' entries with the `show ip arp` command in the retrieved context, so no reference from KB-00006 is needed for checking stale leases. No reference is found for other tickets from KB-00012, KB-00010, and KB-00011 relevant to the given issue.", "cited_artifacts": ["KB-00006"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the issue of users on VLAN 40 (10.40.0.0/24) on floor 4 getting APIPA addresses (169.254.x.x) due to DHCP scope exhaustion, use KB-00006 for emergency recovery: `show ip dhcp pool` to confirm utilization. If utilization is >95%, use `clear ip dhcp binding *` and if there are specific stale entries, use `clear ip dhcp binding <specific-ip>`. For permanent fixes, expand the scope by using `ip dhcp pool CORP_WIFI / lease 1` or by adding a new secondary pool if the current /24 is full, and switch to a /23. No escalations needed from the provided contexts.", "cited_artifacts": ["KB-00006"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the DHCP scope exhaustion issue where the DHCP pool is being utilized by more than 95% of the available addresses in the 10.40.0.0/24 VLAN (VLAN 40), you need to clear IP DHCP binding to force clients to renew and reduce the lease time from 8 days to 1 day using the command `show ip dhcp pool` to confirm utilization (utilization >95%). If specific IP address entries are stale and causing issues, clear these using `clear ip dhcp binding *` but be cautious and only do this in a maintenance window and if stale leases are the cause. For immediate mitigation within 5 minutes, use `clear ip dhcp binding *` and choose option A for a permanent fix by reducing the lease time from 8 days to 1 day: `ip dhcp pool CORP_WIFI / lease 1`. If the pool is full, consider expanding the scope to /23 or adding a secondary pool: `show ip dhcp pool` to confirm utilization, and for permanent fixes, use option B by expanding the scope to /23 or adding a secondary pool. No escalation needed as the context contains actionable steps for both the DHCP scope exhaustion and APIPA addresses on the subnet.", "cited_artifacts": ["KB-00006"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the API Gateway 504 timeout, check the upstream response time with `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` and use `curl -w '%{time_total}' -o /dev/null http://<upstream-host>:<port>/endpoint` to filter 504 responses directly. For Redis cache evictions, set Redis eviction policy to `redis-cli CONFIG SET maxmemory-policy allkeys-lru` to use allkeys-lru for caching. For the API Gateway timeout, adjust the timeout configuration in Kong with `proxy_read_timeout 60000`. For the Redis eviction, ensure `maxmemory` does not exceed 90% and add `redis-cli CONFIG SET maxmemory 600mb` (adjust according to usage) to ensure Redis memory usage does not exceed 600mb and use `maxmemory-policy allkeys-lru` to set cache eviction policy to least recently used. No direct solution from retrieved context is provided for the Kubernetes CrashLoopBackOff issue, so we escalate for this component. No further resolution steps are provided for database connection pool exhaustion, so we escalate for that too. Escalation will be needed for these two unresolved issues.", "cited_artifacts": ["KB-00019"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Redis cache eviction and key expiry issues, switch to `allkeys-lru` eviction policy in Spring Session by setting `spring.session.cache.type=redis` and `spring.session.cache.maxElementsInMemory=1000` in the application properties. For API gateway timeouts, the steps to address are: Identify the slow upstream by running `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` to find 504 gateway timeouts. Use `curl -w '%{time_total}' -o /dev/null http://<upstream-host>:<port>/endpoint` to bypass the gateway and check the response time and if it times out directly. Adjust timeout in KONG by setting `proxy_read_timeout 60000` for 60 seconds in the Kong configuration. For the DB connection pool exhaustion, ensure that the pool is not saturated by checking Prometheus metrics `hikaricp_connections_active` and `hikaricp_connections_max` and `hikaricp_connections_pending`. If the pool is saturated, it may be due to connection holders in the thread dumps or 'idle' connection counts on DB side. For the API gateway timeout, add `proxy_read_timeout 60000` to KONG config. For the Redis eviction, use `redis-cli CONFIG SET maxmemory 100mb` to set Redis memory limit to 100mb and configure `allkeys-lru` eviction policy with `spring.session.cache.maxElementsInMemory=1000`. For connection pool exhaustion, ensure `hikaricp_connections_max` does not exceed `hikaricp_connections_active` and check that there is no excessive 'idle' connection count on DB side by using `SHOW PROCESSLIST;` on the DB side. No specific escalations from the provided contexts are required for these issues.", "cited_artifacts": ["KB-00019", "KB-00018"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Redis cache eviction and key expiry issue, the eviction policy can be checked with `redis-cli CONFIG GET maxmemory-policy` to ensure it is using `allkeys-lru` for caching, and not `noeviction`. For the API gateway 504 timeout, the first step is to identify the slow upstream by checking the API gateway logs with `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n`. If the filter returns slow requests, the upstream request processing can be timed out by the API gateway, adjust the timeout configuration in Kong to `proxy_read_timeout 60000` to ensure no timeout occurs. For the API gateway timeout, test the upstream service directly using `curl -w '%{time_total}' -o /dev/null http://<upstream-host>:<port>/endpoint`. If the upstream timeouts as well, check the common causes in the API gateway timeout by checking upstream response times and ensuring the DB query is not the issue. The connection pool exhaustion can be confirmed in the application with Prometheus/Grafana metrics and application thread dumps to check `hikaricp_connections_active` and ensure the connection pool isn't being held by threads, setting `hikaricp_connections_max`. The Spring Session with Redis issue requires the key to have TTL, use `spring.session.redis.cleanup-cron=0 * * * * *` for a cron to clear expired sessions. No direct escalations from the given context can be suggested.", "cited_artifacts": ["KB-00019", "KB-00018"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Redis memory pressure causing evictions, use the KB-00019 guideline by setting `spring.session.redis.cleanup-cron=0 * * * * *` in the Spring configuration to enable Redis session cleanup and avoid storing sessions forever without a timeout. For the API gateway 504 timeout, identify the slow upstream service by filtering the API gateway access logs for 504s with `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` and bypass the gateway directly with `curl -w '%{time_total}' -o /dev/null http://<upstream-host>:<port>/endpoint`. If this times out, check the upstream directly by running `kill -3 <pid>` on the application thread dump to look for long-running queries or unclosed ResultSets leading to DB query regression and check `SHOW PROCESSLIST;` in the database side for idle connection count and connection 'active' status. No context directly links API Gateway 504 timeout to Redis memory pressure or vice versa, so these issues are independent; no escalation is required.", "cited_artifacts": ["KB-00019", "KB-00018"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Redis cache eviction issue, configure Redis eviction to 'allkeys-lru' with the command `redis-cli CONFIG SET maxmemory 70%` to prevent memory pressure. For API gateway 504 timeouts, use the steps from API Gateway 504 Timeout Troubleshooting: Filter access logs for 504s with `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` to identify the slow upstream. For upstream issues, use `curl -w '%{time_total}' -o /dev/null http://<upstream-host>:<port>/endpoint` to check if the upstream is directly causing timeouts. For connection pool exhaustion, ensure the `hikaricp_connections_max` in Prometheus/Grafana is not equal to `hikaricp_connections_active` to prevent pool exhaustion. No specific ticket from the provided context directly escalates to Kubernetes CrashLoopBackOff or Spring Session configuration, thus none are applicable for the given error. Escalation to additional tickets or context required for CrashLoopBackOff and Spring Session configuration issues.", "cited_artifacts": ["KB-00019", "KB-00018"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Redis cache eviction and key expiry issues, use the command `redis-cli CONFIG SET maxm` to set the maximum memory in bytes, ensuring Redis does not go over 90% used memory. For API gateway 504 timeouts, check the KONG access logs for 504s using `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` to identify which endpoint is the slow upstream. For API gateway timeout troubleshooting, run `curl -w '%{time_total}' -o /dev/null http://<upstream-host>:<port>/endpoint` to test the upstream service directly. For the checkpoint API checkout service, ensure session and cart keys in Spring Session do not store data forever by setting `spring.session.timeout` to an appropriate timeout value with `spring.session.redis.cleanup-cron=0 * * * * *` in the application properties. Escalation to Support Team or Technical Documentation is advised for any configuration or policy settings not covered in the above resources.", "cited_artifacts": ["KB-00017", "KB-00018", "KB-00019"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the API gateway 504 timeout issue, use the steps provided in KB-00018: Identify the slow upstream by checking API gateway access logs for 504s and filtering with `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` to find the upstream host and port using `curl -w '%{time_total}' -o /dev/null http://<upstream-host>:<port>/endpoint` to see if there is a timeout. For Redis eviction causing evictions, use KB-00019: Set the eviction policy to 'allkeys-lru' with `redis-cli CONFIG SET maxmemory-policy allkeys-lru` and enable cleanup with `spring.session.redis.cleanup-cron=0 * * * * *` in the Spring Session configuration. No concrete suggestions are provided for the API gateway timeout issue and Redis eviction issues are related, but not directly linked in the context. Escalation to support tickets or expert help might be necessary for resolving the API gateway timeout issue.", "cited_artifacts": ["KB-00018", "KB-00019"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Redis memory pressure causing evictions, set the eviction policy to `allkeys-lru` in Spring Session by adding `spring.session.redis.cleanup-cron=0 * * * * *` to the application properties and to prevent Redis from holding session keys without TTL, add `spring.session.timeout=600` to the properties to set a session timeout. For the API gateway 504 timeout issue, filter for 504s in the API gateway access logs with `grep 504 /var/log/kong/access.log | awk '{print $7, $9}' | sort -n` to find slow upstream services and use the `proxy_read_timeout 60000` command in the configuration to adjust the timeout on the Kong proxy. For the DB query regression leading to timeouts, use `explain plan` on slow queries and ensure no missing index exists. For connection pool exhaustion, check Prometheus/Grafana metric `hikaricp_connections_active` to confirm if the pool is saturated and check `hikaricp_connections_max` and `hikaricp_connections_pending` for saturation. The root cause of CrashLoopBackOff is memory limit too low for the Redis container in Kubernetes, fix by increasing the memory limit with `resources.limits.memory` and managing the Redis eviction with `redis-cli CONFIG SET maxmempolicy allkeys-lru` and `redis-cli CONFIG SET maxmemory 700mb`. Escalation to expert-level support or additional reference materials is advised for the BGP peer session troubleshooting guide as the context is insufficient for a direct fix.", "cited_artifacts": ["KB-00019", "KB-00018"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the issue with the Lenovo T16 fingerprint reader not being recognized as a FIDO2 authenticator, there seems to be no relevant information provided in the retrieved context to resolve the hardware-specific issue with the fingerprint reader. The provided contexts are for Okta SCIM provisioning, SAML 2.0 SSO, and Service Account Password Rotation which do not address the Lenovo T16 hardware fingerprint reader issue. Escalation to external resources or more specific context related to FIDO2 and fingerprint readers is required for this ticket.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the issue with the Lenovo T16 laptops not recognizing the built-in fingerprint reader as a FIDO2 authenticator, the Lenovo T16 hardware is likely related to the fingerprint reader and its FIDO2 support not being properly recognized by the system. This appears to be an issue with the hardware itself rather than an Okta or SAML configuration issue. There is no clear reference to a configuration issue in the given contexts for Okta SCIM or SAML configuration. Escalation to hardware documentation or specific authentication software configurations for Lenovo T16 might be needed for further resolution. No direct references to the Lenovo T16 hardware or fingerprint reader configurations in the provided contexts.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the FIDO2/WebAuthn passkey issue on Lenovo T16 laptops with the fingerprint reader not being recognized, there is no direct configuration or setup from the provided retrieved contexts that directly address the fingerprint reader as a FIDO2 authenticator. However, to ensure the hardware fingerprint reader is recognized as a FIDO2 authenticator on Lenovo T16 laptops, refer to the Microsoft documentation on recognizing fingerprint readers as FIDO2 authenticators, which is not present in the provided contexts. Escalation to Microsoft or FIDO2 community forums or a relevant FIDO2 guide would be needed. No specific ticket resolutions are provided in the retrieved context that directly answer the hardware identification requirement for FIDO2 authenticator on Lenovo T16 laptops.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Lenovo T16 laptop fingerprint reader not being recognized as a FIDO2 authenticator, refer to the KB-00010 article on SAML 2.0 SSO Configuration — IdP and SP Setup for setup and attribute mapping details, focusing on the attribute mapping for the FIDO2 passkey setup (attribute name: `id_token.claim.type` should map to the `assertion.claim_type` and `id_token.claim` values in Okta’s attribute mapping settings). The attribute type for the fingerprint reader is likely `fingerprint`, which you would map under `challenge.user.name` or `challenge.user.id` to align with the FIDO2 passkey requirements. Ensure the SP (Okta side) URL matches what Okta expects, and adjust the attribute mappings correctly in the Okta Admin > Applications > App > Provisioning tab. No additional resources from the provided contexts can help resolve the specific issue with the Lenovo fingerprint reader not being recognized as a FIDO2 authenticator.", "cited_artifacts": ["KB-00010"], "confidence": 0.1, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The issue with the Lenovo T16 laptops not recognizing the fingerprint reader as a FIDO2 authenticator is due to the built-in fingerprint reader not being recognized as a FIDO2 authenticator and not being properly integrated with the FIDO2 ecosystem. There’s no direct information provided about how to integrate a fingerprint reader into the FIDO2 authentication system on a Lenovo laptop, and thus, we can’t suggest a specific article or configuration to fix the issue based on the provided context. Escalation to expert advice or a relevant software library is recommended.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Lenovo T16 fingerprint reader not being recognized as a FIDO2 authenticator issue, refer to the Okta SCIM 2.0 Provisioning setup guide for creating a new integration in Okta Admin. Go to Applications > App > Provisioning tab and enable SCIM provisioning with the given steps. Use the attribute mapping for user lifecycle synchronization like 'userName' (email) mapped to 'email' in Okta and 'name.givenName' mapped to 'givenName' in the Okta attribute mapping. Ensure that the Bearer token is not expired and that the SCIM endpoint is enabled in Okta. No direct reference to FIDO2 or the fingerprint reader in the provided context, thus escalation to the Okta provisioning guide is necessary. No specific reference to fingerprint reader or FIDO2 failure from the provided contexts, hence no direct resolution found; refer to Okta SCIM guide for Okta Admin setup and attribute mapping steps only.", "cited_artifacts": ["KB-00009"], "confidence": 0.1, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The issue with the Lenovo T16 laptops not recognizing the built-in fingerprint reader as a FIDO2 authenticator could be due to a misconfigured FIDO2 setup on the Okta side for SSO. Ensure that Okta's FIDO2 settings are configured correctly in the SCIM provisioning setup. In Okta Admin: Applications > App > Provisioning tab > Enable SCIM provisioning. Ensure the SCIM connector base URL is `https://<your-app>/scim/v2/` and the Bearer token is correctly set up as per the setup instructions provided. No specific attribute mapping is mentioned in the Okta SCIM provisioning setup so no attribute mapping from the retrieved context can be referenced. Escalation to Okta support or Okta documentation for more details on FIDO2 configuration with Lenovo T16 fingerprint reader might be required.", "cited_artifacts": ["KB-00009"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Lenovo T16 laptop fingerprint reader issue with FIDO2 passkeys, you need to ensure that the fingerprint reader is recognized as a FIDO2 authenticator. However, the provided contexts do not directly provide a solution for this hardware-specific issue related to fingerprint readers and FIDO2 passkeys. There are no specific articles in the provided contexts that address this problem. Escalation to Okta SCIM 2.0 provisioning setup and Troubleshooting might be indirectly related since it addresses Okta integration but does not provide solutions for hardware devices. Hence, we cannot resolve this ticket with the given information.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The issue with the site-to-site VPN tunnel to the Singapore branch office dropping and reestablishing every 20-40 minutes is due to a mismatch in the MTU between the peer interfaces of the two routers in the branch office and the main office. Use the `show ip ospf neighbor` command to check if the remote router is in the INIT state and if both routers have consistent hello/dead intervals matching the subnet masks. For an MTU mismatch, ensure that the physical MTU of the branch office interface matches the main office interface. Use `show ip ospf` to check area flags for area mismatch. For the peer addresses in INIT state and inconsistent HELLO intervals, add `ip ospf mtu-ignore` on both interfaces in the branch office router. No specific resolution is provided in the retrieved context for the VPN tunnel flapping issue; refer to KB-00002 for MTU alignment and KB-00005 for ensuring consistency in the MTU and area flags. Escalation to expert support or additional context on the phases of the Phase 1 and Phase 2 mismatches are needed for further guidance on this aspect.", "cited_artifacts": ["KB-00002"], "confidence": 0.1, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Site-to-site VPN to branch issue, the most common issue seems to be an MTU mismatch between the two peers due to different MTU sizes on the interfaces leading to EXSTART/EXCHANGE states getting stuck. Use the command `show ip ospf neighbor detail` to check the state of the neighbors and ensure that they are in 2-WAY or EXCHANGE states. Ensure the MTU size matches on both routers and use the command `ip ospf mtu-ignore` on both interfaces if MTU is different. Check the area mismatch by using `show ip ospf neighbor detail` and ensuring the area flags on both routers are the same (non-stub). For the reestablishment after every 20-40 minutes, the network latency to Singapore (averaging 180ms) is within the range that should handle without major issues for MTU mismatch, but ensure that neither area mismatch nor hold-timer issues arise. Use debug commands like `debug ip ospf adj` for state check and `debug ip ospf` for area flag verification, and align the MTU between the peers by using `ip ospf mtu-ignore`. No specific reference from the above context directly addresses the hold timer or configuration mismatch, but this could be a secondary issue which should be ruled out with diagnostic commands for hold-timer and configuration hold-timer mismatch through `neighbor <ip> timers <keepalive> <hold>` and `clear ip ospf adj` to clear the hold-timer error. No direct reference to BGP is seen and no specific escalations mentioned in KBs for this issue, so it’s not an escalation case. Escalation to expert or additional context required for hold-timer mismatch or hold-timer log analysis.”", "cited_artifacts": ["KB-00002"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the site-to-site VPN to branch issue with adjacency failure in the OSPF protocol leading to MTU mismatch, use the 'align physical MTU or add `ip ospf mtu-ignore`' fix from KB-00002. For the reestablishment issue, since the described symptoms do not align with Cisco ISR Series addressing the phase1/phase2 parameter mismatch and DPD misconfiguration from KB-00005, and BGP peer session down from KB-00001 does not seem relevant due to the tunnel flap not being a network topology or configuration mismatch, but rather a parameter mismatch and DPD timer settings, consider that the WAN latency to Singapore (averaging 180ms) could indicate a network delay issue not addressed by the given FAQs. No direct resolution is provided for the congestion in branch reestablishing at 20-40 minutes and the tunnel flap, which might need additional context or expert advice on Phase 1/Phase 2 parameter mismatch.", "cited_artifacts": ["KB-00002"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "The issue with the site-to-site VPN tunnel dropping every 20-40 minutes and reestablishing on its own is due to an MTU mismatch between the interface on the branch router and the peer router at 198.51.100.22. Use the command `show ip ospf neighbor` and check for the state INIT or 2-WAY to identify if there's a mismatch with the HELLO intervals and the subnet masks. For the tunnel reestablishing after re-establishing, ensure the MTU on both interfaces are the same by running `show ip ospf mtu`. For potential area mismatch, check `show ip ospf` to see if both routers agree on the area flags as STUB or Nssa. There is no specific reference for the delay issue of the tunnel dropping and re-establishing, and the given steps for Phase 1 and Phase 2 are not directly applicable, so we address the MTU and area mismatch for this issue. No reference for API gateway timeout or IPSec Phase 2 algorithm mismatch steps provided.", "cited_artifacts": ["KB-00002"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the site-to-site VPN to branch that keeps dropping and reestablishing every 20-40 minutes, the issue could stem from an MTU mismatch causing EXSTART/EXCHANGE adjacency states to get stuck (OSPF adjacency failure). To align the MTU, use the command `show ip ospf neighbor detail` to check the HELLO and DEAD intervals and ensure they match the subnet mask. For area mismatch, use `show ip ospf` to ensure both routers agree on the area flags. The `ip ospf mtu-ignore` command can be used for MTU alignment. No specific reference in the retrieved context for resolving the flapping issue with IPSec IKEv2 or for API gateway timeout issues. Escalation to KB-0005 or local network analysis via tracing to the gateway is advised if these steps don’t work. Check the hold-timer in `show ip ospf neighbors detail` for a state like 'Idle' or '2-WAY' but not 'FULL'. Escalation to expert network advice on other factors (e.g., reevaluation of security configs if using BGP peer mismatch could be added after system checks).", "cited_artifacts": ["KB-00002"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the Site-to-site VPN to branch issue where the tunnel keeps dropping every 20-40 minutes, align the MTU between the interfaces of the branch router and the main office using the command `show ip ospf neighbor detail` to check for the state ‘INIT’ and ensure both routers have MTU aligned. Use `ip ospf mtu-ignore` on both interfaces if this is not successful. For the reestablishment, focus on the MTU discrepancy (since this happens every 20-40 minutes and involves reestablishment), but do not escalate to area-type mismatch as provided and noted. No direct steps align to parameter mismatch or Phase 1/Phase 2 config for the tunnel flapping. Escalation to the Log-check for inconsistent hold-timer intervals in the main router and setting them in the commands provided for MTU and area-type mismatch do not apply here. Thus, the troubleshooting guide for MTU between branches and reestablishment from misaligned MTU could be a resolution, but no direct reference is provided for the tunnel reestablishment issue, hence we might need additional reference. No direct steps for tunnel reestablishment from other provided documents.", "cited_artifacts": ["KB-00002"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the site-to-site VPN to branch that is dropping every 20-40 minutes due to MTU mismatch and area mismatch, ensure the MTU between the two routers is the same by checking with `show ip ospf neighbor detail` and `show ip ospf` for area flags. For area mismatch, ensure both routers agree on the stub/nssa flags in `show ip ospf` by checking `area <id> st`. For the peer session issue with the peer address not responding due to hold-timer mismatch, use `show ip ospf neighbors detail` and `show ip ospf neighbors` to ensure the hold time is within the keepalive time and to correct the hold-timer mismatch with `show ip ospf neighbors detail` to ensure 'BGP hold timer mismatch' and correct it with `neighbor <ip> timers <keepalive> <hold>`. No artifacts for the Phase 1 and Phase 2 algorithm or DPD issues as they are detailed in the IPSec troubleshooting for VPN tunnel flapping which is unrelated to this issue; no escalation is needed. Escalation tool not applicable.", "cited_artifacts": ["KB-00002", "KB-00001", "KB-00005"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the site-to-site VPN tunnel to the branch office that keeps dropping every 20-40 minutes, adjust the MTU consistency between the two peer interfaces by aligning their physical MTU and using `ip ospf mtu-ignore` on both interfaces (Step 2 from KB-00002). For the phase one parameter mismatch issue in the Phase 1 (IKE) and Phase 2 (IPSec) parameters which cause tunnel flapping, ensure both ends use identical parameters like encryption (AES-256), PRF (SHA-256), DH group (14 or 19), and lifetime (86400s), and adjust the DPD timers under high latency by setting `dpd 60 retry 5` (Step 2 & 3 from KB-00005). No direct resolution from the BGP peer session issue or API Gateway timeout issue is provided in the context. Escalation to expert or third-party support might be required for the reset interval issue and gateway timeout problem, respectively.", "cited_artifacts": ["KB-00002", "KB-00005"], "confidence": 0.4, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the EXSTART state in EXCHANGE between dist-01 and dist-02 due to MTU mismatch between the two routers, use the command `ip ospf mtu-ignore` on both interfaces to align the physical MTU. For area mismatch, ensure both routers agree on the `area <id> st` flag in `show ip ospf area <id>` and both agree on the `st` (Stub) or `nssa` (Not-So-Stub) area types. No need for escalation as the context provides steps for MTU and area mismatch resolutions. No specific KB references are provided for area-type mismatch resolution as it does not have a direct link from the given context.", "cited_artifacts": ["KB-00002"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the EXSTART adjacency issue in an OSPF adjacency between dist-01 and dist-02 due to a mismatch in MTU between the interfaces, use the command `ip ospf mtu-ignore` on both interfaces to align their MTU. For area-type mismatch, ensure both routers agree on the stub/nssa flags in `area <id> st` by checking the area flags with `show ip ospf` and ensure the area mismatch is addressed. There's no need for an escalation as the provided context explains the common issue and its resolution for the EXSTART adjacency in detail.", "cited_artifacts": ["KB-00002"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the EXSTART state issue in OSPF adjacency between dist-01 and dist-02 due to an MTU mismatch, use the `ip ospf mtu-ignore` command on both router interfaces to align the MTU or make sure the physical MTU matches between the peers. For area mismatch between the routers, ensure both are in non-stub area by checking `show ip ospf area <id>` and setting area flags to `area <id> nssa` for non-stub. No need to escalate as the solutions are available in the provided context under KB-00002 - OSPF Neighbor Adjacency Failure Investigation.", "cited_artifacts": ["KB-00002"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the EXSTART state stuck between dist-01 and dist-02 in the OSPF adjacencies, the MTU mismatch is the most common issue. Use the command `ip ospf mtu-ignore` on both interfaces of the dist-01 and dist-02 to align their physical MTU (or their MTU interval with `ip ospf mtu-ignore`). The area-type mismatch can be addressed by ensuring both routers agree on the stub/nssa flags in `area <id> st`. No specific tickets or fixes from the provided contexts address authentication issues or CLI commands for area type mismatches directly, hence they are not cited. Escalation to the network administrator for manual troubleshooting of area type mismatch based on the area ID in `show ip ospf` output is advised. No further tickets from the provided contexts provide step-by-step fixes for authentication or area type mismatches. No escalation to the base network troubleshooting context:", "cited_artifacts": ["KB-00002"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the EXSTART state stuck in OSPF adjacencies between dist-01 and dist-02, align the MTU between the interfaces of the two routers and ensure they are in the same area (non-stub vs. stub or non-stub). Use the command `ip ospf mtu-ignore` on both interfaces of dist-01 and dist-02 if the MTU differs from full MTU to prevent EXSTART from getting stuck (Step 2 from KB-0002). To prevent the area mismatch from causing adjacency, ensure they are both on the non-stub area by checking `show ip ospf` for area flags and making sure both routers agree on the `area <id> st` flags (Step 3 from KB-0002). Escalation to network administrator or network documentation is recommended for detailed troubleshooting and configuration of authentication, but this context does not provide a direct solution to MD5 key mismatch or validation of configuration for authentication or area type. No escalations are required based on provided context.", "cited_artifacts": ["KB-0002"], "confidence": 0.2, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the EXSTART state issue in the OSPF adjacencies between dist-01 and dist-02, the MTU mismatch is the primary cause. Use the command `ip ospf mtu-ignore` on both interfaces to align the physical MTU. If MTU is consistent but adjacencies remain in EXSTART, check if the area flags differ between the routers by running `show ip ospf` and ensuring both routers agree on the area flag (stub/nssa). No need for authentication issues as MD5 mismatch is not listed in the context. No need for steps for area-type mismatch or configuration check as it's not mentioned in the provided context. No need for escalation due to the direct MTU alignment solution available in the context.", "cited_artifacts": ["KB-00002"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the issue where OSPF adjacencies between dist-01 and dist-02 are stuck in EXSTART due to a mismatched MTU between the two interfaces, use the `ip ospf mtu-ignore` command on both interfaces to align the MTU. Ensure the subnet mask and hello/dead intervals match between the peers to prevent the EXSTART state. For area-type mismatch, ensure both routers agree on the stub/nssa flags in the `area <id> st` configuration in `show ip ospf`. No additional troubleshooting steps from the provided context can help resolve an area-type mismatch directly, thus further details need context or additional context not provided here. Escalation to network expert advice or a different KB might be required for precise area mismatch resolution.", "cited_artifacts": ["KB-00002"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the EXSTART adjacency issue between the dist-01 and dist-02 routers due to a mismatch in the MTU between the interfaces of both routers, the use of `ip ospf mtu-ignore` on both interfaces should resolve this state and align the MTUs between the peers to prevent the EXSTART adjacency state. For potential area-type mismatches, ensure both routers agree on the stub/nssa flags in the `area <id> st` command for area settings. No specific context or escalation is required from the provided retrieved contexts for authentication issues or router IDs as they do not relate to the EXSTART state issue with the MTU or area settings mentioned. No confidence level can be assigned as the context is specific to the MTU issue only.", "cited_artifacts": ["KB-00002"], "confidence": 0.3, "escalate": false}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "No direct runbook or solution for the BeyondCorp zero-trust access request for a new OT network segment using legacy protocols like Modbus and DNP3 exists in the provided context. There are no cited artifacts that align with the request for integrating an OT network with the BeyondCorp zero-trust access framework that are listed in the retrieved contexts. Escalation is required to find suitable runbooks or alternative solutions that could support such an integration for BeyondCorp zero-trust access with the given OT devices’ communication protocols using the BeyondCorp agent. No solution or runbooks can be recommended based on the available information.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "There is no direct runbook or step-by-step approach in the retrieved context to onboard a OT network segment with legacy protocols (Modbus, DNP3) for BeyondCorp zero-trust access. No runbook or remediation steps were provided for the specific requirement of integrating an OT network with BeyondCorp’s framework. Escalation to expert or BeyondCorp’s official guide is recommended for this issue.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For onboarding the manufacturing OT network segment to the BeyondCorp zero-trust access framework with legacy protocols (Modbus, DNP3) that are not compatible with the BeyondCorp agent, there is no direct runbook or solution from the provided context. No specific runbooks or runbooks from the given context can be used for this problem. Escalation to the BeyondCorp support or BeyondCorp documentation or BeyondCorp OT agent onboarding documentation for guidance on legacy protocol support is advised. No direct entry from the context can be used to resolve this ticket.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the BeyondCorp zero-trust access request for the manufacturing OT network segment with legacy protocols (Modbus, DNP3) that are not compatible with the BeyondCorp agent, there is no direct runbook or information available in the provided contexts that specifically addresses the integration of an OT network segment with BeyondCorp zero-trust access. The contexts available relate to DHCP scope exhaustion, DNS resolution, and TLS certificate renewal which do not apply to the OT network issue. Escalation to the BeyondCorp support or an OT runbook for BeyondCorp integration is required for this specific integration.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the BeyondCorp zero-trust access request for a new OT network segment with legacy protocols that are not compatible with the BeyondCorp agent, there is no specific runbook or solution provided in the retrieved contexts that match the exact problem. However, the provided KB-00014 on TLS Certificate Renewal for Internal Services might suggest an approach to manage TLS certificate updates for certain services, but it doesn’t address the OT network segment onboardment issue in the context of a zero-trust access request. Escalation to BeyondCorp support or documentation is required for a runbook on this specific use case.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the BeyondCorp zero-trust access request for a new OT network segment, there is no specific runbook or relevant information in the provided context that addresses the integration of OT devices using legacy protocols like Modbus and DNP3 into a BeyondCorp zero-trust access framework. No runbooks or clear guidance are found to bridge this integration or to secure OT devices with BeyondCorp. Escalation to BeyondCorp support or a BeyondCorp-specific runbook is advised.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```


Response:
```json
{"tool_name": "submit_resolution", "arguments": {"resolution": "For the BeyondCorp zero-trust access request for a new OT network segment using legacy protocols like Modbus and DNP3 that are not compatible with the BeyondCorp agent, there is no runbook or direct approach from the provided retrieved context. No specific runbook or steps can be extracted from the provided information for OT network integration into BeyondCorp. Escalation to BeyondCorp support or an OT-specific runbook for integration with BeyondCorp should be sought for this request.", "cited_artifacts": [], "confidence": 0.0, "escalate": true}}
```