Atlassian Intelligence Certification Interview Questions [2025]

AI-Powered Workflow Automation

1. How do you enable Atlassian Intelligence for Jira workflows?

• Activate AI features with jira ai enable in Jira UI.
• Create automation rules using jira automation create.
• Integrate Prometheus with jira integration add prometheus.
• Validate rules with jira automation list.
• Document configurations in Confluence for audits.
• Notify teams via Slack for updates.

This streamlines task automation, critical for certification.

2. What triggers AI actions in Jira?

Configure triggers with jira ai trigger create for issue updates. Validate with jira issue list for accuracy. Monitor events with Prometheus for insights. Document triggers in Confluence for reference. Notify teams via Slack for rapid response. Use aws cloudwatch list-metrics for cloud validation. This ensures automated responses, vital for certification.

3. Why use Atlassian Intelligence for task prioritization?

Prioritize tasks with jira ai priority set to predict bottlenecks. Validate with jira automation list. Monitor performance with Prometheus for insights. Document in Confluence for audits. Notify teams via Slack for coordination. This enhances efficiency, aligning with certification objectives.

4. When do you escalate critical issues in Atlassian Intelligence?

• Escalate with jira ai escalate for high-severity issues.
• Track escalations using jira issue list.
• Validate with jira ai check for accuracy.
• Document escalations in Confluence for traceability.
• Notify teams via Slack for rapid response.
• Use aws cloudtrail list-trails for audits.

This ensures timely escalation, key for certification.

5. Where are Atlassian Intelligence logs stored?

• Store logs in Jira’s platform for access.
• Use ELK stack via Kibana for analysis.
• Archive logs in Confluence for compliance.
• Validate with jira log list for correctness.
• Monitor log integrity with Prometheus for alerts.
• Notify teams via Slack for issues.

This ensures traceable logs, supporting certification.

6. Who manages Atlassian Intelligence workflows?

• DevOps engineers configure rules with jira ai create.
• Validate setups with jira issue list.
• Monitor actions with Prometheus for insights.
• Document workflows in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.

This ensures organized workflows, key for certification.

7. Which tools integrate with Atlassian Intelligence for automation?

• Prometheus for metrics-based triggers.
• Slack for real-time automation.
• Grafana for visualizing AI trends.
• ELK stack for log aggregation.
• Confluence for documentation.
• AWS CloudWatch for cloud alerts.

This enhances automation, critical for certification.

8. How do you troubleshoot Atlassian Intelligence failures?

Check rule status with jira ai check. Validate triggers using jira automation list. Monitor errors with Prometheus for insights. Document issues in Confluence for audits. Notify teams via Slack for coordination. Use aws cloudtrail list-trails for tracking. This restores functionality, essential for certification.

9. What reduces noise in Atlassian Intelligence alerts?

• Configure suppression with jira ai suppress.
• Prioritize actions with jira ai priority set.
• Validate with jira issue list for accuracy.
• Monitor noise with Prometheus for insights.
• Document rules in Confluence for traceability.
• Notify teams via Slack for coordination.

This ensures focused alerts, vital for certification.

10. Why use AI-driven runbooks in Confluence?

Create runbooks in Confluence for standardized AI workflows. Automate actions with jira ai automate. Validate with jira ai check. Monitor execution with Prometheus for insights. Document runbooks in Confluence for reference. Notify teams via Slack for coordination. Use aws cloudtrail list-trails for audits. This streamlines response, key for certification.

11. When do you validate Atlassian Intelligence configurations?

• Validate during setup with jira ai check.
• Monitor issues with Prometheus for alerts.
• Document validation in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.
• Check aws cloudwatch list-metrics for metrics.

This ensures stable setups, critical for certification.

12. Where do you monitor Atlassian Intelligence actions?

• Monitor via Jira’s AI dashboards.
• Use Grafana for visualizing trends.
• Store configurations in Confluence for reference.
• Validate with jira issue list for accuracy.
• Monitor actions with Prometheus for insights.
• Notify teams via Slack for issues.

This ensures real-time visibility, supporting certification.

13. Who prioritizes AI-driven actions in Jira?

• Team leads set priorities with jira ai priority set.
• Validate with jira issue list for accuracy.
• Monitor priorities with Prometheus for insights.
• Document rules in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures effective prioritization, key for certification.

14. How do you optimize Atlassian Intelligence for workflows?

• Streamline rules with jira ai update.
• Automate with jira ai automate for efficiency.
• Validate with jira ai check for correctness.
• Monitor performance with Prometheus for insights.
• Document optimizations in Confluence for traceability.
• Notify teams via Slack for coordination.

This improves efficiency, critical for certification.

15. What configures Atlassian Intelligence for high-priority tasks?

Configure rules with jira ai priority set for critical tasks. Validate with jira issue list. Monitor priorities with Prometheus for insights. Document configurations in Confluence for traceability. Notify teams via Slack for rapid response. This ensures prioritized handling, essential for certification.

Alerting and Notifications

16. How do you set up Slack notifications for Atlassian Intelligence?

• Add Slack integration with jira integration add slack.
• Configure channels in Jira UI for AI alerts.
• Validate with jira notification check.
• Monitor notifications with Prometheus for insights.
• Document setups in Confluence for traceability.
• Notify teams via Slack for coordination.

This ensures real-time alerts, critical for certification.

17. What configures Atlassian Intelligence for email alerts?

• Add email integration with jira integration add email.
• Configure rules with jira ai trigger create.
• Validate with jira notification check.
• Monitor alerts with Prometheus for insights.
• Document setups in Confluence for traceability.
• Notify teams via Slack for coordination.

This ensures reliable notifications, vital for certification.

18. Why reduce alert fatigue in Atlassian Intelligence?

Reducing alert fatigue improves team focus. Configure jira ai suppress for low-priority alerts. Prioritize with jira ai priority set. Monitor frequency with Prometheus for insights. Document rules in Confluence for traceability. Notify teams via Slack for coordination. This ensures efficient response, aligning with certification.

19. When do you test Atlassian Intelligence notifications?

• Test during setup with jira notification test.
• Validate with jira issue list for accuracy.
• Monitor tests with Prometheus for insights.
• Document results in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.

This ensures reliable alerting, critical for certification.

20. Where do you configure Atlassian Intelligence alert rules?

• Configure rules in Jira UI for AI thresholds.
• Use jira ai trigger create for programmatic setup.
• Validate with jira ai check for correctness.
• Monitor rules with Prometheus for insights.
• Document in Confluence for traceability.
• Notify teams via Slack for updates.

This ensures accurate alerting, supporting certification.

21. Who manages Atlassian Intelligence notification policies?

• SREs configure policies with jira ai create.
• Validate with jira ai check for accuracy.
• Monitor policies with Prometheus for insights.
• Document in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures effective notifications, key for certification.

22. Which integrations enhance Atlassian Intelligence notifications?

• Slack for real-time team alerts.
• Prometheus for metrics-driven notifications.
• ServiceNow for IT service integration.
• Grafana for visualizing AI trends.
• Confluence for documenting configurations.
• AWS SNS for cloud notifications.

This boosts alerting, aligning with certification.

23. How do you debug Atlassian Intelligence notification failures?

Check integration status with jira integration check. Validate rules using jira ai check. Monitor errors with Prometheus for insights. Document issues in Confluence for audits. Notify teams via Slack for coordination. Use aws cloudtrail list-trails for tracking. This restores notifications, critical for certification.

24. What prioritizes Atlassian Intelligence alerts?

• Set priorities with jira ai priority set for severity.
• Validate with jira issue list for accuracy.
• Monitor priorities with Prometheus for insights.
• Document rules in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures focused response, essential for certification.

25. Why monitor Atlassian Intelligence alert metrics?

Track alert frequency with jira ai metrics. Correlate with Prometheus for alerts. Visualize trends with Grafana for clarity. Document monitoring in Confluence for reference. Notify teams via Slack for issues. This ensures proactive alerting, vital for certification.

26. When do you update Atlassian Intelligence notification rules?

• Update rules with jira ai update for new thresholds.
• Validate with jira ai check for correctness.
• Monitor changes with Prometheus for insights.
• Document updates in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.

This ensures accurate notifications, critical for certification.

27. How do you integrate Atlassian Intelligence with Prometheus?

• Add Prometheus integration with jira integration add prometheus.
• Configure alert rules with jira ai trigger create.
• Validate with jira ai check for accuracy.
• Monitor alerts with Prometheus for insights.
• Document setups in Confluence for traceability.
• Notify teams via Slack for coordination.

This ensures metrics-driven alerting, vital for certification.

28. What suppresses low-priority alerts in Atlassian Intelligence?

Configure suppression rules with jira ai suppress to reduce noise. Validate with jira issue list. Monitor suppression with Prometheus for insights. Document rules in Confluence for traceability. Notify teams via Slack for coordination. This ensures focused alerts, essential for certification.

29. Why use Atlassian Intelligence for on-call notifications?

Schedule on-call rotations with jira schedule create. Notify via Slack or email with jira integration add. Validate with jira notification check. Monitor notifications with Prometheus for insights. Document schedules in Confluence for traceability. Notify teams via Slack for coordination. Use aws cloudtrail list-trails for audits. This ensures effective on-call management, key for certification.

Kubernetes Integration

30. How do you monitor Kubernetes with Atlassian Intelligence?

• Integrate Kubernetes with jira integration add kubernetes.
• Track pod metrics with jira ai trigger create.
• Validate with jira issue list for accuracy.
• Monitor alerts with Prometheus for insights.
• Document setups in Confluence for traceability.
• Notify teams via Slack for coordination.

This ensures Kubernetes observability, critical for certification.

31. What alerts on Kubernetes pod failures in Atlassian Intelligence?

Configure alerts with jira ai trigger create for pod crashes. Use kubectl describe pod for details. Monitor alerts with Prometheus for insights. Document triggers in Confluence for traceability. Notify teams via Slack for rapid response. This ensures proactive monitoring, vital for certification.

32. Why integrate Atlassian Intelligence with Kubernetes?

Integrating Atlassian Intelligence with Kubernetes enables real-time pod and node alerts. Use jira integration add kubernetes for setup. Validate with jira issue list. Monitor alerts with Prometheus for insights. Document in Confluence for traceability. Notify teams via Slack for coordination. This reduces downtime, aligning with certification.

33. When do you debug Kubernetes alerts in Atlassian Intelligence?

• Debug with jira ai check for issues.
• Check kubectl describe pod for pod events.
• Monitor errors with Prometheus for insights.
• Document findings in Confluence for traceability.
• Notify teams via Slack for resolution.
• Use aws cloudtrail list-trails for audits.

This ensures stable alerting, critical for certification.

34. Where do you store Kubernetes alert logs in Atlassian Intelligence?

• Store logs in Jira’s platform for access.
• Use ELK stack via Kibana for analysis.
• Archive logs in Confluence for audits.
• Validate with jira log list for correctness.
• Monitor log integrity with Prometheus for alerts.
• Notify teams via Slack for issues.

This ensures traceable alerts, supporting certification.

35. Who monitors Kubernetes in Atlassian Intelligence?

• SREs configure alerts with jira ai trigger create.
• Validate with jira issue list for accuracy.
• Monitor SREs with Prometheus for insights.
• Document in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures proactive monitoring, key for certification.

36. Which tools enhance Kubernetes alerting in Atlassian Intelligence?

• Prometheus for metrics-driven alerts.
• Grafana for visualizing Kubernetes trends.
• Slack for real-time notifications.
• ELK stack for pod log aggregation.
• Confluence for documenting configurations.
• AWS CloudWatch for cloud metrics.

This enhances observability, critical for certification.

37. How do you scale Atlassian Intelligence for Kubernetes workloads?

Adjust alert thresholds with jira ai update for dynamic workloads. Validate with jira ai check. Monitor performance with Prometheus for insights. Document scaling in Confluence for traceability. Notify teams via Slack for coordination. Use aws cloudwatch list-metrics for validation. This ensures robust alerting, critical for certification.

38. What detects Kubernetes misconfigurations in Atlassian Intelligence?

• Use jira ai trigger create to detect misconfigurations.
• Validate with kubectl describe pod for details.
• Monitor anomalies with Prometheus for insights.
• Document findings in Confluence for traceability.
• Notify teams via Slack for resolution.
• Use aws cloudtrail list-trails for audits.

This ensures stable clusters, critical for certification.

39. Why monitor Kubernetes events with Atlassian Intelligence?

Track events with jira ai track for insights. Correlate with Prometheus for alerts. Validate with kubectl get events for accuracy. Document monitoring in Confluence for reference. Notify teams via Slack for issues. This ensures proactive monitoring, vital for certification.

40. When do you update Kubernetes alert rules in Atlassian Intelligence?

• Update rules with jira ai update for new thresholds.
• Validate with jira ai check for correctness.
• Monitor changes with Prometheus for insights.
• Document updates in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.

This ensures accurate alerting, critical for certification.

41. How do you prioritize Kubernetes alerts in Atlassian Intelligence?

• Set priorities with jira ai priority set for severity.
• Validate with jira issue list for accuracy.
• Monitor priorities with Prometheus for insights.
• Document rules in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures focused response, essential for certification.

42. What optimizes Kubernetes monitoring in Atlassian Intelligence?

Configure lightweight alert rules with jira ai optimize. Validate with jira ai check. Monitor performance with Prometheus for observability. Document optimizations in Confluence for traceability. Notify teams via Slack for coordination. This improves efficiency, critical for certification.

Cloud Integrations

43. How do you integrate Atlassian Intelligence with AWS?

• Add AWS CloudWatch integration with jira integration add cloudwatch.
• Configure alerts with jira ai trigger create for EC2 metrics.
• Validate with jira issue list for accuracy.
• Monitor alerts with Prometheus for insights.
• Document setups in Confluence for traceability.
• Notify teams via Slack for coordination.

This ensures AWS observability, critical for certification.

44. What monitors Azure incidents in Atlassian Intelligence?

Integrate Azure Monitor with jira integration add azure. Configure alerts with jira ai trigger create for VM issues. Validate with jira issue list. Monitor alerts with Prometheus for insights. Document in Confluence for traceability. Notify teams via Slack for coordination. This ensures proactive Azure monitoring, vital for certification.

45. Why use Atlassian Intelligence for GCP alerting?

Integrate GCP Stackdriver with jira integration add stackdriver. Configure alerts with jira ai trigger create for GKE issues. Validate with jira issue list. Monitor alerts with Prometheus for insights. Document setups in Confluence for traceability. Notify teams via Slack for coordination. This ensures GCP reliability, aligning with certification.

46. When do you validate cloud integrations in Atlassian Intelligence?

• Validate with jira integration check for issues.
• Monitor issues with Prometheus for alerts.
• Document validation in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.
• Check aws cloudwatch list-metrics for metrics.

This ensures stable integrations, critical for certification.

47. Where do you store cloud alert logs in Atlassian Intelligence?

• Store logs in Jira’s platform for access.
• Use CloudTrail for AWS log tracking.
• Centralize logs with ELK via Kibana for analysis.
• Archive logs in Confluence for audits.
• Validate with jira log list for correctness.
• Monitor log integrity with Prometheus for alerts.

This ensures traceable alerts, supporting certification.

48. Who manages cloud alerts in Atlassian Intelligence?

• SREs configure integrations with jira integration add.
• Validate with jira issue list for accuracy.
• Monitor alerts with Prometheus for insights.
• Document in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures proactive monitoring, key for certification.

49. Which tools enhance cloud alerting in Atlassian Intelligence?

• AWS CloudWatch for EC2 and EKS monitoring.
• Azure Monitor for VM and AKS alerts.
• GCP Stackdriver for GKE alerts.
• Prometheus for metrics-driven notifications.
• Confluence for documenting configurations.
• Slack for team notifications.

This enhances observability, critical for certification.

50. How do you debug cloud alert failures in Atlassian Intelligence?

Check integration status with jira integration check. Validate rules using jira ai check. Monitor errors with Prometheus for insights. Document issues in Confluence for audits. Notify teams via Slack for coordination. Use aws cloudtrail list-trails for tracking. This restores cloud alerting, critical for certification.

51. What optimizes cloud monitoring in Atlassian Intelligence?

• Streamline alerts with jira ai optimize.
• Validate with jira ai check for correctness.
• Monitor performance with Prometheus for insights.
• Document optimizations in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This improves efficiency, critical for certification.

52. Why monitor cloud performance with Atlassian Intelligence?

Track EC2 and GKE metrics with jira ai trigger create. Correlate with Prometheus for alerts. Visualize trends with Grafana for clarity. Document monitoring in Confluence for reference. Notify teams via Slack for issues. This ensures proactive monitoring, vital for certification.

53. When do you update cloud alert rules in Atlassian Intelligence?

• Update rules with jira ai update for new thresholds.
• Validate with jira ai check for correctness.
• Monitor changes with Prometheus for insights.
• Document updates in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.

This ensures accurate alerting, critical for certification.

54. How do you prioritize cloud alerts in Atlassian Intelligence?

• Set priorities with jira ai priority set for severity.
• Validate with jira issue list for accuracy.
• Monitor priorities with Prometheus for insights.
• Document rules in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures focused response, essential for certification.

55. What detects cloud misconfigurations in Atlassian Intelligence?

Configure alerts with jira ai trigger create for misconfigurations. Validate with aws configservice describe-configuration-recorders. Monitor anomalies with Prometheus for insights. Document findings in Confluence for traceability. Notify teams via Slack for resolution. This ensures stable cloud setups, critical for certification.

56. Why use Atlassian Intelligence for cloud SLA compliance?

Track SLAs with jira ai sla monitor for compliance. Configure alerts with jira ai trigger create for breaches. Validate with jira issue list. Monitor SLAs with Prometheus for insights. Document in Confluence for traceability. Notify teams via Slack for coordination. Use aws cloudwatch list-metrics for validation. This ensures compliance, critical for certification.

CI/CD Pipeline Integration

57. How do you integrate Atlassian Intelligence with Jenkins?

• Add Jenkins integration with jira integration add jenkins.
• Configure alerts with jira ai trigger create for pipeline failures.
• Validate with jira issue list for accuracy.
• Monitor alerts with Prometheus for insights.
• Document setups in Confluence for traceability.
• Notify teams via Slack for coordination.

This ensures CI/CD observability, critical for certification.

58. What alerts on CI/CD failures in Atlassian Intelligence?

Configure alerts with jira ai trigger create for build failures. Validate with jira issue list. Monitor alerts with Prometheus for insights. Document triggers in Confluence for traceability. Notify teams via Slack for rapid response. This ensures proactive pipeline monitoring, vital for certification.

59. Why integrate Atlassian Intelligence with CI/CD pipelines?

Monitor pipelines with jira integration add gitlab. Configure alerts with jira ai trigger create for failures. Validate with jira issue list. Monitor alerts with Prometheus for insights. Document setups in Confluence for traceability. Notify teams via Slack for coordination. This reduces pipeline downtime, aligning with certification.

60. When do you debug CI/CD alerts in Atlassian Intelligence?

• Debug with jira ai check for issues.
• Check pipeline logs with jenkins logs view.
• Monitor errors with Prometheus for insights.
• Document findings in Confluence for traceability.
• Notify teams via Slack for resolution.
• Use aws cloudtrail list-trails for audits.

This ensures stable pipelines, critical for certification.

61. Where do you store CI/CD alert logs in Atlassian Intelligence?

• Store logs in Jira’s platform for access.
• Use ELK stack via Kibana for analysis.
• Archive logs in Confluence for audits.
• Validate with jira log list for correctness.
• Monitor log integrity with Prometheus for alerts.
• Notify teams via Slack for issues.

This ensures traceable alerts, supporting certification.

62. Who monitors CI/CD pipelines in Atlassian Intelligence?

• DevOps engineers configure alerts with jira ai trigger create.
• Validate with jira issue list for accuracy.
• Monitor alerts with Prometheus for insights.
• Document in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.

This ensures proactive monitoring, key for certification.

63. Which tools enhance CI/CD alerting in Atlassian Intelligence?

• Jenkins for pipeline failure alerts.
• GitLab for build status notifications.
• Prometheus for metrics-driven alerts.
• Grafana for visualizing pipeline trends.
• Confluence for documenting configurations.
• Slack for team notifications.

This enhances pipeline observability, critical for certification.

64. How do you optimize CI/CD monitoring in Atlassian Intelligence?

Streamline alerts with jira ai optimize. Validate with jira ai check. Monitor performance with Prometheus for insights. Document optimizations in Confluence for traceability. Notify teams via Slack for coordination. Use aws cloudwatch list-metrics for validation. This improves pipeline efficiency, critical for certification.

65. What prioritizes CI/CD alerts in Atlassian Intelligence?

• Set priorities with jira ai priority set for severity.
• Validate with jira issue list for accuracy.
• Monitor priorities with Prometheus for insights.
• Document rules in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures focused response, essential for certification.

66. Why monitor CI/CD performance with Atlassian Intelligence?

Track pipeline metrics with jira ai trigger create. Correlate with Prometheus for alerts. Visualize trends with Grafana for clarity. Document monitoring in Confluence for reference. Notify teams via Slack for issues. This ensures proactive monitoring, vital for certification.

67. When do you update CI/CD alert rules in Atlassian Intelligence?

• Update rules with jira ai update for new thresholds.
• Validate with jira ai check for correctness.
• Monitor changes with Prometheus for insights.
• Document updates in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.

This ensures accurate alerting, critical for certification.

68. How do you automate CI/CD alerts in Atlassian Intelligence?

• Configure alerts with jira ai trigger create for pipeline failures.
• Integrate with Jenkins using jira integration add jenkins.
• Validate with jira issue list for accuracy.
• Monitor alerts with Prometheus for insights.
• Document setups in Confluence for traceability.
• Notify teams via Slack for coordination.

This ensures automated monitoring, vital for certification.

69. What detects CI/CD pipeline issues in Atlassian Intelligence?

Configure alerts with jira ai trigger create for build issues. Validate with jira issue list. Monitor alerts with Prometheus for insights. Document findings in Confluence for traceability. Notify teams via Slack for resolution. This ensures proactive monitoring, critical for certification.

70. Why integrate Atlassian Intelligence with GitLab?

Add GitLab integration with jira integration add gitlab. Configure alerts with jira ai trigger create for pipeline failures. Validate with jira issue list. Monitor alerts with Prometheus for insights. Document setups in Confluence for traceability. Notify teams via Slack for coordination. Use aws cloudtrail list-trails for audits. This reduces pipeline downtime, vital for certification.

SLA Compliance

71. How do you ensure SLA compliance with Atlassian Intelligence?

• Track SLAs with jira ai sla monitor for uptime.
• Configure alerts with jira ai trigger create for breaches.
• Validate with jira issue list for accuracy.
• Monitor SLAs with Prometheus for insights.
• Document in Confluence for traceability.
• Notify teams via Slack for coordination.

This ensures compliance, critical for certification.

72. What tracks SLA breaches in Atlassian Intelligence?

Configure alerts with jira ai trigger create for SLA breaches. Validate with jira issue list. Monitor with Prometheus for insights. Document in Confluence for traceability. Notify teams via Slack for rapid response. This ensures proactive compliance, vital for certification.

73. Why monitor SLAs with Atlassian Intelligence?

Track SLAs with jira ai sla monitor to ensure uptime. Correlate with Prometheus for alerts. Visualize trends with Grafana for clarity. Document in Confluence for reference. Notify teams via Slack for issues. This ensures reliability, aligning with certification.

74. When do you validate SLA configurations in Atlassian Intelligence?

• Validate with jira ai check for SLA rules.
• Monitor breaches with Prometheus for alerts.
• Document validation in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.
• Check aws cloudwatch list-metrics for metrics.

This ensures accurate SLA tracking, critical for certification.

75. Where do you store SLA logs in Atlassian Intelligence?

• Store logs in Jira’s platform for access.
• Use ELK stack via Kibana for analysis.
• Archive logs in Confluence for audits.
• Validate with jira log list for correctness.
• Monitor log integrity with Prometheus for alerts.
• Notify teams via Slack for issues.

This ensures traceable SLA records, supporting certification.

76. Who manages SLA alerts in Atlassian Intelligence?

• SREs configure alerts with jira ai trigger create.
• Validate with jira issue list for accuracy.
• Monitor alerts with Prometheus for insights.
• Document in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures proactive SLA management, key for certification.

77. Which tools enhance SLA monitoring in Atlassian Intelligence?

• Prometheus for metrics-driven SLA monitoring.
• Grafana for visualizing SLA trends.
• Slack for real-time notifications.
• Confluence for documenting configurations.
• AWS CloudWatch for cloud SLA metrics.
• ELK stack for log aggregation.

This enhances SLA observability, critical for certification.

78. How do you debug SLA alert failures in Atlassian Intelligence?

Check rule status with jira ai check. Validate triggers using jira issue list. Monitor errors with Prometheus for insights. Document issues in Confluence for audits. Notify teams via Slack for coordination. Use aws cloudtrail list-trails for tracking. This restores SLA alerting, critical for certification.

79. What prioritizes SLA alerts in Atlassian Intelligence?

• Set priorities with jira ai priority set for severity.
• Validate with jira issue list for accuracy.
• Monitor priorities with Prometheus for insights.
• Document rules in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures focused SLA response, essential for certification.

80. Why use runbooks for SLA management in Atlassian Intelligence?

Create runbooks in Confluence for standardized SLA responses. Automate actions with jira ai automate. Validate with jira ai check. Monitor execution with Prometheus for insights. Document runbooks in Confluence for reference. Notify teams via Slack for coordination. This streamlines SLA management, key for certification.

81. When do you automate SLA alerts in Atlassian Intelligence?

• Automate alerts with jira ai trigger create for breaches.
• Validate with jira issue list for accuracy.
• Monitor alerts with Prometheus for insights.
• Document automation in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.

This ensures proactive SLA alerting, critical for certification.

82. Where do you visualize SLA trends in Atlassian Intelligence?

• Use Grafana for SLA trend visualization.
• Monitor metrics with jira ai sla monitor.
• Validate with jira issue list for accuracy.
• Document trends in Confluence for reference.
• Notify teams via Slack for issues.
• Use aws cloudwatch list-metrics for cloud insights.

This ensures clear SLA insights, supporting certification.

83. Who validates SLA compliance in Atlassian Intelligence?

• SREs validate with jira ai check for accuracy.
• Monitor compliance with Prometheus for insights.
• Document validation in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for metrics.
• Track audits with aws cloudtrail list-trails.

This ensures reliable compliance, key for certification.

84. How do you optimize SLA monitoring in Atlassian Intelligence?

Streamline alerts with jira ai optimize for efficient monitoring. Validate with jira ai check. Monitor performance with Prometheus for insights. Document optimizations in Confluence for traceability. Notify teams via Slack for coordination. Use aws cloudwatch list-metrics for validation. This improves SLA efficiency, critical for certification.

Security and Compliance

85. How do you secure Atlassian Intelligence integrations?

• Configure RBAC with jira ai rbac set for access control.
• Validate with jira issue list for accuracy.
• Monitor access with Prometheus for insights.
• Document security policies in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.

This ensures secure integrations, critical for certification.

86. What detects security vulnerabilities in Atlassian Intelligence?

Configure alerts with jira ai trigger create for vulnerabilities. Validate with jira issue list. Monitor with Prometheus for insights. Document findings in Confluence for traceability. Notify teams via Slack for resolution. Use aws configservice describe-configuration-recorders for checks. This ensures proactive security, vital for certification.

87. Why enforce compliance in Atlassian Intelligence?

Enforce compliance with jira ai sla monitor to meet standards. Validate with jira issue list. Monitor with Prometheus for insights. Document policies in Confluence for audits. Notify teams via Slack for coordination. This ensures regulatory adherence, aligning with certification.

88. When do you audit Atlassian Intelligence configurations?

• Audit with jira ai check for compliance.
• Track audits with aws cloudtrail list-trails.
• Monitor issues with Prometheus for alerts.
• Document audits in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures auditable configurations, critical for certification.

89. Where do you store security logs in Atlassian Intelligence?

• Store logs in Jira’s platform for access.
• Use CloudTrail for AWS log tracking.
• Centralize logs with ELK via Kibana for analysis.
• Archive logs in Confluence for audits.
• Validate with jira log list for correctness.
• Monitor log integrity with Prometheus for alerts.

This ensures traceable security logs, supporting certification.

90. Who manages security policies in Atlassian Intelligence?

• Security teams configure policies with jira ai create.
• Validate with jira issue list for accuracy.
• Monitor policies with Prometheus for insights.
• Document in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for validation.

This ensures robust security, key for certification.

91. Which tools enhance security in Atlassian Intelligence?

• AWS CloudTrail for audit logging.
• Prometheus for security alert monitoring.
• ELK stack for log analysis.
• Confluence for policy documentation.
• Slack for real-time security notifications.
• AWS Config for compliance checks.

This enhances security, critical for certification.

92. How do you handle zero-day vulnerabilities in Atlassian Intelligence?

Configure alerts with jira ai trigger create for zero-day issues. Validate with jira issue list. Monitor with Prometheus for insights. Document mitigation in Confluence for traceability. Notify teams via Slack for rapid response. Use aws configservice describe-configuration-recorders for checks. This ensures quick response, vital for certification.

93. What ensures secure API integrations in Atlassian Intelligence?

• Configure API tokens with jira ai token create.
• Validate with jira integration check for accuracy.
• Monitor API calls with Prometheus for insights.
• Document configurations in Confluence for traceability.
• Notify teams via Slack for issues.
• Use aws cloudtrail list-trails for audits.

This ensures secure APIs, critical for certification.

94. Why use RBAC in Atlassian Intelligence?

Implement RBAC with jira ai rbac set to control access. Validate with jira issue list. Monitor access with Prometheus for insights. Document policies in Confluence for traceability. Notify teams via Slack for coordination. This ensures secure access, aligning with certification.

95. When do you update security rules in Atlassian Intelligence?

• Update rules with jira ai update for new threats.
• Validate with jira ai check for correctness.
• Monitor changes with Prometheus for insights.
• Document updates in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudtrail list-trails for audits.

This ensures up-to-date security, critical for certification.

96. Where do you monitor security events in Atlassian Intelligence?

• Monitor via Jira’s security dashboards.
• Use Grafana for visualizing trends.
• Store logs in Confluence for reference.
• Validate with jira log list for accuracy.
• Monitor events with Prometheus for insights.
• Notify teams via Slack for issues.

This ensures real-time security visibility, supporting certification.

97. Who validates security compliance in Atlassian Intelligence?

• Security teams validate with jira ai check.
• Monitor compliance with Prometheus for insights.
• Document validation in Confluence for traceability.
• Notify teams via Slack for coordination.
• Use aws cloudwatch list-metrics for metrics.
• Track audits with aws cloudtrail list-trails.

This ensures compliant security, key for certification.

98. How do you automate security alerts in Atlassian Intelligence?

Configure alerts with jira ai trigger create for security events. Validate with jira issue list. Monitor alerts with Prometheus for insights. Document automation in Confluence for traceability. Notify teams via Slack for coordination. Use aws cloudtrail list-trails for audits. This ensures automated security, critical for certification.

Data Analytics and Insights

99. How do you leverage Atlassian Intelligence for data analytics?

• Enable analytics with jira ai analytics enable in Jira UI.
• Configure dashboards with jira ai dashboard create.
• Validate with jira issue list for accuracy.
• Monitor trends with Prometheus for insights.
• Document dashboards in Confluence for reference.
• Notify teams via Slack for updates.

This ensures data-driven insights, critical for certification.

100. What generates predictive insights in Atlassian Intelligence?

Use jira ai predict to forecast trends. Validate with jira issue list. Monitor predictions with Prometheus for insights. Document models in Confluence for traceability. Notify teams via Slack for coordination. Use aws cloudwatch list-metrics for validation. This enables predictive analytics, vital for certification.

101. Why use Atlassian Intelligence for team performance analytics?

Track metrics with jira ai metrics for team performance. Visualize with Grafana for clarity. Validate with jira issue list. Document in Confluence for reference. Notify teams via Slack for insights. Use aws cloudwatch list-metrics for validation. This enhances team efficiency, aligning with certification.