Kong Engineer Interview Questions with Answers [2025]

Core Kong Architecture

1. What is the primary role of Kong in API management?

Kong acts as an API gateway, routing requests to backend services while applying plugins for security, monitoring, and transformation. It integrates with cloud networking practices, Prometheus for metrics, and GitLab for CI/CD, ensuring scalable API orchestration in Kubernetes.

2. Why is Kong chosen for API gateways?

• Extensible plugin ecosystem.
• Efficient request routing.
• Prometheus metrics integration.
• Kubernetes deployment support.
• OAuth and ACL security.
• GitLab CI/CD compatibility.
• Compliance with standards.

3. When should Kong be used in microservices?

• Managing API traffic flows.
• Securing service endpoints.
• During Kubernetes scaling.
• Integrating observability tools.
• Automating gateway workflows.
• Troubleshooting API issues.
• Conducting team audits.

4. Where does Kong handle API requests?

Kong handles API requests in its proxy layer, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management to ensure reliable request processing.

5. Who oversees Kong gateway deployments?

DevOps engineers configure Kong nodes, SREs optimize performance, security specialists apply plugins, and auditors ensure compliance. They collaborate via Jira, with team leads managing deployments and executives monitoring metrics.

Periodic audits maintain gateway reliability.

6. Which Kong components are critical for operations?

• Proxy for request routing.
• Plugins for extended functionality.
• Prometheus for performance metrics.
• Grafana for visualization dashboards.
• GitLab for configuration versioning.
• Database for state management.
• Logs for compliance tracking.

7. How does Kong manage traffic routing?

Kong manages traffic routing using routes and services, applying plugins for load balancing and rate limiting, integrated with Prometheus for metrics, Grafana for visualization, and GitLab for CI/CD.

8. What if Kong fails to route traffic correctly?

• Verify route configurations.
• Check service endpoint validity.
• Inspect plugin conflicts.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Explore network protocols to optimize Kong routing.

9. Why do Kong routes cause performance delays?

• Incorrect route matching logic.
• Plugin processing overheads.
• Kubernetes namespace conflicts.
• Compliance restrictions on routes.
• Network latency in routing.
• Untracked analytics for delays.
• Inconsistent configuration reviews.

10. When should Kong routes be optimized?

• Scaling API traffic volumes.
• During microservices updates.
• Validating Kubernetes performance.
• Integrating observability tools.
• Automating route workflows.
• Troubleshooting latency issues.
• Conducting team audits.

11. Where does Kong store route configurations?

Kong stores route configurations in its database or Kubernetes CRDs, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management.

12. Who configures Kong routing?

DevOps engineers set up routes, SREs optimize performance, security specialists enforce plugins, and auditors review compliance. They collaborate via Jira, with team leads overseeing configurations and executives monitoring metrics.

Regular audits ensure routing reliability.

13. Which Kong features enhance routing?

• Routes for path-based matching.
• Services for backend integration.
• Prometheus for routing metrics.
• Grafana for visualization dashboards.
• GitLab for route versioning.
• Plugins for routing extensions.
• Logs for compliance tracking.

14. How does Kong handle route conflicts?

Kong handles route conflicts by prioritizing matching rules and validating configurations, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for CI/CD.

15. What if Kong routes cause API errors?

• Verify route priority settings.
• Check service endpoint mappings.
• Inspect plugin interference.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Learn about scalable network designs to improve routing.

Plugin Development and Customization

16. Why do Kong plugins fail to execute?

• Incorrect Lua script syntax.
• Missing plugin dependencies.
• Kubernetes namespace mismatches.
• Compliance restrictions on plugins.
• Network latency in execution.
• Untracked analytics for failures.
• Inconsistent plugin reviews.

17. When should Kong plugins be customized?

• Extending routing functionality.
• Implementing custom security.
• During Kubernetes upgrades.
• Integrating observability tools.
• Automating plugin workflows.
• Troubleshooting plugin issues.
• Conducting team audits.

18. Where are Kong plugins executed?

Kong executes plugins in the proxy layer, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management to ensure efficient processing.

19. Who develops Kong plugins?

DevOps engineers write Lua plugins, SREs optimize performance, security specialists enforce compliance, and auditors review setups. They collaborate via Jira, with team leads overseeing development and executives monitoring metrics.

Regular audits ensure plugin reliability.

20. Which Kong plugin features are critical?

• Lua for custom logic.
• Plugin schemas for validation.
• Prometheus for plugin metrics.
• Grafana for visualization dashboards.
• GitLab for plugin versioning.
• API for automated plugin tasks.
• Logs for compliance tracking.

21. How does Kong support plugin development?

Kong supports plugin development using Lua for custom logic, extending routing and security, with integration to Prometheus for metrics, Grafana for visualization, and GitLab for CI/CD.

22. What if Kong plugins cause performance degradation?

• Verify Lua script optimizations.
• Check plugin execution order.
• Inspect resource constraints.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Explore logical addressing to enhance plugin networking.

23. Why do Kong plugins impact API latency?

• Complex Lua script execution.
• High plugin processing loads.
• Kubernetes resource limits.
• Compliance restrictions on plugins.
• Network latency in calls.
• Untracked analytics for degradation.
• Inconsistent plugin reviews.

24. When should Kong plugin performance be tuned?

• Scaling plugin workloads.
• During gateway configuration updates.
• Validating Kubernetes performance.
• Integrating observability tools.
• Automating plugin workflows.
• Troubleshooting latency issues.
• Conducting team audits.

25. Where does Kong store plugin configurations?

Kong stores plugin configurations in its database or Kubernetes CRDs, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management.

26. Who tunes Kong plugin performance?

SREs optimize Lua scripts, DevOps engineers configure plugins, security specialists enforce policies, and auditors review compliance. They collaborate via Jira, with team leads overseeing tuning and executives monitoring metrics.

Regular audits ensure plugin efficiency.

27. Which tools support Kong plugin development?

• Lua for custom logic.
• Plugin schemas for validation.
• Prometheus for plugin metrics.
• Grafana for visualization dashboards.
• GitLab for plugin versioning.
• API for automated plugin tasks.
• Logs for compliance tracking.

28. How does Kong handle plugin conflicts?

Kong handles plugin conflicts by prioritizing execution order and validating schemas, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for CI/CD.

29. What if Kong plugins fail to load?

• Verify Lua script syntax.
• Check dependency configurations.
• Inspect Kubernetes namespaces.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Learn about secure-by-design principles for plugin security.

Security and Authentication

30. Why do Kong ACLs fail to enforce access?

• Misconfigured consumer groups.
• Incorrect role assignments.
• Kubernetes namespace conflicts.
• Compliance restrictions on ACLs.
• Network latency in enforcement.
• Untracked analytics for failures.
• Inconsistent ACL reviews.

31. When should Kong ACLs be configured?

• Securing API endpoints.
• Implementing role-based access.
• During Kubernetes upgrades.
• Integrating observability tools.
• Automating ACL workflows.
• Troubleshooting access issues.
• Conducting team audits.

32. Where does Kong enforce ACL policies?

Kong enforces ACL policies in the proxy layer, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management to ensure secure access.

33. Who configures Kong ACLs?

Security engineers configure ACL plugins, SREs optimize enforcement, DevOps specialists manage consumers, and auditors review compliance. They collaborate via Jira, with team leads overseeing configurations and executives monitoring metrics.

Regular audits maintain ACL reliability.

34. Which Kong plugins support ACLs?

• ACL plugin for access control.
• Consumer groups for roles.
• Prometheus for ACL metrics.
• Grafana for visualization dashboards.
• GitLab for plugin versioning.
• API for automated ACL tasks.
• Logs for compliance tracking.

35. How does Kong implement OAuth for authentication?

Kong implements OAuth using the OAuth2 plugin for token validation, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for CI/CD to secure API access.

36. What if Kong OAuth fails to authenticate?

• Verify token validation rules.
• Check OAuth provider connectivity.
• Inspect plugin configurations.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Explore cloud security practices to enhance OAuth configurations.

37. Why does Kong OAuth cause authentication delays?

• Misconfigured token endpoints.
• Invalid client credentials.
• Kubernetes namespace conflicts.
• Compliance restrictions on OAuth.
• Network latency in validation.
• Untracked analytics for delays.
• Inconsistent configuration reviews.

38. When should Kong OAuth be optimized?

• Scaling authentication workloads.
• During security policy updates.
• Validating Kubernetes performance.
• Integrating observability tools.
• Automating OAuth workflows.
• Troubleshooting token issues.
• Conducting team audits.

39. Where does Kong validate OAuth tokens?

Kong validates OAuth tokens in the proxy layer, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management to ensure secure authentication.

40. Who configures Kong OAuth plugins?

Security engineers configure OAuth plugins, SREs optimize validation, DevOps specialists manage integrations, and auditors review compliance. They collaborate via Jira, with team leads overseeing configurations and executives monitoring metrics.

Regular audits maintain OAuth reliability.

41. Which Kong OAuth features enhance security?

• Token validation for access.
• Client credential management.
• Prometheus for OAuth metrics.
• Grafana for visualization dashboards.
• GitLab for plugin versioning.
• API for automated OAuth tasks.
• Logs for compliance tracking.

42. How does Kong integrate with external identity providers?

Kong integrates with external identity providers using OAuth2 and OIDC plugins, validating tokens and enforcing access, with Prometheus for metrics and GitLab for CI/CD.

43. What if Kong identity provider integration fails?

• Verify OIDC configuration settings.
• Check provider endpoint connectivity.
• Inspect plugin configurations.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Learn about Prometheus monitoring to track identity issues.

Observability and Monitoring

44. Why does Kong observability data lack accuracy?

• Misconfigured Prometheus scrape jobs.
• Plugin metric export errors.
• Kubernetes namespace mismatches.
• Compliance restrictions on telemetry.
• Network latency affecting data.
• Untracked analytics for inaccuracies.
• Inconsistent configuration reviews.

45. When should Kong observability be configured?

• Monitoring API performance metrics.
• During gateway deployment updates.
• Validating Kubernetes performance.
• Integrating Prometheus metrics.
• Automating observability workflows.
• Troubleshooting data issues.
• Conducting team audits.

46. Where does Kong collect observability data?

Kong collects observability data from proxy and plugin metrics, integrating with Prometheus for collection, Grafana for visualization, and GitLab for configuration management.

47. Who configures Kong observability tools?

SREs configure Prometheus and Grafana, DevOps engineers collect metrics, security specialists enforce log policies, and auditors review compliance. They collaborate via Jira, with team leads overseeing setups and executives monitoring metrics.

Periodic audits ensure observability reliability.

48. Which Kong features support observability?

• Plugin metrics for telemetry.
• Prometheus for data collection.
• Grafana for visualization dashboards.
• Kubernetes for workload telemetry.
• API for automated observability tasks.
• GitLab for configuration versioning.
• Logs for compliance tracking.

49. How does Kong integrate with Prometheus?

Kong integrates with Prometheus by exporting plugin and proxy metrics via endpoints, enabling scrape jobs, with Grafana for visualization and GitLab for CI/CD.

50. What if Kong observability data is delayed?

• Verify Prometheus scrape intervals.
• Check plugin metric exports.
• Inspect Kubernetes connectivity.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Explore Grafana visualization for observability dashboards.

51. Why does Kong telemetry collection fail?

• Incomplete Prometheus configurations.
• Plugin metric export errors.
• Kubernetes pod misconfigurations.
• Compliance restrictions on telemetry.
• Network latency affecting data.
• Untracked analytics for failures.
• Inconsistent configuration reviews.

52. When should Kong telemetry be optimized?

• Tracking API performance metrics.
• During gateway configuration updates.
• Validating Kubernetes performance.
• Integrating Prometheus metrics.
• Automating telemetry workflows.
• Troubleshooting data issues.
• Conducting team audits.

53. Where does Kong send telemetry data?

Kong sends telemetry data to Prometheus for metrics and Grafana for visualization, integrating with GitLab for configuration management and Kubernetes for workload monitoring.

54. Who manages Kong telemetry tools?

SREs manage Prometheus and Grafana, DevOps engineers collect telemetry, security specialists enforce log policies, and auditors review compliance. They collaborate via Jira, with team leads overseeing setups and executives monitoring metrics.

Regular audits ensure telemetry accuracy.

55. Which integrations enhance Kong observability?

• Prometheus for metric collection.
• Grafana for visualization dashboards.
• Kubernetes for workload telemetry.
• Plugin metrics for API insights.
• API for automated telemetry tasks.
• GitLab for configuration versioning.
• Logs for compliance tracking.

56. How does Kong handle observability conflicts?

Kong handles observability conflicts by validating metric exports and resolving plugin issues, integrating with Prometheus for diagnostics and GitLab for CI/CD.

57. What if Kong telemetry data is inconsistent?

• Verify metric export settings.
• Check plugin configurations.
• Inspect Kubernetes namespaces.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Learn about SRE practices for observability tuning.

Multi-Cloud API Deployments

58. Why does Kong fail in multi-cloud environments?

• Misconfigured cross-cloud routing.
• Plugin synchronization issues.
• Kubernetes namespace conflicts.
• Compliance restrictions on gateways.
• Network latency across clouds.
• Untracked analytics for failures.
• Inconsistent configuration reviews.

59. When should Kong be used for multi-cloud APIs?

• Orchestrating cross-cloud services.
• Securing multi-cloud endpoints.
• During compliance-driven audits.
• Integrating Prometheus metrics.
• Automating gateway workflows.
• Troubleshooting cloud issues.
• Validating with team audits.

60. Where does Kong deploy multi-cloud nodes?

Kong deploys multi-cloud nodes in cloud-specific clusters, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management.

61. Who configures Kong for multi-cloud?

Cloud architects configure nodes, SREs optimize performance, security specialists enforce plugins, and auditors review compliance. They collaborate via Jira, with team leads overseeing configurations and executives monitoring metrics.

Regular audits maintain multi-cloud reliability.

62. Which Kong features support multi-cloud?

• Nodes for cloud-specific routing.
• Plugins for multi-cloud extensions.
• Prometheus for delivery metrics.
• Grafana for visualization dashboards.
• GitLab for configuration versioning.
• Database for state synchronization.
• Logs for compliance tracking.

63. How does Kong handle multi-cloud load balancing?

Kong handles multi-cloud load balancing using upstreams and targets, integrating with Prometheus for metrics and GitLab for CI/CD to distribute traffic across clouds.

64. What if Kong load balancing causes uneven traffic?

• Verify upstream configurations.
• Check target health checks.
• Inspect plugin interference.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Explore multi-cloud strategy for load balancing.

65. Why does Kong load balancing fail?

• Misconfigured upstream targets.
• Health check misconfigurations.
• Kubernetes namespace conflicts.
• Compliance restrictions on balancing.
• Network latency in distribution.
• Untracked analytics for failures.
• Inconsistent configuration reviews.

66. When should Kong load balancing be tuned?

• Handling API traffic spikes.
• During multi-cloud migrations.
• Validating Kubernetes performance.
• Integrating observability tools.
• Automating balancing workflows.
• Troubleshooting uneven distribution.
• Conducting team audits.

67. Where does Kong apply load balancing?

Kong applies load balancing in the proxy layer, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management.

68. Who tunes Kong load balancing?

SREs tune upstream configurations, DevOps engineers manage targets, security specialists enforce policies, and auditors review compliance. They collaborate via Jira, with team leads overseeing tuning and executives monitoring metrics.

Regular audits ensure balancing reliability.

69. Which Kong tools support load balancing?

• Upstreams for target management.
• Health checks for availability.
• Prometheus for balancing metrics.
• Grafana for visualization dashboards.
• GitLab for configuration versioning.
• Plugins for balancing extensions.
• Logs for compliance tracking.

70. How does Kong ensure compliance in multi-cloud?

Kong ensures compliance by logging requests and integrating with audit tools, using Prometheus for metrics, Grafana for visualization, and GitLab for versioning.

71. What if Kong violates compliance requirements?

• Verify log export configurations.
• Check plugin compliance rules.
• Inspect Kubernetes namespaces.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Explore incident management for compliance issues.

Troubleshooting and Diagnostics

72. Why do Kong gateways cause performance issues?

• Misconfigured plugin logic.
• High request processing loads.
• Kubernetes resource constraints.
• Compliance restrictions on gateways.
• Network latency in routing.
• Untracked analytics for issues.
• Inconsistent configuration reviews.

73. When should Kong performance be debugged?

• Resolving latency spikes.
• During gateway configuration updates.
• Validating Kubernetes performance.
• Integrating observability tools.
• Automating debug workflows.
• Troubleshooting API issues.
• Conducting team audits.

74. Where does Kong log diagnostic data?

Kong logs diagnostic data in the proxy layer, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management.

75. Who debugs Kong performance issues?

SREs debug plugin configurations, DevOps engineers validate setups, security specialists review policies, and auditors ensure compliance. They collaborate via Jira, with team leads overseeing debugging and executives monitoring metrics.

Regular audits ensure troubleshooting effectiveness.

76. Which Kong tools support troubleshooting?

• Proxy logs for diagnostics.
• Prometheus for performance metrics.
• Grafana for visualization dashboards.
• Plugins for debug logic.
• API for automated debug tasks.
• GitLab for configuration versioning.
• Logs for compliance tracking.

77. How does Kong handle performance conflicts?

Kong handles performance conflicts by analyzing logs and metrics, integrating with Prometheus for diagnostics, Grafana for visualization, and GitLab for versioning.

78. What if Kong performance metrics are inconsistent?

• Verify metric export settings.
• Check plugin configurations.
• Inspect Kubernetes namespaces.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Explore incident response tools for troubleshooting.

79. Why do Kong metrics cause conflicts?

• Inconsistent metric exports.
• Misconfigured plugin metrics.
• Kubernetes namespace conflicts.
• Compliance restrictions on metrics.
• Network latency affecting data.
• Untracked analytics for conflicts.
• Inconsistent metric reviews.

80. When should Kong performance conflicts be resolved?

• After metric export updates.
• During gateway configuration updates.
• Validating Kubernetes performance.
• Integrating observability tools.
• Automating conflict resolution.
• Troubleshooting metric issues.
• Conducting team audits.

81. Where does Kong resolve performance conflicts?

Kong resolves performance conflicts in proxy logs, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management.

82. Who resolves Kong performance conflicts?

SREs resolve metric conflicts, DevOps engineers validate plugins, security specialists review policies, and auditors ensure compliance. They collaborate via Jira, with team leads overseeing resolutions and executives monitoring metrics.

Regular audits maintain conflict-free performance.

83. Which tools support Kong conflict resolution?

• Proxy logs for diagnostics.
• Prometheus for conflict metrics.
• Grafana for visualization dashboards.
• Plugins for performance alignment.
• API for automated conflict tasks.
• GitLab for configuration versioning.
• Logs for compliance tracking.

84. How does Kong optimize API performance?

Kong optimizes API performance using plugins for caching and rate limiting, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for CI/CD.

85. What if Kong API performance degrades?

• Verify plugin caching settings.
• Check rate limiting rules.
• Inspect Kubernetes resources.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Explore monitoring and security for performance diagnostics.

Scalability and High Availability

86. Why do Kong gateways face scalability issues?

• High request processing volumes.
• Misconfigured plugin logic.
• Kubernetes resource constraints.
• Compliance restrictions on scaling.
• Network latency in routing.
• Untracked analytics for bottlenecks.
• Inconsistent configuration reviews.

87. When should Kong scalability be optimized?

• Scaling high-traffic APIs.
• During gateway configuration updates.
• Validating Kubernetes performance.
• Integrating observability tools.
• Automating scaling workflows.
• Troubleshooting bottleneck issues.
• Conducting team audits.

88. Where does Kong optimize scalability?

Kong optimizes scalability in the proxy layer, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management to handle high-traffic workloads.

89. Who optimizes Kong scalability?

SREs optimize plugin configurations, DevOps engineers manage nodes, security specialists enforce policies, and auditors review compliance. They collaborate via Jira, with team leads overseeing optimizations and executives monitoring metrics.

Regular audits maintain scalability reliability.

90. Which Kong features support scalability?

• Upstreams for load distribution.
• Plugins for scalable routing.
• Prometheus for scalability metrics.
• Grafana for visualization dashboards.
• GitLab for configuration versioning.
• Kubernetes for node scaling.
• Logs for compliance tracking.

91. How does Kong ensure high availability?

Kong ensures high availability using clustered nodes and health checks, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for CI/CD.

92. What if Kong nodes fail in a cluster?

• Verify health check configurations.
• Check node connectivity.
• Inspect Kubernetes namespaces.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Explore fault-tolerant designs for high availability.

93. Why do Kong clusters lose availability?

• Misconfigured health checks.
• Node resource exhaustion.
• Kubernetes namespace conflicts.
• Compliance restrictions on clusters.
• Network latency in failover.
• Untracked analytics for failures.
• Inconsistent configuration reviews.

94. When should Kong high availability be tuned?

• Handling traffic spikes.
• During cluster configuration updates.
• Validating Kubernetes performance.
• Integrating observability tools.
• Automating failover workflows.
• Troubleshooting node failures.
• Conducting team audits.

95. Where does Kong manage cluster nodes?

Kong manages cluster nodes in Kubernetes or standalone setups, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management.

96. Who manages Kong cluster nodes?

SREs manage node health, DevOps engineers configure clusters, security specialists enforce policies, and auditors review compliance. They collaborate via Jira, with team leads overseeing management and executives monitoring metrics.

Regular audits ensure node reliability.

97. Which Kong tools support high availability?

• Health checks for node monitoring.
• Upstreams for load balancing.
• Prometheus for availability metrics.
• Grafana for visualization dashboards.
• GitLab for configuration versioning.
• Kubernetes for cluster scaling.
• Logs for compliance tracking.

98. How does Kong handle high-traffic scenarios?

Kong handles high-traffic scenarios using plugins for caching and rate limiting, with upstreams for load balancing, integrated with Prometheus for metrics and GitLab for CI/CD.

99. What if Kong fails under high traffic?

• Verify plugin caching settings.
• Check upstream configurations.
• Inspect Kubernetes resources.
• Integrate Prometheus for diagnostics.
• Test in staging environments.
• Escalate via Jira for resolution.
• Monitor trends with analytics.

Explore network topology choices for traffic handling.

100. Why do Kong gateways struggle with high traffic?

• Overloaded node resources.
• Misconfigured plugin logic.
• Kubernetes resource constraints.
• Compliance restrictions on traffic.
• Network latency in routing.
• Untracked analytics for failures.
• Inconsistent configuration reviews.

101. When should Kong traffic handling be optimized?

• Handling peak traffic events.
• During gateway configuration updates.
• Validating Kubernetes performance.
• Integrating observability tools.
• Automating traffic workflows.
• Troubleshooting performance issues.
• Conducting team audits.

102. Where does Kong manage high-traffic workloads?

Kong manages high-traffic workloads in the proxy layer, integrating with Prometheus for metrics, Grafana for visualization, and GitLab for configuration management.

103. Which tools enhance Kong traffic handling?

• Plugins for caching and limiting.
• Upstreams for load balancing.
• Prometheus for traffic metrics.
• Grafana for visualization dashboards.
• GitLab for configuration versioning.
• Kubernetes for workload scaling.
• Logs for compliance tracking.

Explore secure TCP/UDP practices to protect traffic.