Cloud Monitoring and Performance Management Questions and Answers for Viva

Answer-1: Cloud monitoring is the process of tracking the performance, availability, and health of cloud resources and services.

Answer-2: It ensures optimal performance, identifies issues early, improves reliability, and helps in resource optimization.

Answer-3: CPU usage, memory utilization, disk I/O, network traffic, latency, error rates, and uptime.

Answer-4: AWS CloudWatch, Azure Monitor, Google Cloud Operations Suite, Datadog, New Relic, Prometheus.

Answer-5: Performance management involves measuring, analyzing, and optimizing cloud resources to meet service-level objectives.

Answer-6: Cloud monitoring is dynamic, scalable, and often automated for virtualized and distributed resources.

Answer-7: Logs provide detailed records of system events and are essential for troubleshooting and analysis.

Answer-8: Alerts notify administrators of abnormal conditions to prompt timely action.

Answer-9: An SLA defines expected performance and availability levels agreed between providers and customers.

Answer-10: Auto-scaling adjusts resources dynamically based on monitored metrics to maintain performance.

Answer-11: A dashboard visualizes real-time data and metrics for easier monitoring and decision making.

Answer-12: It uses algorithms to identify unusual patterns or deviations from normal behavior.

Answer-13: Synthetic monitoring simulates user interactions to proactively check system performance and availability.

Answer-14: RUM collects data from actual users to measure real-world performance and user experience.

Answer-15: Black-box monitors external system behavior without internal knowledge; white-box monitors internal system components.

Answer-16: An incident is any event that disrupts normal system operation or degrades performance.

Answer-17: By analyzing logs, metrics, and traces to identify the origin of a problem.

Answer-18: Agents collect metrics and logs from cloud resources and send data to monitoring systems.

Answer-19: Tracking how efficiently CPU, memory, storage, and network resources are used.

Answer-20: By identifying over-provisioned or idle resources that can be optimized to reduce costs.

Answer-21: Measuring the time taken for data to travel between components or to respond to requests.

Answer-22: Ensures services are operational and accessible to users as expected.

Answer-23: By tracking failed login attempts, unusual network traffic, and configuration changes.

Answer-24: Aggregating metrics helps to analyze trends and get a holistic view of system health.

Answer-25: Tools designed specifically for cloud environments, supporting scalability and automation.

Answer-26: Monitoring tracks predefined metrics; observability provides comprehensive insights using logs, metrics, and traces.

Answer-27: Thresholds define when alerts trigger, balancing sensitivity and noise reduction.

Answer-28: It tracks requests across microservices to identify bottlenecks and failures.

Answer-29: An SLA that guarantees the monitoring service?s availability, accuracy, and response time.

Answer-30: Leads to undetected issues, poor performance, downtime, and increased costs.

Answer-31: APIs enable integration of monitoring tools with cloud services and automation workflows.

Answer-32: Monitoring of physical and virtual infrastructure components like servers, storage, and network.

Answer-33: Using container-specific tools like Kubernetes metrics server, Prometheus, and Grafana.

Answer-34: Using historical data and machine learning to predict future performance issues.

Answer-35: Analyzing monitoring data to forecast resource needs and prevent bottlenecks.

Answer-36: Reactive responds to problems after they occur; proactive anticipates and prevents issues.

Answer-37: A periodic test to verify a service or resource is functioning correctly.

Answer-38: Using secure transmission, redundancy, and validation checks.

Answer-39: Fine granularity gives detailed insight but requires more storage and processing.

Answer-40: They offer built-in monitoring services integrated with their cloud platforms.

Answer-41: Linking multiple related events to identify root causes and reduce alert noise.

Answer-42: By providing unified dashboards and integrations for different cloud platforms.

Answer-43: Testing application workflows by simulating user transactions regularly.

Answer-44: Tracking bandwidth, latency, packet loss, and connection stability.

Answer-45: Centralizes logs for easier analysis, troubleshooting, and compliance.

Answer-46: By automating anomaly detection, root cause analysis, and predictive maintenance.

Answer-47: Constantly assessing system health to maintain uptime and performance.

Answer-48: Monitoring the performance and availability of cloud-based applications.

Answer-49: By providing audit trails, alerts on policy violations, and configuration monitoring.

Answer-50: Handling dynamic environments, data volume, alert fatigue, and ensuring real-time visibility.