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+Q1. What is Observability, and how is it different from monitoring?
+Monitoring tells us when something is wrong. Observability tells us why it is wrong.
+Observability is based on three pillars:
+• Metrics (Prometheus)
+• Logs
+• Traces
+Prometheus focuses mainly on metrics-based observability
+
+Q2. What is Prometheus and why is it widely used?
+Prometheus is an open-source monitoring and alerting system designed for:
+• Time-series metrics
+• Pull-based metric collection
+• Powerful querying using PromQL
+It is popular because it:
+• Works well with Kubernetes
+• Is highly scalable
+• Has strong alerting and visualization support
+
+Q3. Explain Prometheus architecture.
+Prometheus consists of:
+• Prometheus Server – scrapes and stores metrics
+• Exporters – expose metrics (Node Exporter, JVM Exporter)
+• Service Discovery – finds targets dynamically
+• Alertmanager – manages alerts
+• Grafana – visualization layer
+
+Q4. What is a metric in Prometheus?
+A metric is a time-series data point identified by:
+• Metric name
+• Labels (key-value pairs)
+• Timestamp
+• Value
+Example:
+http_requests_total{method="GET",status="200"}
+
+Q5. What are the different metric types in Prometheus?
+Type Description
+Counter Always increases (e.g., request count)
+Gauge Can go up and down (e.g., memory usage)
+Histogram Measures distributions with buckets
+Summary Similar to histogram but client-side
+
+Q6. What is PromQL?
+PromQL (Prometheus Query Language) is used to:
+• Query metrics
+• Aggregate data
+• Perform calculations
+Example:
+rate(http_requests_total[5m])
+
+Q7. Difference between rate() and irate()?
+• rate() → average over time (stable,preferred)
+• irate() → instant rate (more volatile)
+
+Q8. What is an exporter?
+An exporter converts system/application metrics into Prometheus format.
+Examples:
+• Node Exporter(OS metrics)
+• Blackbox Exporter(endpoint checks)
+• JVM Exporter
+
+Q9. How does Prometheus store data?
+Prometheus stores data in a local TSDB(Time-Series Database) with:
+• Efficient compression
+• Retention-based deletion
+
+Q10. What are labels and why are they important?
+Labels provide dimensions for metrics.
+They allow:
+• Filtering
+• Aggregation
+• Multi-dimensional analysis
+Example:
+{pod="payment-service", namespace="prod"}
+
+Scenario-Based Questions(Prometheus)
+Q11. Your Prometheus server is running out of disk space. What would you do?
+• Reduce retention period
+• Enable remote storage(Thanos/Cortex)
+• Clean unused metrics
+• Increase disk size
+• Reduce label cardinality
+
+Q12. Metrics are missing from a Kubernetes pod. How do you debug?
+• Check pod annotations
+• Verify ServiceMonitor/PodMonitor
+• Check target status in Prometheus UI
+• Validate exporter endpoint
+• Check network policies
+
+Q13. Prometheus performance is degrading. What could be the reasons?
+• High cardinality labels
+• Too many scrape targets
+• Long retention
+• Expensive PromQL queries
+
+Q14. How do you monitor application latency using Prometheus?
+• Use Histogram or Summary
+• Track request duration
+• Use histogram_quantile() for percentiles
+
+Q15. How do you handle multi-cluster monitoring?
+• Deploy Prometheus per cluster
+• Use Thanos/Cortex for aggregation
+• Centralized Grafana dashboards
+
+Conceptual Questions(Grafana)
+Q16. What is Grafana?
+Grafana is an open-source visualization and analytics tool used to:
+• Create dashboards
+• Visualize metrics
+• Set alerts
+
+Q17. How does Grafana integrate with Prometheus?
+Grafana uses Prometheus as a data source and executes PromQL queries to visualize metrics.
+
+Q18. What are dashboards and panels in Grafana?
+• Dashboard - Collection of panels
+• Panel - Single visualization(graph,table,gauge)
+
+Q19. What types of visualizations does Grafana support?
+• Time-series graphs
+• Heatmaps
+• Gauges
+• Tables
+• Bar charts
+
+Q20. What are Grafana variables?
+Variables make dashboards dynamic and reusable.
+Example:
+• $namespace
+• $pod
+
+Scenario-Based Questions(Grafana)
+Q21. A Grafana dashboard is slow. How do you optimize it?
+• Reduce query complexity
+• Increase time range step
+• Limit panels per dashboard
+• Use recording rules
+
+Q22. How do you create alerts in Grafana?
+• Define alert conditions on panels
+• Configure thresholds
+• Set notification channels(Slack,Email)
+
+Q23. Multiple teams use the same Grafana instance. How do you manage access?
+• Use Organizations
+• Use Folders
+• Apply RBAC
+• Integrate with LDAP/OAuth
+
+Q24. How do you correlate metrics with logs and traces?
+• Use consistent labels(traceId,service)
+• Integrate with Loki(logs)
+• Integrate with Tempo(traces)
+
+Q25. How do you visualize error rates in Grafana?
+• Use PromQL to calculate error percentage
+• Plot time-series graph
+• Add threshold-based alerts
+
+Q26. Production latency increased suddenly. How do you troubleshoot using Prometheus & Grafana?
+1. Check latency dashboards
+2. Identify affected service
+3. Drill down by pod/instance
+4. Correlate with CPU/memory
+5. Check error rates
+6. Validate recent deployments