Ensuring the health of deployed applications relies on a combination of metrics monitoring and centralized logging, giving visibility into both current system behavior and the underlying cause when something goes wrong.
Key Points: • Prometheus scrapes and stores time-series metrics like CPU usage, memory, request latency, and error rates from every service. • Grafana visualizes those metrics in dashboards and can trigger alerts when thresholds are crossed, surfacing issues before users report them. • The ELK stack (Elasticsearch, Logstash, Kibana) centralizes logs from all instances, making it possible to search and correlate events across services. • Metrics tell you something is wrong and roughly where; logs tell you why, by showing the actual error messages and stack traces. • Alerting rules on top of these tools notify the team proactively, rather than relying on users to report outages.
Example: When response times spike, Grafana's dashboard flags the affected service immediately, and searching Kibana for that time window reveals a flood of database connection timeout errors, pointing straight at the root cause.
Interview Tip: A concise interview answer is:
"I use Prometheus to collect metrics like latency and error rates, visualized and alerted on through Grafana, alongside the ELK stack for centralized log search. Metrics tell me something's wrong and where, and the logs tell me why, so together they give fast root-cause visibility."