Operations | Monitoring | ITSM | DevOps | Cloud

HAProxy is the workhorse in front of countless APIs and apps because it’s fast, lean, and flexible. Because it sits on the traffic hot path, it’s also your earliest warning system when something slows down or breaks entirely. This means that monitoring it isn’t optional. You need to see connection queues and retries, per-stage timings, health-check failures, and spikes in error statuses to catch incidents before users do.

Want a quick path to NVIDIA DCGM monitoring? This guide shows how to install the DCGM Exporter, scrape /metrics, visualize in Grafana, and set alerts for power, errors, and utilization.

Elasticsearch is a distributed search and analytics engine that powers everything from log management platforms to e-commerce search bars. It excels at indexing and retrieving large volumes of data quickly, but like any complex system it can slow down under heavy load or inefficient queries.

Database latency rarely starts in your app layer because it’s almost always a query doing more work than it should. Metrics tell you when that happens, but slow-query logging tells you which statement did it and how. That’s gold for tracking down missing indexes, inefficient filters, or accidental full scans. Pair the logging with a some lightweight counter metrics, and you get both an early warning and a clear path to a fix.

MongoDB’s strength of flexible schema and fast iteration can also hide costly queries until they surface as user-facing latency, replica lag, or spiky CPU. A handful of slow operations can impact the cache, starve other workloads, and cascade into timeouts across services. Monitoring slow queries gives you an early warning system for index gaps and query-plan regressions introduced by code deploys, schema changes, or shifting data shapes.