Grafana

Overview After deploying a CDN, many teams stop at glancing at the hit rate number on the vendor’s console. Hit rate at 90%? Looks fine, moving on. Then one day the origin bandwidth gets maxed out, pages take 8 seconds to load, user complaints flood in — and you discover that 90% was the request hit rate, not the byte hit rate. Large files were all going back to origin, while small requests inflated the number....

Overview When the database slows down, the business slows down. Every ops engineer has heard this, but honestly, not many teams do database monitoring right. I’ve seen too many teams whose database monitoring looks like this: Zabbix templates running decade-old metrics, only two alert rules — “CPU over 90%” and “disk full” — while connection count, lock waits, cache hit rate, replication lag, and other metrics that actually provide early warning are not being collected at all....

Overview When selecting a monitoring system, one of the most debated questions is “commercial platform or self-hosted open-source.” Datadog is the benchmark for commercial observability platforms — out-of-the-box, feature-complete, with rich integrations, but at a premium price. Prometheus + Grafana represents the open-source self-hosted approach — flexible, controllable, with no license fees, but requiring investment in operations personnel. This isn’t a simple “save money vs save effort” choice. For fast-growing startups, Datadog’s out-of-the-box experience may be more valuable than the license fees saved....

Grafana is the most popular visualization platform in the cloud-native era, but there’s a world of difference between “functional” and “effective.” A cluttered dashboard leaves on-call engineers lost in a sea of panels, while a well-designed one conveys system health in 5 seconds. This article starts from design principles, covers the variable system, panel selection, and alerting integration, and ties everything together with a complete SLO dashboard. Reference: Grafana Official Documentation...

Why Choose Loki The traditional ELK (Elasticsearch + Logstash + Kibana) stack is powerful, but has two core pain points: High storage costs: Elasticsearch fully indexes log content, with index bloat reaching 3-5x the raw data Operational complexity: ES cluster scaling, shard rebalancing, and index lifecycle management are complex, making production clusters costly to maintain Loki, open-sourced by Grafana Labs, is designed around the philosophy of “doing for logs what Prometheus did for metrics....