Which do you prefer for Kubernetes monitoring: Prometheus or Datadog, and why?
I’m looking for opinions on using Prometheus vs Datadog for monitoring Kubernetes clusters.
Which tool do you prefer and why? Also, I’d love to hear any horror stories or examples where these tools have failed or caused issues.
I’ve been using Prometheus for Kubernetes clusters for a few years, and here’s what I like about it:
It’s open-source and free, which is great for startups or smaller teams.
Kubernetes integration is native, with service discovery, metrics scraping, and exporters.
Works perfectly with Grafana for dashboards.
The trade-off? You need to manage it yourself, storage, scaling, and alerting can get tricky as your cluster grows.
I once had a cluster with huge metric volume, and Prometheus needed careful tuning and multiple instances to avoid downtime. But when configured right, it’s rock solid.
If you prefer something that “just works,” Datadog is amazing:
Cloud-hosted, so you don’t worry about scaling or storage.
Built-in Kubernetes integration, alerts, dashboards, and anomaly detection.
Supports multi-cloud and hybrid setups without extra configuration.
I used Datadog on a production cluster, and it saved hours of setup. The downside is cost, large clusters or high-cardinality metrics can get expensive fast. Also, you’re tied to their SaaS platform.
From my experience:
Small/medium clusters / DIY teams: Prometheus + Grafana is my pick. Powerful, flexible, and no recurring costs. But expect some operational overhead.
Enterprise / large clusters / limited ops bandwidth: Datadog wins. Less setup pain, faster alerts, and integrated dashboards. Costly, but you pay for convenience.
Horror stories:
Prometheus: Forget to tune retention, and it crashed during a traffic spike.
Datadog: Hit high-cardinality billing unexpectedly because a deployment added thousands of new pods reporting metrics.
Personally, I run Prometheus for my clusters at home/side projects, but I’ve recommended Datadog for enterprise clients who don’t want to maintain their own monitoring stack.