Grafana Review

Grafana describes itself as the open-source platform for monitoring and observability, letting you query, visualize, alert on, and understand your data regardless of where it is stored. The README lists data sources including Prometheus, Loki, Elasticsearch, InfluxDB, Postgres, and MySQL, the ability to mix data sources in one graph, client-side graphs and panel plugins, dashboards with template variables, Explore views for ad-hoc metrics and logs queries with split views, and alert rules that notify tools such as Slack, PagerDuty, VictorOps, and OpsGenie. OpenAlternative highlights the commercial Grafana platform's Adaptive Telemetry (which it says can cut telemetry costs by up to 80%), AI-assisted root cause analysis, a unified signal map, incident response, and synthetic monitoring, and lists FedRAMP, PCI DSS, SOC Type II, and GDPR compliance for Grafana Cloud.

Grafana runs on Debian and Ubuntu, RHEL and Fedora, SUSE and openSUSE, macOS, and Windows, in Docker, or on Kubernetes with the Helm chart, and supports current Chrome, Firefox, Safari, and Edge. The documented floor is 512 MB of memory and 1 CPU core, which is for evaluation, not production. The sizing guidance (Grafana server only, excluding data sources) is: Small (under 25 users and 100 alert rules) 2 cores, 2 to 4 GB of memory, and 1 instance; Medium (25 to 200 users and 100 to 1,000 alert rules) 4 to 8 cores, 8 to 16 GB, and 2 load-balanced instances; Large (200+ users and 1,000+ alert rules) 8 to 16+ cores and 16 to 32+ GB per instance, 3+ load-balanced instances, and a 10 Gbps or faster network, ideally on Kubernetes. The embedded SQLite database is not recommended for production, and MySQL 8.0 or later or PostgreSQL 12 or later is required for high availability, along with sticky sessions or a shared Redis session store. Image rendering uses about 1 GB of memory per worker and should run on a separate host at Medium and Large scale, and at Large scale alert evaluation should move to dedicated instances in remote evaluation mode. On licensing, Grafana Labs announced on April 20, 2021 that its core open-source projects (Grafana, Loki, and Tempo) would move from Apache 2.0 to AGPLv3.

You connect data sources, build dashboards panel by panel with template variables, explore logs and metrics ad hoc, and define alert rules that route to your on-call tools. The strength is flexibility across heterogeneous data, and the cost is that you design and maintain the dashboards. The docs name the main load drivers: concurrent active users, alert rule count and evaluation frequency, data source types (proxied SQL sources cost more than pull-based sources such as Prometheus), and panel count with refresh intervals. This section reflects the README, installation docs, pricing page, and OpenAlternative; we did not run Grafana.

• Dashboards with template variables and many panel types
• Dozens of data sources, mixed in a single graph
• Explore for ad-hoc metrics and logs queries with split views
• Alert rules with notifications to Slack, PagerDuty, VictorOps, and OpsGenie
• Panel and data source plugins
• Grafana Cloud with metrics, logs, traces, profiles, incident response, and synthetic monitoring

• Works with almost any data source, with a huge plugin ecosystem
• A de facto standard, with about 77,000 stars and commits within hours of this review
• Generous Grafana Cloud free tier and a self-hosted OSS path with published sizing guidance
• Pairs naturally with Prometheus, Loki, and OpenTelemetry

• You must assemble storage and collection (Prometheus, Loki, Tempo) yourself for a full observability stack
• AGPL-3.0-only licensing for the core projects matters if you modify and offer it as a service
• Dashboards can sprawl without governance, and high availability needs MySQL or PostgreSQL plus sticky sessions or Redis
• Enterprise features and self-managed support start at a $25,000 per year minimum commit
• The cloud free tier limits retention to 14 days and active users to 3

Grafana Cloud Free includes 10k active metrics series, 50 GB of logs, 50 GB of traces, 50 GB of profiles (14-day retention each), and 3 active users each for visualization, IRM, and AI (Grafana Assistant). Pro has a $19/month platform fee including 10k series or 50 GB of logs, traces, or profiles, then pay as you go, with metrics from $6.50 per 1k series, logs, traces, and profiles at $0.05/GB processing, $0.40/GB write, and $0.10/GB retention, and Grafana Visualization from $8 per active user, with 13 months of metrics retention and email support. Enterprise (self-managed or cloud) is custom with a $25,000 per year minimum commit.

Datadog, Splunk, New Relic, and Dynatrace are commercial all-in-one observability suites with agents, storage, and APM under one bill. Grafana is the open, modular alternative: it visualizes and alerts on data that lives in the systems you choose, and Grafana Cloud sells the full stack on usage. You get flexibility and lower lock-in, and you give up some of the turnkey integration and unified agent of the commercial suites.

• Teams building an open observability stack with Prometheus, Loki, and Tempo
• Organizations that want one dashboard layer over many data sources
• Companies that want to avoid per-host observability pricing

• Small teams that want a single agent that does everything with no assembly
• Organizations that cannot accept AGPL obligations for modified deployments
• Teams without the time to design and maintain dashboards