Prometheus vs. Grafana: Which Is Right for Your Team?

Your monitoring stack fires alerts. But who owns the ticket? Choosing between Prometheus and Grafana is one of the first decisions DevOps teams face when building an observability stack, and the confusion makes sense: the two tools show up in every guide together, but they do completely different things.

Prometheus collects and stores metrics. Grafana visualizes them. Most teams end up using both, but knowing where each one fits (and where it doesn't) saves you from over-engineering a setup you'll regret later.

Here's how they compare on features, pricing, and use cases so you can pick the right tool, or combination, for your team.

Prometheus vs. Grafana at a glance

Here's how these two popular observability tools compare across key dimensions.

Overview of Prometheus

Prometheus is an open-source systems monitoring and alerting toolkit that collects and stores metrics as time-series data for IT infrastructure and cloud-native environments. As a graduated CNCF project, it serves as the de facto standard for Kubernetes monitoring with a pull-based architecture designed for reliability during outages.

Key Features:

• Multi-dimensional time-series data model with flexible labels
• PromQL query language for complex metric analysis
• Pull-based monitoring with automatic service discovery
• Built-in alerting system with Alert Manager integration
• Native Kubernetes integration and cloud-native design
• Extensive exporter ecosystem for third-party systems
• Autonomous operation without distributed storage dependencies
• Local on-disk storage with optional remote storage adapters

Ideal for: DevOps teams running Kubernetes infrastructure who need reliable metrics collection with powerful querying capabilities and don't mind managing their own storage and visualization layers.

Overview of Grafana

Grafana is an observability platform that enables teams to query, visualize, and alert on metrics from multiple data sources through unified dashboards. Recognized as a Gartner Leader in Observability Platforms, it functions as a vendor-agnostic visualization layer that connects to diverse backends without requiring data migration or vendor lock-in.

Key Features:

• Unified visualization across 100+ data source integrations
• Cross-platform alerting with flexible notification routing
• Advanced data transformations for multi-source analysis
• Dynamic dashboards with templating and variables
• Observability-as-code with programmatic configuration
• Integrated application-to-infrastructure monitoring
• Native cloud platform integrations (AWS, Azure, GCP)
• Enterprise features, including SAML/LDAP and audit logging

Ideal for: IT operations teams managing diverse monitoring infrastructure who need unified visibility across multiple data sources and want flexible deployment options from open-source to fully managed services.

Side-by-Side Feature Comparison

When to Choose Prometheus vs. Grafana

The decision between Prometheus and Grafana depends on your specific monitoring architecture needs and team capabilities.

Choose Prometheus if you need:

• Standalone metrics collection and storage for Kubernetes environments
• Reliable monitoring that operates independently during infrastructure failures
• Native time-series database with powerful query capabilities
• Cost-effective solution with only infrastructure overhead
• Pull-based monitoring architecture with service discovery
• Strong operational team comfortable with PromQL and ecosystem tools
• Autonomous monitoring system without vendor dependencies

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Choose Grafana if you value:

• Unified visualization across multiple existing monitoring systems
• Vendor-agnostic architecture preventing monitoring tool lock-in
• Professional dashboards and advanced visualization capabilities
• Multi-source data correlation and cross-platform alerting
• Managed service options to reduce operational overhead
• Enterprise features like SAML/LDAP, RBAC, and audit logging
• Gradual migration path from legacy monitoring tools

How Does Monitoring Tie Into Incident Response?

Neither Prometheus nor Grafana integrates directly with Siit, but the real bottleneck isn't the alerting itself. It's what happens after the alert fires. Monitoring tools detect problems in seconds, then the response falls apart: someone copies the alert into Slack, tags three people, and hopes the right person picks it up.

Siit closes that gap by turning Slack and Teams into a structured incident management layer. AI Triage classifies and routes requests to the right responder automatically, while AI-Powered Workflows handle escalations, status updates, and cross-team coordination without manual handoffs. Your monitoring stack catches the fire; Siit makes sure someone actually puts it out.

Start a free trial and see how Siit turns monitoring alerts into resolved incidents, right where your team works.