Grafana is an open-source analytics and visualization platform that transforms your metrics into interactive dashboards. Learn what makes it essential for modern infrastructure monitoring and how to get it running.
Publish date: 10/10/2025
If you've ever needed to make sense of a mountain of server metrics, application logs, or infrastructure data, you know how quickly raw numbers can become overwhelming. That's where Grafana comes in. It's the tool that turns those miscellaneous data streams into clean, interactive dashboards that actually tell you what's happening with your systems.
Whether you're managing a single VPS or orchestrating a fleet of dedicated servers, Grafana gives you the visibility you need to keep things running smoothly. Let's explore what Grafana is, why it's become the go-to choice for monitoring and observability, and how you can get it installed on your own infrastructure.
Grafana is an open-source analytics and interactive visualization platform. It connects to your data sources, whether that's Prometheus, InfluxDB, Elasticsearch, MySQL, or dozens of other systems, and lets you create dashboards that display your metrics in real time.
Think of it as the command center for your infrastructure. Instead of SSH-ing into servers to check logs or running manual queries to see CPU usage, you get a unified view of everything in one place. Grafana doesn't collect the data itself; it pulls from whatever monitoring stack you're already using and presents it in a way that's actually useful.
The platform has been around since 2014 and has grown into one of the most popular tools in the DevOps ecosystem. It's used by everyone from solo developers monitoring personal projects to Fortune 500 companies tracking massive distributed systems.
The beauty of Grafana lies in its flexibility. You're not locked into a single vendor's ecosystem or forced to use proprietary tools. You can connect it to multiple data sources simultaneously, which means you might be pulling server metrics from Prometheus, application performance data from Jaeger, and business analytics from PostgreSQL, all displayed on the same dashboard.
Dashboards are completely customizable. You can build exactly what you need, from simple time-series graphs showing CPU and memory usage to complex panels with heat maps, histograms, and geospatial data. The query editor supports different query languages depending on your data source, so you can write PromQL for Prometheus data or SQL for relational databases.
Alerting is built directly into Grafana. You can set thresholds on any metric and get notified through Slack, PagerDuty, email, or a dozen other channels when something goes wrong. This means you can catch problems before they become outages.
The community around Grafana is massive. There are thousands of pre-built dashboards available that you can import and customize, which saves you from building everything from scratch. If you're monitoring a common service like NGINX, PostgreSQL, or Docker, someone has probably already created a dashboard for it.
Before installing Grafana, it helps to understand how it fits into your monitoring stack. Grafana itself is just the visualization layer. You'll need at least one data source that's actually collecting metrics.
A typical setup might include Prometheus scraping metrics from your servers and applications, storing that time-series data, and then Grafana querying Prometheus to display those metrics. Grafana doesn't replace Prometheus or any other monitoring tool; it complements them by providing a better interface for exploring and visualizing the data.
Grafana runs as a standalone web application. It uses a backend database to store dashboard configurations, user accounts, and settings. By default it uses SQLite, which is fine for single-server deployments. For larger installations, you can switch to MySQL or PostgreSQL.
The web interface runs on port 3000 by default. Users access dashboards through their browser, and Grafana handles all the queries to your data sources on the backend. This means your data sources don't need to be publicly accessible; they just need to be reachable from wherever Grafana is running.
Getting Grafana up and running isn't complicated. The installation process varies slightly depending on your operating system, but the Grafana team maintains official packages for most major distributions.
For Ubuntu or Debian-based systems, you'll want to use the official APT repository. This makes sure you get updates through your normal package management workflow.
First, install the prerequisite packages and add the Grafana GPG key:
sudo apt-get install -y software-properties-common
sudo wget -q -O - https://packages.grafana.com/gpg.key | sudo apt-key add -
Add the Grafana repository:
echo "deb https://packages.grafana.com/oss/deb stable main" | sudo tee /etc/apt/sources.list.d/grafana.list
Update your package list and install Grafana:
sudo apt-get update
sudo apt-get install grafana
Once installed, start the Grafana service and enable it to run on boot:
sudo systemctl start grafana-server
sudo systemctl enable grafana-server
You can check that Grafana is running:
sudo systemctl status grafana-server
For Red Hat-based distributions, the process is similar but uses YUM or DNF instead of APT.
Create a new repository file:
sudo tee /etc/yum.repos.d/grafana.repo <<EOF
[grafana]
name=grafana
baseurl=https://packages.grafana.com/oss/rpm
repo_gpgcheck=1
enabled=1
gpgcheck=1
gpgkey=https://packages.grafana.com/gpg.key
sslverify=1
sslcacert=/etc/pki/tls/certs/ca-bundle.crt
EOF
Install Grafana:
sudo yum install grafana
Or if you're using a newer version with DNF:
sudo dnf install grafana
Start and enable the service:
sudo systemctl start grafana-server
sudo systemctl enable grafana-server
If you're running Docker, Grafana can be deployed as a container, which is particularly convenient for testing or when you're already managing other services with Docker.
Pull the official Grafana image:
docker pull grafana/grafana
Run Grafana in a container:
docker run -d -p 3000:3000 --name=grafana grafana/grafana
For a more permanent setup, you'll want to mount volumes to persist your data and configuration:
docker run -d \
-p 3000:3000 \
--name=grafana \
-v grafana-storage:/var/lib/grafana \
grafana/grafana
This makes sure your dashboards and settings survive container restarts. Using Docker Compose is also another option.
After installation, open your browser and navigate to http://your-server-ip:3000. The default login credentials are:
adminadminYou'll be prompted to change the password immediately after your first login, which you absolutely should do.
The first thing you'll want to set up is a data source. Click on the gear icon in the left sidebar to access the configuration menu, then select "Data Sources." Click "Add data source" and choose your monitoring backend. If you're using Prometheus, you'll need to provide the URL where Prometheus is running, typically something like http://localhost:9090 if it's on the same server.
Once your data source is connected, you can start creating dashboards. The "+" icon in the sidebar lets you create a new dashboard. You can add panels, choose visualization types, and write queries against your data source. If you're new to this, it's worth browsing the Grafana community dashboards to see what's possible and import some pre-built examples.
Running Grafana on port 3000 with the default configuration is fine for testing, but you'll want to secure it before putting it into production.
First, don't expose Grafana directly to the internet if you don't have to. Put it behind a reverse proxy like NGINX or Traefik, and use that proxy to handle SSL/TLS termination. This gives you HTTPS without needing to configure SSL directly in Grafana.
The Grafana configuration file is located at /etc/grafana/grafana.ini. You can modify settings like the HTTP port, domain name, and authentication options here. If you're integrating with an existing authentication system, Grafana supports LDAP, OAuth, and SAML.
Consider setting up user roles and permissions. Grafana has a flexible permission system that lets you control who can view, edit, or create dashboards. For teams, this prevents accidental changes to important monitoring dashboards.
Enable and configure alerting so you get notified when metrics cross thresholds. Under the alerting menu, you can set up notification channels for email, Slack, PagerDuty, or webhook integrations. This turns Grafana from a passive visualization tool into an active monitoring solution.
While Grafana supports over 100 data sources, a few are particularly common and worth understanding.
Prometheus is probably the most popular pairing with Grafana. It's a time-series database designed for metrics, and Grafana's query builder has excellent support for PromQL. If you're monitoring Kubernetes or any containerized infrastructure, this combination is nearly standard.
InfluxDB is another time-series database that works well with Grafana. It uses a SQL-like query language called InfluxQL, which can be easier to learn if you're already comfortable with relational databases.
For log analysis, Loki (also from Grafana Labs) provides a lightweight alternative to Elasticsearch. It's designed to work seamlessly with Grafana and uses the same label-based approach as Prometheus.
If you need to monitor traditional databases, you can connect directly to MySQL, PostgreSQL, or Microsoft SQL Server. This lets you create dashboards around application data, not just infrastructure metrics.
Prometheus is a monitoring system that collects and stores metrics, while Grafana is a visualization platform that displays those metrics. They're complementary tools, not competitors. Prometheus scrapes metrics from your services and stores them as time-series data. Grafana queries Prometheus and turns that data into visual dashboards. You typically use both together.
Absolutely. Grafana works with many different data sources including InfluxDB, Elasticsearch, MySQL, PostgreSQL, and cloud monitoring services like CloudWatch or Azure Monitor. You don't need Prometheus at all if you're using a different backend for metrics collection.
Yes, Grafana is open source and free to use under the AGPL v3 license. There's also Grafana Cloud, which is a hosted service with a free tier and paid plans for larger deployments. For self-hosted installations on your own infrastructure, there's no licensing cost.
For small to medium deployments, Grafana isn't particularly resource-intensive. A server with 2GB of RAM and a single CPU core can handle dozens of users and dashboards. The actual resource usage depends more on how many data sources you're querying and how complex your dashboard queries are. The data sources themselves, like Prometheus or InfluxDB, typically require more resources than Grafana.
Yes, you can configure dashboards to allow anonymous access. In the Grafana configuration file, you can enable anonymous authentication and set default permissions for anonymous users. This lets you share monitoring dashboards publicly or embed them in other applications without requiring login credentials.
Grafana has become the standard for metrics visualization because it does one thing really well: it takes complex data and makes it understandable. Whether you're tracking server performance, monitoring application health, or analyzing business metrics, Grafana gives you the tools to see what's happening at a glance.
The installation process is straightforward, and once you've got it running, you'll quickly find it becoming an indispensable part of your infrastructure toolkit. Start with a simple dashboard or two, connect your existing monitoring systems, and build from there.
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