Grafana¶

📊 What is Grafana?¶

Grafana is an open-source observability and visualization platform. It lets you query, visualize, alert, and explore metrics, logs, and traces from multiple data sources.

Originally created by Torkel Ödegaard, Grafana has grown into a CNCF incubating project and is now the de facto dashboarding tool in cloud-native monitoring stacks.

👉 If Prometheus is the “brain” of monitoring (data collection & querying), Grafana is the eyes (dashboards & visualizations).

🧐 Why Do We Need Grafana?¶

Modern systems generate huge amounts of telemetry data:

• Metrics (from Prometheus, InfluxDB, Graphite, etc.)
• Logs (from Loki, Elasticsearch, Splunk, etc.)
• Traces (from Jaeger, Tempo, Zipkin, etc.)

Without visualization, raw metrics are hard to interpret. Grafana solves this by:

• Turning metrics into interactive dashboards
• Providing alerting when thresholds are crossed
• Enabling multi-source observability (metrics + logs + traces in one UI)

👉 Grafana = single pane of glass for observability.

🔧 How Grafana Works¶

Grafana itself does not collect data. Instead, it:

1. Connects to data sources (Prometheus, Loki, Elasticsearch, etc.)
2. Executes queries against them
3. Renders results in panels (graphs, gauges, tables, heatmaps, etc.)
4. Organizes panels into dashboards
5. Provides alerting & notifications based on panel queries

🔗 Architecture Overview¶

+------------------+
| Data Sources     |   (Prometheus, Loki, Tempo, etc.)
+---------+--------+
          |
          v
+---------+---------+
|  Grafana Server   |
|  - Query engine   |
|  - Panels         |
|  - Alerting       |
+---------+---------+
          |
   +------+------+
   | Dashboards |
   +------+------+
          |
      End Users

🔄 Data Flow: From Metrics → Grafana → User¶

sequenceDiagram
    participant DS as Data Source (Prometheus, Loki, etc.)
    participant G as Grafana
    participant User as User (SRE/DevOps)

    User->>G: Request dashboard
    G->>DS: Query metrics/logs/traces
    DS-->>G: Return results
    G-->>User: Render panels
    G->>User: Send alerts (if configured)

📊 Example Grafana Panels¶

Grafana supports many visualization types:

• Time series graph → CPU usage over time
• Gauge / SingleStat → current memory usage
• Heatmap → latency distribution
• Table → list of failing pods
• Pie chart → % of requests per region

👉 Panels can be grouped into dashboards (e.g., “Kubernetes Cluster Health”).

🛠 Common Data Sources¶

Grafana supports dozens of backends. Most common:

👉 Grafana turns it into a multi-source observability platform.

🔔 Alerting in Grafana¶

Grafana provides a unified alerting system (since v8):

• Create alerts directly from panels.
• Alerts are evaluated on the Grafana server.

• Notifications are sent via channels:

• Slack

• Email
• PagerDuty
• Microsoft Teams
• Webhooks

Example Alert Flow¶

1. Define a threshold (e.g., CPU usage > 80%).
2. Grafana runs the query periodically.
3. If condition matches, an alert fires.
4. Notification goes to configured channel.

⚙️ Installing Grafana¶

Docker¶

docker run -d -p 3000:3000 grafana/grafana

• UI: http://localhost:3000
• Default credentials: admin/admin

Kubernetes (Helm)¶

helm repo add grafana https://grafana.github.io/helm-charts
helm install grafana grafana/grafana

🛡️ Security Best Practices¶

• ✅ Always set admin password (default is insecure).
• ✅ Enable TLS if exposed publicly.
• ✅ Use OAuth/SAML/LDAP for authentication.
• ✅ Use folders & permissions to restrict dashboard access.
• ✅ Enable audit logs for compliance.

🔍 Key Strengths of Grafana¶

• 🌐 Multi-data-source (metrics, logs, traces, SQL, cloud).
• 🎨 Rich visualizations (100+ panel types, plugins).
• 📦 Pre-built dashboards (Grafana.com library).
• ⚡ Fast querying & exploration (great with Prometheus).
• 📢 Unified alerting with many integrations.
• 🔌 Extensible (plugins for panels, datasources, apps).

⚠️ Limitations & Watch Outs¶

• ❌ No storage → relies on external data sources.
• ❌ Query-heavy dashboards → can overload Prometheus/DB.
• ❌ High availability setup requires external DB (MySQL/Postgres).
• ❌ User management is limited in OSS (Grafana Enterprise adds RBAC, reporting).

📦 Grafana in the Observability Stack¶

flowchart TD

    subgraph Metrics
        P[Prometheus]
        N[node_exporter]
        C[cAdvisor]
    end

    subgraph Logs
        L[Loki]
    end

    subgraph Traces
        T[Tempo]
    end

    subgraph Grafana["Grafana Dashboards"]
        G["Dashboards + Alerts"]
    end

    P --> G
    L --> G
    T --> G

👉 Grafana = central observability frontend for metrics, logs, and traces.

🧾 Grafana Cheat Sheet¶

✅ Core Concepts¶

📊 Common Use Cases¶

• System monitoring (CPU, memory, disk usage).
• Kubernetes monitoring (pods, nodes, namespaces).
• Business metrics (orders per minute, revenue trends).
• Application performance monitoring (APM).
• Log exploration (with Loki/Elasticsearch).

🎯 Final Takeaway¶

Grafana is:

• The visualization + alerting layer of modern monitoring stacks.
• Datasource-agnostic (works with metrics, logs, traces, SQL).
• Essential for Kubernetes, microservices, and cloud-native setups.

👉 Think of Grafana as the dashboard and control room where DevOps, SREs, and engineers get their insights.