OrionIQ Agentic Observability
TL; DR
Grafana is an open source observability platform best known for creating interactive dashboards that visualize metrics, logs, and traces from multiple data sources. Engineering teams use Grafana to monitor infrastructure, applications, Kubernetes clusters, databases, and cloud services in real time.
Originally developed as a metrics visualization tool, Grafana has evolved into a broader observability platform with support for alerting, incident management, distributed tracing, and log analysis. It integrates with popular technologies such as Prometheus, Elasticsearch, OpenSearch, Loki, InfluxDB, and major cloud monitoring services, making it a common choice for DevOps, SRE, and platform engineering teams.
Grafana is an open source analytics and visualization platform that helps organizations monitor the health and performance of their systems through customizable dashboards.
Instead of storing monitoring data itself, Grafana connects to external data sources and displays the information in charts, graphs, tables, heatmaps, and other visualizations. This flexibility allows teams to monitor virtually every aspect of modern infrastructure, from application response times and server utilization to Kubernetes workloads and cloud services.
Today, Grafana is one of the most widely adopted tools in the observability ecosystem because it supports hundreds of integrations and enables engineers to visualize telemetry from multiple systems in a single interface.
Whether you’re monitoring a small application or a global distributed architecture, Grafana provides a centralized way to understand system performance and identify potential issues before they impact users.
Grafana acts as a visualization layer between your monitoring data and your engineering teams.Rather than collecting telemetry directly, Grafana queries data from connected sources whenever a dashboard or panel loads.
A typical workflow looks like this:
Because Grafana separates visualization from storage, organizations can continue using their preferred telemetry backends while providing a consistent dashboard experience across teams.
Grafana supports a wide variety of monitoring and observability use cases.
Common applications include:
Track CPU, memory, storage, network traffic, and system availability across servers, virtual machines, and cloud environments.
Visualize request latency, throughput, error rates, and service health to understand how applications perform under real-world workloads.
Monitor clusters, nodes, namespaces, pods, containers, and resource utilization through Kubernetes dashboards and Prometheus metrics.
When connected to log management platforms like Elasticsearch, OpenSearch, or Loki, Grafana enables engineers to search logs and correlate them with metrics during incident investigations.
Many organizations also use Grafana to visualize operational KPIs, business metrics, and custom analytics alongside infrastructure data.
Dashboards are Grafana’s defining feature.
A dashboard consists of multiple panels that display different visualizations, including:
Each dashboard updates automatically as new monitoring data arrives.
Teams often create separate dashboards for infrastructure health, Kubernetes clusters, application performance, database monitoring, cloud services, and executive reporting.
Because dashboards are highly customizable, organizations can tailor them to different engineering roles without changing the underlying telemetry.
One of Grafana’s biggest strengths is its broad ecosystem of supported data sources.
Popular integrations include:
Grafana currently supports hundreds of official and community-built integrations, making it suitable for organizations with diverse technology stacks.
Modern observability extends beyond dashboards.
Today’s engineering teams need to correlate logs, metrics, traces, alerts, and deployment events to quickly understand why incidents occur.
Grafana supports this approach by integrating multiple telemetry signals into shared dashboards and investigations.
However, visualization is only one component of observability. Organizations also require systems that collect, process, store, and analyze telemetry data, as well as capabilities for automated root cause analysis and AI-assisted investigations.
For this reason, Grafana is often deployed alongside dedicated observability platforms rather than replacing them entirely.
Grafana and Kibana are frequently compared because both help teams visualize operational data, but they were designed for different purposes.
| Grafana | Kibana |
| Supports hundreds of data sources | Built specifically for Elasticsearch |
| Strong focus on metrics dashboards | Strong focus on log analytics and search |
| Popular for infrastructure monitoring | Popular for log management and security analytics |
| Flexible visualization across multiple systems | Deep integration with the Elastic ecosystem |
Organizations using Elasticsearch often choose Kibana for log exploration while using Grafana for infrastructure dashboards. Others consolidate these capabilities within a unified observability platform.
Grafana has become a standard monitoring tool because it offers several advantages:
These capabilities ake Grafana suitable for organizations of nearly every size.
Although Grafana is extremely popular, it has some limitations.
Grafana primarily focuses on visualization and alerting rather than telemetry storage or analysis.
Organizations still need separate systems to:
As environments become increasingly distributed, many teams supplement Grafana with full observability platforms that combine telemetry storage, AI-powered analytics, and automated incident response.
Yes. Grafana is available as free open source software that organizations can self-host. Grafana Labs also offers enterprise and managed cloud editions with additional features and commercial support.
No. Grafana is primarily a visualization platform. It queries data from external systems such as Prometheus, Elasticsearch, OpenSearch, Loki, and cloud monitoring services rather than storing telemetry itself.
Yes. Grafana supports all three pillars of observability when connected to compatible data sources, allowing engineers to correlate telemetry and investigate incidents more efficiently.
Prometheus collects and stores metrics, while Grafana visualizes that data through dashboards and alerts. They are commonly used together for infrastructure and Kubernetes monitoring.
Grafana provides many observability capabilities, including dashboards, visualization, alerting, and telemetry correlation. However, most organizations pair Grafana with dedicated telemetry backends and observability platforms that handle data collection, storage, and AI-powered analysis – like Logz.io.
