Best Observability Tools

Grafana Labs provides an open and composable observability stack built around Grafana, the leading open source technology for dashboards and visualization. Recognized as a 2025 Gartner® Magic Quadrant™ Leader for Observability Platforms and positioned furthest to the right for Completeness of Vision, Grafana Labs supports over 25M users and 5,000+ customers—including Bloomberg, Citigroup, Dell Technologies, Salesforce, and TomTom. The LGTM Stack combines Grafana for visualization, Mimir for metrics, Loki for logs, and Tempo for traces. Grafana Cloud, the fully managed offering, accelerates time to value with turnkey solutions for Kubernetes monitoring, incident response, load testing, and more. It features Adaptive Metrics for cost-efficient data aggregation and native OpenTelemetry support. Built on open standards, Grafana empowers teams to visualize and correlate data from any source—without vendor lock-in—whether self-managed or in the cloud. Grafana Cloud scales with you, securely.

Splunk Enterprise is a powerful platform that turns data into actionable insights across security, IT, and business operations. It enables organizations to search, analyze, and visualize data from virtually any source, providing a unified view across edge, cloud, and hybrid environments. With real-time monitoring, alerts, and dashboards, teams can detect issues quickly and act decisively. Splunk AI and machine learning features predict problems before they happen, improving resilience and decision-making. The platform scales to handle terabytes of data and integrates with thousands of apps, making it a flexible solution for enterprises of all sizes. Trusted by leading organizations worldwide, Splunk helps teams move from visibility to action.

Monitor your data health and pipeline performance. Gain unified visibility for pipelines running on cloud-native tools like Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. An observability platform purpose built for Data Engineers. Data engineering is only getting more challenging as demands from business stakeholders grow. Databand can help you catch up. More pipelines, more complexity. Data engineers are working with more complex infrastructure than ever and pushing higher speeds of release. It’s harder to understand why a process has failed, why it’s running late, and how changes affect the quality of data outputs. Data consumers are frustrated with inconsistent results, model performance, and delays in data delivery. Not knowing exactly what data is being delivered, or precisely where failures are coming from, leads to persistent lack of trust. Pipeline logs, errors, and data quality metrics are captured and stored in independent, isolated systems.