Grafana Labs unveiled Grafana 13 and a wave of open source updates anchored by a next-generation Grafana Loki architecture and simpler paths to OpenTelemetry on Linux and Kubernetes.
“We’re seeing a clear shift in how organizations think about observability. It’s no longer about choosing a single vendor; it’s about building on open foundations,” said Anthony Woods, Co-Founder, Grafana Labs. “Open source, open standards, and an open ecosystem give teams the control and flexibility they need in a world that’s only getting more complex. The future of observability will be defined by interoperability and community-driven innovation, not closed systems. What we’re announcing at GrafanaCON today helps make that open model not just possible, but practical at scale.”
Grafana 13: From Insight to Action, Faster
Grafana 13 focuses on helping teams move from raw telemetry to actionable insight more quickly. Key updates include:
- Faster time-to-value through suggested dashboards, dashboard layout templates supporting standard methodologies like DORA and USE/RED method that reduce the blank-page problem, as well as guided learning paths for onboarding new and growing teams.
- Dynamic dashboards, now generally available, allow dashboards to adapt based on variables, context, and user needs instead of multiplying static copies.
- Programmability and governance at scale, 2-way Git workflows (supporting GitHub, GitLab, Bitbucket, and git) based on a redesigned dashboard schema and a versioned dashboard API, improved secrets handling, and dashboard restore, as well as advisory tooling for safer change management.
- Expanded ecosystem support, with more than 170 data sources and 120 visualization panels, plus continued guidance on repeatable patterns and best practices.
Grafana Labs introduced a major evolution of Grafana Loki, designed for modern log use cases and next-generation scale, specifically:
- Kafka-backed ingestion for more efficient, durable pipelines at the ingestion layer.
- A redesigned query engine and scheduler to better handle large-scale analytical workloads. A new query planner will distribute work across partitions and execute queries in parallel, optimizing for data locality and maximizing throughput, and allowing Loki to process significantly less data per query while returning results faster.
Together, these changes deliver up to 20x less data scanned and 10x faster performance on aggregated queries, making it possible to answer complex questions across massive log datasets with far greater efficiency.
To further accelerate Loki’s evolution, Grafana Labs also announced the acquisition of Logline, an early-stage company founded by tenured engineering leader and entrepreneur Jason Nochlin, focused on performant search of large-scale log data. Logline’s technology is designed to efficiently power “needle in the haystack” queries, such as searching for a specific user ID or error identifier across massive datasets, one of the most common and challenging use cases in log analysis. By bringing this capability into Loki, Grafana Labs aims to significantly improve precision search performance while maintaining Loki’s cost-efficient, index-light architecture.
Grafana Labs continues to invest in an open observability model built on open standards and a broad ecosystem, anchored by Prometheus and OpenTelemetry.
Grafana Labs engineers are working with the broader community to help make OpenTelemetry easier to install and operate, including:
- Integrated OpenTelemetry packages for Linux environments, enabling installation with a single command, and enhanced support for Kubernetes through the OpenTelemetry Operator.
- A more unified experience through Grafana Alloy, the company’s distribution of the OpenTelemetry Collector. In a recent OpenTelemetry community survey, Grafana Alloy was the most cited vendor distribution of the OpenTelemetry Collector. With the new OpenTelemetry Engine mode, teams can now configure Alloy using standard OpenTelemetry Collector YAML, enabling fully OpenTelemetry-native pipelines seamlessly integrated with Grafana.
Grafana Labs continues to contribute upstream to improve the stability of instrumentation, semantic conventions, and distributions, helping make OpenTelemetry more consistent, interoperable, and production-ready across the ecosystem.
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