Grafana Labs, the company behind the open observability cloud, today unveiled Grafana 13 and a wave of open source updates at GrafanaCON 2026, anchored by a next-generation Grafana Loki architecture and simpler paths to OpenTelemetry on Linux and Kubernetes.According to Grafana Labs’ 2026 Observability Survey, more than 77% of organizations now lean on open source/open standards for observability, yet more than 38% of teams still cite complexity as their top challenge. The updates announced at GrafanaCON are aiming to address that tension: keep the openness, lose the friction.“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

Loki: Architecture for the Next Wave of Log Workloads
As observability data continues to evolve, Grafana Labs is also rethinking how logs are stored and queried at scale. The rise of structured logs and OpenTelemetry has fundamentally changed how teams use logs, shifting from simple search toward more analytical, high-cardinality queries, making it critical to rethink the system design to address performance bottlenecks and increasing infrastructure costs.

To address this, 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.

OpenTelemetry: Easier to Install, Easier to Run
Grafana Labs continues to invest in an open observability model built on open standards and a broad ecosystem, anchored by Prometheus and OpenTelemetry.

According to Grafana Labs’ 2026 Observability Survey, a majority of organizations are using OpenTelemetry or are actively migrating toward it, signaling a clear industry shift toward vendor-neutral instrumentation. But while adoption is accelerating, many teams still face challenges around complexity, evolving semantic conventions, and operational overhead. 

To reduce these barriers, 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.

GrafanaCON 2026: Innovation Across the Open Observability Ecosystem
GrafanaCON 2026 brings together the global community behind Grafana’s 35 million users worldwide, with thousands of engineers, SREs, and developers gathering in Barcelona to share how they use observability in practice. The event goes beyond product announcements, showcasing real-world applications of open observability across industries.

This year’s agenda features user-led sessions highlighting observability in action, including:

• How Google uses Grafana to build planet-scale dashboards
• How LEGO Group uses Grafana Foundation SDK to build a better dashboard framework
• How Irish Rail modernized monitoring across a 180-year-old railway system
• How Theia Scientific uses Grafana, machine learning, and Jupyter notebooks to help manage nuclear-powered data centers
• And more – from measuring cow emissions and e-bike battery health to monitoring golf simulators and digital pets

“GrafanaCON is where the future of observability gets built in the open,” said Torkel Ödegaard, co-founder, Grafana Labs. “What you see in these announcements is a direct result of that collaboration. Everything we build is shaped by how people actually run these systems at scale. We continue to invest in open source because it’s the most effective way to solve hard technical problems together and push the entire ecosystem forward.”