Birds of a Feather discussions
Join us to explore the topics you care about in small, intimate group discussions with your fellow community members.
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Join us for the official kickoff of our biggest community conference of the year. Grafana Labs CEO/Co-founder Raj Dutt and Grafana creator Torkel Ödegaard celebrate the highlights from the past year. Members of our engineering team make some exciting announcements around our open source projects and unveil what’s new in Grafana 13.
April 26, 2025, is a date the Grafana Labs security team won’t forget. Internally, it needs no explanation: “The Incident” is enough.
In this talk, David Andersson and Nick Moore walk through a real security incident response, from first alert to resolution, and how open source tooling and open collaboration shaped every step. It started with a Saturday morning alert from canary tokens, turning a quiet weekend into an immediate investigation.
They'll explain how a misconfigured GitHub Actions workflow led to unauthorized access to CI credentials, and how the team used open source security and observability tools to understand what happened and how far it went. Logs in Loki, incident coordination with Grafana Cloud IRM, credential scanning using Trufflehog, and workflow auditing using both Gato-X and Zizmor allowed them to trace activity, coordinate response, rotate tokens, and verify that no customer data or systems were impacted.
A key aspect of the incident response was the fact that the team was in fact working in the open. Instead of waiting to communicate with the open source community after the fact, they collaborated directly with maintainers and contributors during triage and validation. Open tools, shared context, and public artifacts helped the Grafana Labs security team move faster and with more confidence.
This is a candid look at what happens when things go wrong in complex, open systems. It’s also the story of how preparation, openness, and trust in open source tooling meant that the team got to write the “no customer impact” post.
Marine ecosystems face accelerating pressures from climate change, overexploitation, and habitat degradation, demanding continuous, high-resolution environmental intelligence. To achieve that, DIGI4ECO, a Horizon Europe project, is developing a 4D ecological monitoring system built on a digital twin of the ocean, integrating advanced robotics, AI-powered analytics, and unified data observability pipelines with Grafana.
In this session, Jacopo Aguzzi, Senior Research Scientist at the Institute of Marine Sciences, and Enoc Martinez, Assistant Professor at the Electronic Engineering Department of UPC, discuss how DIGI4ECO's coordinated network of fixed and mobile robotic platforms forms a distributed "physical twin of the ocean." These platforms capture biological, environmental, opto-acoustic, and molecular (eDNA/eRNA) information at unprecedented temporal frequency and spatial resolution.
At the Digital Twin Ocean (DTO) layer, AI algorithms — including state-of-the-art convolutional neural networks and object-detection architectures (e.g., YOLO) — automatically identify species, compute ecological indicators, and characterize biodiversity trends. These indicators inform restoration strategies and support policy-relevant assessments aligned with EU biodiversity and restoration goals.
Jacopo and Enoc also share the interactive Grafana dashboards that visualize both physical and biological data streams, from oceanographic time series and acoustic profiles to AI-processed underwater imagery and ecological indicators. These dashboards demonstrate how observability tools can bridge robotics, environmental monitoring, and marine policy needs, turning complex ocean data into actionable intelligence.
The next generation of Loki is coming, with big architectural changes to make it the most performant open source logging database available and a new storage engine for faster insights.
In this session, Loki engineers Poyzan Taneli and Trevor Whitney explain the new architecture designed for petabyte-scale logging. They discuss the benefits of the key changes, which include: a new ingestion path backed by Kafka that effectively achieves replication factor 1 (RF-1) durability, a redesigned query engine, a new scheduler, and a new data format. All of these developments are aimed at enabling significantly higher performance and scalability at large log volumes.
Plus, as structured logging and OpenTelemetry adoption grow, users are running more analytical queries over massive volumes of increasingly high cardinality data. To help with that, Loki team members Ben Clive and Jason Nochlin will dive into the open source database's new storage engine and data format, and the design decisions behind it that enable faster large-scale scans, minimize the impact of stream cardinality, and improve performance for analytical workloads. They'll share results from benchmarks to show where Loki is already faster, where performance is comparable, and where the team is still pushing forward.
In a recent OpenTelemetry community survey, Grafana Alloy was the most cited vendor distribution of the OpenTelemetry Collector. Alloy brings together the best of both worlds: powerful Prometheus-native features plus OpenTelemetry’s extensive ecosystem and upstream innovation. And now, the new OpenTelemetry Engine mode lets you configure Alloy using standard OpenTelemetry Collector YAML and enable OpenTelemetry-native pipelines integrated with Grafana.
In this session, Grafana Labs engineers Bejal Lewis and Marko Bachvarovski explain Alloy’s new capabilities and show you exactly what changes (and what doesn’t). You’ll learn the differences between Alloy’s Default Engine and the new OpenTelemetry Engine, understand which use cases apply to which, and get a sneak peak into upcoming features.
Java is one of the most widely used programming languages for enterprise applications, powering everything from monoliths to large-scale microservice architectures. Frameworks such as Spring Boot and Quarkus, together with a rich ecosystem of ORM, messaging, and communication libraries, have made application-level observability relatively straightforward through the OpenTelemetry Java agent.
However, there are many real-world scenarios where modifying application code or JVM startup parameters is not possible. The OpenTelemetry eBPF Instrumentation (OBI) project focuses on these cases, offering a powerful alternative by enabling observability without code changes or JVM configuration modifications.
In this talk, Grafana Labs Principal Software Engineer and a maintainer of OBI, Nikola Grcevski and Causely co-founder Endre Sara, explore the challenges of instrumenting Java applications using eBPF, including the diversity of JDK distributions and versions, differences in JVM internals, and the combinatorial explosion of frameworks and libraries that makes generic instrumentation difficult. The problem becomes even harder when applications communicate over TLS-encrypted protocols, such as HTTPS, gRPC, encrypted database connections, and secure messaging systems, where payloads are opaque to traditional eBPF techniques.
This session explains the design decisions and implementation details behind OBI's approach to these challenges, including how OBI correlates low-level kernel events with higher-level application semantics and how it deals with encrypted communication paths. Nikola and Endre also discuss the trade-offs involved, highlighting what information can be reliably extracted today and where limitations remain.
To ground the discussion, the talk includes several real-world examples: a Spring Boot application communicating with Keycloak over HTTPS, a Spring Boot application using gRPC to interact with Google Pub/Sub, and a Quarkus application using TLS-encrypted PostgreSQL and Kafka.
And the Golden Grot goes to…. Our annual Golden Grot Awards celebrate the amazing dashboards our community creates. The winners in the two categories (personal and professional) receive their prizes and share the stories of why and how they built their dashboards.
What would it look like if you applied observability best practices to how you approach your business data? Join Chris Shih, Senior Director of Analytics, and Sam Jewell, Staff Software Engineer, to hear about how their teams have built Grafana Labs' business data stack around Grafana dashboards and alerting, and what they're excited about for the future of analytics.
Over the last five years, Grafana has become the company's operational backbone with interactive, custom dashboards tracking everything from daily signups to customer health metrics. And as the organization has scaled, the team is leveraging a semantic layer in combination with AI agents to move toward self-service analytics.
In this session, Chris and Sam share their journey and the lessons learned, and demonstrate how you can take this approach for your own organization's business analytics using a fully open source stack with DuckDB, dbt, Cube, Grafana MCP, and Grafana.
With Pyroscope 2.0, we’re delivering a ground-up rearchitecture of our open source continuous profiling database. Designed to make continuous profiling faster and more cost-effective at scale, the latest major release of Pyroscope includes a new storage layer: replication-free, no persistent disks, and reads fully decoupled from writes.
This talk covers why we rebuilt, the architectural decisions behind 2.0—including how symbol co-location exploits profiling data's natural redundancy for a 20x storage reduction—and what we measured after rolling it out across every Grafana Cloud region.
In a demo, we'll investigate a page for request timeouts on Pyroscope's own query-backend service, using a span heatmap to spot the slow requests, drilling into an individual profile, and pinpointing exactly which code path is causing the timeouts.
How do we power AI? Next-generation nuclear fission and fusion reactors present a potential solution to sustainably meet escalating energy demands with zero carbon emissions. This is driving a renaissance in nuclear technology, as evidenced by recent collaborations between cloud providers, AI companies, and nuclear energy firms. Traditionally, nuclear materials research has been hampered by slow, manual processes that quickly become obsolete. Today's challenges require adaptable systems and platforms that can scale and evolve with each new discovery and technological breakthrough.
In this session, Theia Scientific Co-founders Christopher Field and Kevin Field share their company's approach to materials research and non-destructive testing workflows, built on a novel combination of Grafana, machine learning, and Jupyter notebooks. This application development platform enables (data) scientists, engineers, and developers to rapidly create their own custom machine learning-powered applications.
Grafana delivers the customizable dashboard-driven web-based "single pane of glass" window into the ML-analyzed data collected with electron microscopes and industrial X-ray inspection systems. Grafana’s plugin architecture, “big tent” philosophy for interoperability, and open source observability ecosystem provide the foundation for the platform’s adaptability.
See a live demonstration of the platform that is paving the way for nuclear energy to literally power Grafana-based observability, cloud infrastructure, and AI systems.
Refresh latencies of Grafana dashboards are dependent on how quickly the underlying system (like Prometheus or Clickhouse) can answer queries. Naturally, as these systems ingest and query more data, dashboard refreshes become slower. While one could scale out the underlying systems to speed up queries, this increases the Total Cost of Ownership (TCO).
In this lightning talk, Milind Srivastava, a PhD student at Carnegie Mellon University, proposes a new way to compute observability queries that doesn't force you to choose between low TCO and low latency. Instead of traditional queries that are executed on raw data, queries can be executed on "semantic-preserving summaries" that use orders of magnitude lower memory and CPU resources, compared to executing on raw data. Milind is releasing an open source system that speeds up Grafana query latencies by 100x using this method. See a live demo of ASAPQuery, which is built to be backwards-compatible with an existing observability deployment and can be deployed in a drop-in manner between Grafana and the underlying system (like Prometheus or Clickhouse).
Why did original digital pets fail? No telemetry, no alerting, no incident response.
Now imagine if they had:
Meet TamaGrotChi: the fully observable digital pet. TamaGrotChi is the first fully instrumented digital lifeform. This WiFi-enabled pet is powered by OpenTelemetry and reports its hunger, happiness, and emotional instability straight into Grafana Cloud.
Every button press is a trace.
Every ignored cry for attention is a log.
Every missed feeding window is a measurable SLO violation.
If you think you understand alert fatigue now, wait until Grot starts escalating to IRM because you breached the Mean Time To Feed.
GrotShotPro began as an experiment to build a launch monitor at home. With costly commercial launch monitors often running on buggy software that deliver mixed results, the goal was to open source and democratize launch monitor technology in the golf space.
Armed with nothing but a Claude subscription, the project went from a crazy idea to a reality, building a sizable social media following and a growing open source repository. This hackathon project integrates golf simulator software into Grafana and connects it to an open source launch monitor, OpenFlight.
It’s a fully featured launch monitor. Fore!
It wouldn’t be GrafanaCON without a major Grafana release. In this session, Grafana team members walk you through Grafana 13 and the most impactful improvements across the platform.
Hear about how Grafana is becoming easier and safer to operate as production infrastructure, with updates that improve configuration management, recovery, and long-term maintainability. The session also showcases significant advances in core user workflows, including more flexible and powerful dashboards, with improved performance.
This session brings together the product and engineering work behind the release and shows how Grafana continues to evolve to meet the needs of the community, reducing friction in everyday use and helping teams get to insights from their data faster, even as systems grow in scale and complexity.
Google runs hundreds of thousands of services globally, often interdependent and with shared telemetry. At that scale, classic federated observability—a platform team providing foundations and/or building blocks for each team to assemble on their own—does not work anymore.
In this talk, Katia Giarda, Software Reliability Manager at Google, and Carl Bergquist, Principal Engineer at Grafana Labs, demonstrate how Google managed to cut toil dramatically while providing best-in-class monitoring out of the box.
The presentation covers:
Katia draws on Google’s research paper on planet-scale dashboards (to be published) and more than a decade of experience in SRE. Carl demos how Grafana has incorporated these ideas to enable Google to replace its existing dashboarding tool with Grafana.
Operating distributed databases at scale can be challenging. It is not just about algorithms, but also about surviving failure, unpredictable load, and human mistakes.
In this session, Grafana Mimir maintainer Marco Pracucci and Grafana Tempo maintainer Marty Disibio share hard-earned lessons from growing these two databases to massive scale in Grafana Cloud. Although Mimir and Tempo serve different telemetry signals, they share the same core architecture and design principles.
Marty and Marco start by presenting the architecture and the key decisions that allow Mimir and Tempo to scale reliably and cost-effectively. Then they move to practice, showing how those principles hold up in production – and where they don’t – by contrasting the real bottlenecks, breaking points, and operational failure modes they see in metrics versus traces.
Have you ever wanted to visualize live Apache Kafka data directly in Grafana, eliminating the need for complex intermediate storage or external services?
In this session, Hamed Karbasi, a data engineer at 0+X, chronicles the open source development journey of the Grafana Kafka data source plugin, which allows users to query and visualize real-time Kafka data streams instantly.
See a live demonstration of how to get started with the plugin to integrate Kafka data for observability, including the steps you take to:
By highlighting the strong community collaboration and support available for building new Grafana plugins that address real-world needs, Hamed hopes to inspire other developers to contribute their own integrations to the Grafana ecosystem.
As Grafana Assistant expanded its capabilities, the challenges changed. The hard part was no longer just adding functionality. It was making the Assistant’s agentic workflows actually useful, improving it with confidence, and understanding how it behaved in the real world. In this session, members of the Grafana Labs engineering team share what they learned scaling Assistant: how better context makes it more useful, how trusted feedback loops make iteration safer, and how observability helps them understand Assistant once it is live.
When Irish Rail needed to modernize infrastructure monitoring across the national railway network, traditional consultancy approaches failed. Multiple million-euro, proprietary solutions were disqualified due to rigid dashboards, vendor lock-in, and systems that looked impressive in PowerPoint presentations but couldn't meet operational requirements.
In this session, learn how Irish Rail got on the right track by leveraging Grafana's open source plugin ecosystem, data source flexibility, and community support. Today, Irish Rail Intelligent Sensing (IRIS)—a production-grade IIoT platform powered by Grafana, MQTT Unified Namespace, and TimescaleDB—monitors everything from track-side pumps and bridge sensors to passenger platforms and critical infrastructure across Ireland's 2,400 kilometers of railways.
The team walks through how it scaled from a single sensor proof-of-concept to ISA-95 compliant enterprise monitoring integrated with SAP and ServiceNow. With IRIS, Mean Time to Notification (MTTN) for safety-critical events has decreased, preventing bridge strikes and enabling predictive maintenance.
One unexpected result: Grafana didn't just replace monitoring dashboards. It became the foundation for Irish Rail's AI-powered operational intelligence platform, positioning a 180-year-old railway operator alongside digitally mature European leaders.
This is a story about choosing adaptability over vendor promises, open source collaboration over proprietary lock-in, and how the right tooling empowers engineers to build what consultants couldn't deliver.
Bugs and bottlenecks are inevitable, but letting them reach your users isn't. In this session, k6 team members Théo Crevon and Andrey Slotin demonstrate how k6 v2.0 lowers the barriers to proactive testing. With AI-assisted authoring, visual scripting using k6 Studio, rich assertions to validate app behavior, and a native ecosystem that extends support to any protocol, the latest version of k6 makes it easy to validate performance and correctness before they impact production.
In their own experience, performance testing is often treated as an afterthought. Teams care about it only after an incident occurs. This reactive approach usually comes from the perception that there's a high cost to creating tests for complex systems. Théo and Andrey highlight how v2.0 was designed specifically to address those concerns and walk through how the native extension ecosystem adapts k6 to your specific tech stack and workflows. Learn how to turn reliability from a late-stage panic into a proactive habit.
Grafana is evolving as a mature and powerful platform for alerting. In this session, Staff Software Engineer Alexander Akhmetov and Senior Software Engineer Sonia Aguilar from the Grafana alerting team detail their progress in high availability and core stability; and how they rigorously validate features with intense internal dogfooding.
Discover new features that will make alerts more actionable and reduce response time to incidents:
Alexander and Sonia also discuss how the user experience has been enhanced with new features, such as the ability to configure multiple notification policy trees, significantly improving how you can manage observability of large systems across multiple teams.
Every year at the Supercomputing Conference, more than 16,000 attendees from industry, academia, and government gather to see the future of high-performance computing – AI at scale, quantum experiments, and bleeding-edge research. Powering it all is SCinet, the world’s fastest temporary network: a one-of-a-kind system that takes a year to design, a month to build, a week to operate, and a day to tear down.
In 2025, SCinet delivered an astonishing 13.72 Tbps of bandwidth, creating a network whose scale and complexity are hard to grasp, even for seasoned network engineers. A network that impressive deserves more than raw metrics and CLI outputs. It needs a way to be seen.
In this talk, ESNet Software Engineer Andrew Lake and ESNet Data Viz Developer Katrina Turner discuss how Grafana became the storytelling engine for SCinet, transforming massive volumes of network telemetry into intuitive, compelling visualizations that made sense to everyone, from network operators and researchers, to first-time conference attendees, and even government officials. With little time to build bespoke tools, the team used the new MetrANOVA pipeline, a Clickhouse database, and Grafana’s flexible dashboards with custom plugins to visualize network flows, performance, and behavior – all in less than a week.
Andrew and Katrina dive into the unique challenges of visualizing a massive, short-lived network, the design decisions behind dashboards that had to work on a bustling conference floor, and how observability can be used not just to monitor systems, but to communicate scale, impact, and awe. From our traffic map of the show room floor to the bumpchart booth race, they put a fun twist on the way people usually look at network metrics, and it paid off.
This talk is a story-driven look at observability under extreme constraints, packed with lessons for anyone using Grafana to explain complex systems to both experts and novices alike.
The Python Software Foundation (PSF) manages critical infrastructure that serves millions of developers worldwide every day: PyPI (Python Package Index), PyCon, PyLadiesCon, python.org, docs.python.org, bugs.python.org, mail.python.org, and numerous other services that power the Python ecosystem.
In this session, PSF Infrastructure Engineer Jacob Coffee shares how the PSF uses Grafana, Alloy, and Loki to maintain reliability and security across a complex, distributed infrastructure:
Gerard de Jong used to believe the same lie everyone else does: More screen = more observability.
But then he hacked a Stream Deck to show 72x72 pixel Grafana dashboard panels, always visible in his peripheral vision, and it completely changed how he handles incidents. Suddenly: No more hunting for the right browser tab. No more joining calls already behind. No more surprises when an alert fires.
While wall displays are great for high-level status, they fail during the "fog of war" of an active incident. Peripheral vision is tuned for motion and patterns, not dense charts. That’s why car dashboards, cockpits, and game HUDs all put tiny signals just below the line of sight.
In this lightning talk, Gerard demonstrates how and why small displays make this possible (be it on a Stream Deck, Raspberry Pi, and everything in-between), the layouts that actually work, and why micro-dashboards let you often see anomalies before alerts fire while everyone else is still opening Grafana.
This is not a toy – it’s a practical hack for real on-call life.
Learn:
Drive Terra runs a fleet of electric delivery bikes and battery swapping stations across the Middle East. Instead of using separate tools for IoT monitoring and business reporting, the team built everything in Grafana.
In this session, Terra CTO Mohammad Omar shares how the company uses Grafana for two very different jobs. On the technical side, real-time vehicle telemetry, battery health monitoring, and notifications are all connected to Terra's databases directly. On the business side, Grafana powers swap station utilization, bike availability, inventory tracking, and operational dashboards used by the ops team, executives, and partners. Learn practical lessons from a small team running Grafana as its single source of truth – what worked, what was tricky, and why they skipped Power BI entirely.
This lightning talk explains how emissions can be measured in naturally ventilated livestock barns housing cattle and pigs using temporary sensor campaigns and Grafana. The sensors run for 2–3 weeks per campaign, several times per year, so the focus is on collecting consistent data and comparing results across campaigns — not on 24/7 live monitoring.
Sunil Gopalakrishna, a Researcher at the Institute of Agricultural Technology, walks through the full pipeline: sensor nodes, data ingestion, a time series database, and Grafana dashboards. He shares what must be consistent for results to be trustworthy: a shared time reference, a stable naming scheme for sensors and measurements, and clear metadata (campaign, site, animal type, sensor location, and calibration state). Simple quality flags highlight missing periods and obvious spikes so plots are interpreted correctly.
Finally, Sunil shares the campaign dashboards: annotated time series for key events (cleaning, feeding, ventilation changes) and a canvas panel with a barn layout that displays sensor dots on a floorplan and marks when thresholds are crossed. Basic integrity checks (data completeness, “last seen” during active windows, and ingestion errors) help identify data capture problems quickly.