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The Golden Grot Awards: Celebrating Innovation in Observability! 🌟
Welcome to a special highlight from GrafanaCON, where we celebrate the brightest minds and most innovative projects in the observability space with the coveted Golden Grot Awards! This year marks the fifth anniversary of these prestigious awards, recognizing excellence and pushing the boundaries of what’s possible, especially with the growing influence of AI. Let’s dive into the incredible winners who are shaping the future of technology! 🚀
🌌 Aurora Chaser: Your Personal Northern Lights Forecast 🌌
First up in the personal dashboard category, we have Mohamed Adem from DRW, who takes home a Golden Grot for his breathtaking dashboard, the Aurora Chaser! 🌠
The Challenge: While the Northern Lights are a spectacular natural phenomenon, catching them can be incredibly difficult. Mohamed found that while scientific data on the probability of aurora activity exists, there wasn’t a single, easy-to-understand indicator to tell you if they’d be visible at your specific location.
The Solution: Mohamed built the Aurora Chaser to answer that one crucial question: “Should I go out tonight to see the Northern Lights?” He expertly aggregated public data from various sources to create a composite view.
- Data Sources:
- NOAA (National Oceanic and Atmospheric Administration): For Bz component of the magnetic field and solar wind data.
- Open-Meteo: For atmospheric weather data like cloud coverage and visibility.
- NASA: For sun imagery.
- Technology Stack:
- Telegraf: Used to collect data from public APIs.
- InfluxDB Cloud: Stores the collected time-series data.
- Grafana: For querying data and visualization.
- Business Charts Panel (Volkov Labs/Grafana): Enabled the use of the Apache ECharts JavaScript library for advanced visualizations, unlocking over 100 new chart types.
Key Features:
- Aurora Go/No-Go Score: A custom score from 0 to 100, derived from the K-index (global aurora activity), Bz (north-south direction of the solar wind’s magnetic field), and cloud coverage. This score translates into actionable statements like “stay home” or “drop everything and go outside!”
- Real-time Sun Imagery: Displays magnetograms from NASA, highlighting solar flares.
- Satellite Data Comparison: Compares solar wind data from ACE and DSCOVR satellites.
- Live Webcam Feeds: Integrates live webcam panels from different cities for a real-world view.
Takeaways: Mohamed emphasizes starting with a clear question, leveraging public APIs with Telegraf for free time-series data (and using AI-assisted development to generate Telegraf configs!), and exploring plugins like Business Charts when native Grafana panels don’t suffice. 💡
🌕 Blue Ghost Lunar Lander: Mission-Critical Observability on the Moon 🌕
Our next Golden Grot winner operates in an environment where mistakes are not an option: space! Jackson Sweeney from Firefly Aerospace is recognized for building the Observability system for the Blue Ghost lunar lander. 🚀
The Mission: Firefly Aerospace designs and builds rockets and lunar landers. Their Blue Ghost Mission 1, launched on January 15th, 2025, successfully landed on the Moon on March 2nd, 2025, carrying over 100 kilograms of scientific instruments for NASA. The stakes were incredibly high, with no room for error during the landing.
The Dashboard’s Role: The dashboard Jackson developed was crucial for decision support during the mission’s most critical moments, especially the landing. It provided real-time vehicle health verification, enabling the operations center to make informed, non-risky decisions.
Key Aspects of the Dashboard:
- Focus: Primarily thermal-focused, monitoring temperatures and heater data.
- Data Points: Queried over 500 different telemetry points, including:
- Temperatures
- Heater status
- Power system data (battery charge)
- Vehicle orientation in space (sun exposure impact on temperature)
- Organization: All this critical data was neatly organized onto just two screens within Grafana, ensuring quick access.
- Impact: This dashboard wasn’t just about monitoring; it was instrumental in achieving a monumental outcome – a successful lunar landing, watched by the world! 🌎
Mission Imagery: Jackson shared breathtaking visuals, from launch and Earth orbit to lunar orbit and the final image taken just after landing on the Moon, showcasing the lander’s shadow and the Earth in the background.
🤖 AI in Action: Transforming Incident Response and Cost Optimization 🤖
This year, the Golden Grot Awards put a spotlight on AI innovation. We have two winners in this exciting new category!
⚡ Grafana Assistant: Accelerating Incident Response at TeleTracking ⚡
Oren Lion from TeleTracking receives a Golden Grot for pioneering the use of Grafana Assistant to revolutionize their incident triage, mitigation, and reporting processes. ⏱️
The Context: TeleTracking optimizes patient flow through the healthcare system, acting as “air traffic control for hospitals.” The availability and performance of their platform directly impact patient care. With a move to a new platform, existing engineers have increased responsibilities, making efficiency paramount.
The Solution: Grafana Assistant
- Incident Response Lifecycle Acceleration:
- When an incident is detected and alerts fire, engineers can use Grafana Assistant to analyze the situation directly within the dashboard.
- Demo Example: In a scenario with multiple alerts and a potential system-wide disruption, Grafana Assistant quickly analyzed the data, identified that all three Kafka brokers experienced a significant drop, and concluded it was likely an AWS blip, ruling out traffic spikes. This significantly reduced investigation time.
- Built-in Grounding: The assistant provides its reasoning and data sources directly in the report, eliminating the need to search elsewhere.
- Post-Incident Reports: The assistant’s analysis contributes to creating comprehensive post-incident reports, saving time.
- Mitigating Defects:
- Grafana Assistant helps create new alerts to prevent recurring issues. For example, an alert for deviations in error messages from a noisy service.
- It can simplify complex alert configurations and even help with adding necessary annotations for “Alerting as Code.”
- Cost Optimization:
- Leveraging Grafana’s cost attribution features and Grafana Assistant’s prompting capabilities, TeleTracking can now visualize application spend as a percentage of total spend, identify cost drivers, and target cost optimization by team.
- This allows for better prioritization of cost-saving efforts, especially when teams are over budget.
Key Impact: Oren states that Grafana Assistant is helping them spend less time and get more done across all roles, from individual contributors to managers. 👨💻
👂 NeoSapien: Privacy-First AI Wearables and Observability 👂
Our final Golden Grot winner is Dhananjay Yadav, CEO and co-founder of NeoSapien, for their privacy-focused AI wearable and how they leverage Grafana Cloud and Grafana Assistant Investigations to optimize complex AI pipelines. 🦾
The Product: NeoSapien AI Wearable
- Concept: The world’s first AI wearable that understands conversations, creates an individualized knowledge graph, and builds deep context.
- Functionality: It seamlessly captures daily conversations (telephonic, online, offline) and performs four AI services simultaneously: diarization, transcription, and summarization.
- Privacy-First Design: Audio data lives only in memory and is destroyed after processing, with only raw transcripts and traces retained. This is a deliberate departure from traditional devices that are not privacy-first.
The Challenges & Solutions with AI Pipelines:
- No Audio Storage: The constraint of not storing audio logs forced them to focus on optimizing traces and logs to understand system behavior.
- Key Pillars for Optimization:
- Latency: Standardizing conversation processing time (e.g., within 13 seconds) is crucial for user experience. Delays of minutes can significantly degrade usability.
- Discard Rate: Identifying and discarding non-meaningful conversations (e.g., background noise, talking to a third person) is vital for optimizing the AI model and reducing costs.
- Cost: With a 24/7 wearable device, optimizing cost is paramount. The entire pipeline must maintain standardized costs, with alerts for any variance.
How Grafana Helped:
- Grafana Assistant Investigations: A small team of four engineers used Grafana Assistant to analyze their complete pipeline and identify key bottlenecks.
- Example Finding: They discovered issues with BLE advertising failures that were impacting the overall user experience. Grafana helped them identify, fix, and validate these issues directly in their codebase.
- Learning from Constraints: Dhananjay highlighted three key learnings:
- Intense constraints (like no audio storage) lead to clarity on what needs to be logged and how.
- Cost Observability is critical, and Grafana helped optimize per-user costs.
- Privacy is not blindness. Even without storing audio, insights can be gained through duration, discard rates, and latency.
Impact: NeoSapien has scaled significantly, becoming one of the highest-selling wearables in India and preparing for a global launch, all while maintaining a strong focus on privacy and cost-efficiency. ✨
Congratulations to all the Golden Grot Award winners! Your innovation, dedication, and groundbreaking work are truly inspiring and are driving the observability community forward! 🎉