Unlocking Insights at ObservabilityCON 2026: What You Need to Know
ObservabilityCON 2026 exists to equip you with the tools and knowledge to navigate the complexities of observability in today's fast-paced AI landscape. This flagship conference from Grafana Labs brings together industry leaders and innovators, providing a platform for sharing insights and best practices that can directly impact your production systems.
The event features hands-on workshops that offer firsthand experience in observing, governing, and improving AI systems running in production. You'll learn to build telemetry pipelines with Alloy, enhancing your ability to monitor and optimize your applications effectively. Additionally, the Ask the Experts booth allows you to engage directly with Grafana Labs engineers, giving you the chance to resolve your most pressing questions and challenges. ObservabilityCON on the Road also offers a condensed, one-day version of the event in cities like São Paulo, London, Madrid, and Bengaluru, making it more accessible for professionals worldwide.
As you prepare for the conference, remember that a separate ticket is required for workshops, which can only be purchased alongside a full conference ticket. This ensures that you get the most out of your experience by participating in both the main sessions and the specialized workshops designed to deepen your understanding of observability practices.
Key takeaways
- →Register for ObservabilityCON 2026 to gain insights from industry leaders.
- →Participate in hands-on workshops to learn about telemetry pipelines with Alloy.
- →Visit the Ask the Experts booth to get direct answers from Grafana Labs engineers.
- →Attend ObservabilityCON on the Road for a one-day version of the event in major cities.
Why it matters
In production, observability is crucial for maintaining system reliability and performance. Attending this conference can provide you with actionable strategies to enhance your observability practices, ultimately leading to better system health and user satisfaction.
When NOT to use this
The official docs don't call out specific anti-patterns here. Use your judgment based on your scale and requirements.
Want the complete reference?
Read official docsOpenAI & Anthropic-compatible inference API — no GPU provisioning needed. 55+ models, pay-per-token with no minimums. VPC + zero data retention by default.
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