Operations | Monitoring | ITSM | DevOps | Cloud

Canvas is an AI-guided workspace inside Honeycomb that combines an AI assistant with an interactive notebook for visualizing query results and traces. You can ask a natural language question about your data and Canvas will immediately start exploring your traces, through multiple queries and other tools, to find the right next steps. Instead of having to write each query yourself, Canvas automatically proposes relational queries, comparisons, and visualizations that explain why an SLO fired or what changed after a deploy.

In this episode of Pastries with SREs, we dig into Limitless Observability with a sweet side of unified observability strategy. If you're tired of siloed tools, fractured data, and swivel-chair investigations, this one’s for you. We explore: Why are silos still the norm in modern observability? What’s the true cost of inefficiencies across logs, metrics, and traces? How can SREs, IT operations, and dev teams shift to a no-compromise, unified observability model?

Modern teams face a persistent challenge: knowing when something goes wrong before their customers do. With architectures sprawling across dozens or hundreds of services, creating comprehensive alerting becomes an overwhelming task. You're left playing whack-a-mole with manual alert configurations, often missing critical issues or drowning in false positives. Today, we're excited to announce our solution to this challenge: Anomaly Detection (currently in alpha), Honeycomb's proactive approach to understanding and acting on service health.