Operations | Monitoring | ITSM | DevOps | Cloud

Clint Sharp explains why a common model like OCSF is critical for the future of AI. Agents need standardized data to analyze information effectively on your behalf. He contrasts the traditional manual workflow of checking Slack, tickets, and wikis while asking colleagues with a future where AI fuses this human context with machine data. Instead of just search results, AI agents will hand you examined hypotheses so you know exactly where to take your investigation.

Google Cloud Security Operations is deprecating the legacy SecOps Forwarder, and OpenTelemetry with Bindplane is the official telemetry ingestion method. In this workshop, you’ll learn how to migrate from the SecOps Forwarder to Bindplane and OpenTelemetry Collectors, the officially supported ingestion model for Google SecOps going forward. We walk through the why, the what, and the how — with practical guidance you can apply immediately.

Clint Sharp explains why traditional schema-on-read systems cannot handle the query loads of the future. Agentic telemetry requires a 360-degree view, but structuring data only when you read it is too slow for AI-driven workloads. The solution is using LLMs to drive the cost of building parsers to near zero. Tools like Copilot Editor allow teams to map data to OCSF instantly, effectively building factories of parsers to handle the scale of agentic AI.

Join us live on Wednesday, December 10th at 11am EDT for the December Community Call. We’ll cover: Hands-on demos of the new Bindplane features you’ve been asking for Recaps of KubeCon+CloudNativeCon NA in Atlanta New Bindplane feature guides and blog posts As always, we’ll wrap with an interactive Q&A, so bring your questions!

Join us as Diego teaches how to build, optimize, and refine high-performing queries, including using key operators and the new Query Agent for natural-language searches.

Learn how to quickly track down performance bottlenecks using Sentry Logs and Tracing. In this video, we walk through identifying a slow screen, jumping into the connected trace, and pinpointing slow backend steps, database calls, and AI/LLM operations. See how logs, issues, and traces work together to show the full picture of what happened in a single session.

See how Sentry Logs can surface hidden state bugs that stack traces alone can’t explain. In this walkthrough, we debug a React Native app with an Express.js backend where a missing diet value causes a crash. We inspect the issue, pull in the connected logs, and confirm whether the problem comes from an initial render or from real backend data. By combining issues, traces, and logs from the same session, you get the full story—and a faster path to the fix.

Learn how to use Sentry Logs to measure how often a bug occurs and which users it impacts. In this example, a React Native app with an Express.js backend crashes when the diet value becomes undefined. After identifying the root cause, we use Explore Logs to count how many times users switch their diet to “none,” filter the related log messages, and group results by user type to understand the impact.