Operations | Monitoring | ITSM | DevOps | Cloud

Honeycomb Innovation Week: Debugging Agentic Workflows with Ken Rimple

Canvas skills are how your team's runbooks and tribal knowledge become an active part of the investigation instead of a document someone has to remember to open. Pre-built skills cover the most common investigation patterns out of the box. Custom skills let you encode the specific context, thresholds, and decision logic your team has accumulated, so every auto-investigation starts with your best thinking already applied.

Observability for the Agent Era: Day 2 | Launches

Honeycomb's Innovation Week: Observability for the Agent Era (May 12-14) For Day 2 of Innovation Week, Honeycomb's product and engineering teams will take you inside the new capabilities purpose-built for the agent era. Expect live demos, real scenarios, and a hands-on look at what it means to own observability for the Agentic era, with AI in Honeycomb to observe AI in production. A 3-Day Virtual Event for Teams Building the Future May 12: Get insights on how the best engineering teams are tackling the challenges of the agentic era.

Honeycomb Innovation Week: Observability With AI With Kale and Taylor

Watch this video to see the re-imagined Canvas in action, where auto-investigation has already ranked your hypotheses before you open the tab, multiplayer agents build on each other's work in real time, and a custom skill encoding your team's own runbook can reprioritize the entire incident before you've had your morning coffee.

Why Some Roles Care About Open Source & Why Others Don't: 4th Annual Observability Survey | Grafana

Note: We're happy to share that since the recording of this video, OpenTelemetry *has* graduated from the CNCF! SREs, developers, and CTOs say open source is essential to observability. Engineering managers and directors? Not so much. Grafana's 4th annual observability survey — 1,363 responses — reveals a split inside the same orgs that's worth a conversation.

Innovation Week Day 2: Observability for AI, and Observability With AI

AI is reshaping the SDLC in two directions at once. AI-generated code is shipping faster and with less human supervision than ever before, while agents and LLMs are running directly in production, where they behave very differently from traditional software: non-deterministic, with a wider blast radius than any single function or component, with no stack trace to catch when something goes wrong.

Choosing a Software Engineering Intelligence Platform (2026)

Engineering leaders face a common challenge: too much data scattered across too many tools, and no clear picture of how software delivery is actually performing. A software engineering intelligence platform pulls together metrics from your Git repositories, CI/CD pipelines, and issue trackers into a single view – helping you make decisions based on evidence rather than intuition.

How to Monitor Applications and End User Experiences

In this video, see how Skylar One helps you understand the impact of changes on application performance and the end user experience. By tracking service level metrics across an e commerce environment, you can quickly identify when performance degrades and how it affects user behavior. Explore how Skylar One enables: With Skylar One, teams can quickly connect performance changes to real user impact, helping ensure a consistent and reliable digital experience.