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Latest Videos

Surface and Confirm Buggy Patterns in Your Logs Without Slow Search

Debugging with logs in distributed systems can be a pain. It’s tough to search raw data looking for a pattern, relating potential causes with other logs, and checking trace and metrics data for more confirmation. Is finding one pattern enough? What if there are other problems? Who knows how many colliding factors are relevant? At Honeycomb, we’re flipping the script on the log search problem. Hear our resident experts, (former Splunk Ninja) Michael Wilde and Andy Dufour, discuss how Honeycomb customers have technically evolved their log analysis process to achieve fast pattern detection, skipping the search grep/search loop entirely.

Platform Engineering Is the Future of Ops

Ops and DevOps roles as we know them are on their way to becoming extinct—the future is platform engineering. While DevOps engineers typically focus on the application layer, platform engineers focus on the underlying infrastructure layer. Without a solid and reliable platform, it can be challenging to deploy and maintain software applications effectively. This can result in downtime, poor performance, and security vulnerabilities. Platform engineering enables software applications and services to run effectively and efficiently and has a direct impact on the user experience and the success of the entire organization.

Honeycomb Service Level Objectives (SLOs)

In this 3-minute video, you’ll see how Honeycomb’s actionable SLOs can help you get to the source of an issue faster. Using a real production SLO (latency per-event) as an example, we walk you through what exhaustion time alerts are and how to configure them, as well as how to use a heatmap to investigate and take action when things happen.

Building Observability in Your CircleCI Deploy

With Liz Fong Jones, Principal Developer Advocate at Honeycomb and Ryan Pedersen, Senior Solutions Engineer at CircleCI In this talk, you’ll learn how Honeycomb keeps its CircleCI workflow duration at about 10 minutes per build through parallelizing build steps, using native container builders per architecture, and tracing execution of the build to know where to optimize.