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Honeycomb

Discover Unknown Service Interaction Patterns With Istio & Honeycomb

Istio service meshes enable organizations to secure, connect, and monitor microservices to modernize their enterprise apps more swiftly and securely. With the addition of distributed tracing and powerful observability tooling, platform operators can gain immediate actionable insights about their applications.

Intercom: Building a More Resilient Ecosystem Through Observability

Learn how Intercom implemented Honeycomb’s distributed traces to learn about production. Kesha Mykhailov, Product Engineer at Intercom joins Honeycomb Developer Advocate Jessica Kerr, and Account Executive Michael Wilde to discuss how Intercom uses distributed traces to streamline their observability workflows, allowing their product engineers to learn about and from their production to increase Intercom’s resilience. Topics include.

See How Coveo Engineers Reduced User Latency

Many teams are wasting far too much time and energy searching through massive amounts of log data trying to find answers to user latency issues. Metrics data doesn’t help either as it only tells you that there is a problem, not where to fix it. This is why Coveo turned to observability. Through implementing observability with Honeycomb, Coveo was able to reduce their user latency by 50 percent.

Join Jeli and Honeycomb for an Incident Response and Analysis Discussion

Solutions Engineers Vanessa Huerta Granda and Emily Ruppe from Jeli, along with Honeycomb’s Field CTO Liz Fong-Jones and SRE Fred Hebert discuss some of our more interesting recent incidents and how we use Honeycomb and Jeli together for incident response.

Learn How SumUp Implemented SLOs to Mitigate User Outages and Reduce Customer Churn

Blake Irvin and Matouš Dzivjak from SumUp’s Software Engineering team, Honeycomb Solution Architect Michael Sickles and Account Executive Nathan Leary, discuss how SumUp incorporated observability, specifically, SLOs, to identify and resolve issues before they grew into customer-noticeable problems.

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.

Ask Miss O11y: Is There a Beginner's Guide On How to Add Observability to Your Applications?

I want to make my microservices more observable. Currently, I only have logs. I’ll add metrics soon, but I’m not really sure if there is a set path you follow. Is there a beginner's guide to observability of some sort, or best practice, like you have to have x kinds of metrics? I just want to know what all possibilities are out there. I am very new to this space.

How Do We Cultivate the End User Community Within Cloud-Native Projects?

The open source community talks a lot about the problem of aligning incentives. If you’re not familiar with the discourse, most of this conversation so far has centered around the most classic model of open source: the solo unpaid developer who maintains a tiny but essential library that’s holding up half the internet. For example, Denis Pushkarev, the solo maintainer of popular JavaScript library core-js, announced that he can’t continue if not better compensated.