In episode 19 of O11ycast, Liz and Charity speak with Shelby Spees of Honeycomb. They discuss Shelby’s diverse engineering background and how the software community has gradually pulled back the curtain on observability.
In episode 18 of O11ycast, Charity and Liz speak with Michael Hood, a senior staff performance engineer at Optimizely. They discuss real user monitoring (RUM), the shortcomings of traditional metrics, and ramping up observability.
In episode 17 of O11ycast, Charity and Liz are joined by Pete Hodgson, an independent software delivery consultant. They discuss the DORA report, closing the CI/CD gap, and leveling up software delivery.
In episode 16 of O11ycast, Charity and Liz are joined by Abby Bangser of MOO. They discuss observability from a testing engineer’s perspective, the key factors that lead a company to spin up a testing team, and the highlights of DeliveryConf 2020.
In episode 15 of O11ycast, Charity and Liz speak with Rachel Myers of Google and Emily Nakashima of Honeycomb. They discuss serverless development, customer-vendor relations, using logs correctly, and better understanding your data model.
In episode 14 of O11ycast, Charity and Liz are joined by Mehdi Daoudi of Catchpoint. They discuss the importance of team players when scaling, as well as the hidden value in measuring the experience of your employees, not just your customers.
In episode 13 of O11ycast, Charity Majors and Liz Fong-Jones talk with Natalie Bennett, Software Engineering Manager at Pivotal. They discuss the difference between projects and teams, continuous verification, and diagnosing failed deployments.
In episode 12 of O11ycast, Charity Majors and Liz Fong-Jones speak with Rich Archbold of Intercom. They discuss the crucial importance of timely shipping, high-cardinality metrics, and the engineering value of running less software.
In episode 11 of O11ycast, Charity Majors and Liz Fong-Jones speak with Gremlin chaos engineer Ana Medina. They discuss the relevance of breaking things in order to engineer them more efficiently, monitoring vs observability, and chaos engineering at scale.