Jason Baum’s Post

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I am excited to give you an insider's look at platform engineering best practices that can be incorporated in your API strategy. Join Dan Boerner and I on 1/30 for an interactive fireside chat covering topics including: - Practical steps for integrating API platform engineering within your organization - How a single platform and architecture can support both domain and experience APIs - How the right level of abstraction can balance the needs of API consumers and producers 🚀 Register today ➡ bit.ly/3vF0sft

You can safely A/B test new features without code deployments using 𝗔𝗪𝗦 𝗖𝗹𝗼𝘂𝗱𝗪𝗮𝘁𝗰𝗵 𝗘𝘃𝗶𝗱𝗲𝗻𝘁𝗹𝘆 🕵️♀️ You can even create launches with automated rollbacks based on your own metrics 🏗️ I like it 😎

There are two kinds of things you can announce in a product release. Cool new sexy features, and the sum of many small improvements that together make your users experience better. I remember a big VMware release around 15 years ago (I'm sure some of you will remind me which one it was). We had one big banner feature (I think it was SMP HA, the ability to do HA even if your app was running across multiple cores or CPUs). But the truth was that the engineering team had made thousands of small changes that unblocked thousands and thousands of folks and just made VMware way easier to use. The first got everyone excited, but actually the dominant feedback was that the sum of all the small features and fixes enabled people to run VMware at much greater scale. What you focus on is always a tradeoff, big new features or stability, performance, reliability, polish. Ideally you're able do both. I'm super happy with this release because there's a great balance. Interactive Debugging is SUPER cool. I fully expect that it'll be game changing for so many as the power to open up a terminal to any point in your pipeline is so powerful. But I'm as proud with the dozens of PRs that addressed so many of the feedback from our user community. I'm so proud of our engineering team for this release and can't wait to hear our users experience as they get their hands on it.

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This describes my entire experience as a programmer.

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While there is a lot of talk of observability in our production apps and deployments. I don't see much discussion on observability in the CICD space. How do you know if your pipelines are getting slower? How do you identify if they are failing more often. How do you debug your pipeline to understand which bits are consistently slow and know where the constraint point is that your team should focus on to give the biggest improvement. This week I have been experimenting with Honeycomb as an open telemetry backend. Using a simple GitLab pipeline for example for adding observability to the pipeline flow. Being able to visualise pipeline flow can be very powerful for driving pipeline improvements. Also being observable and adding attributes to the span we can ask questions about the unknown unknowns like how many times has our pipeline run for each branch in the last 7 days and for each branch what was the 95th percentile for the pipeline duration. As always feel free to reach out if you want to discuss anything.