Operations | Monitoring | ITSM | DevOps | Cloud

It may surprise you to hear, but Honeycomb doesn’t currently have a platform team. We have a platform org, and my title is Director of Platform Engineering. We have engineers doing platform work. And, we even have an SRE team and a core services team. But a platform team? Nope. I’ve been thinking about what it might mean to build a platform team up from scratch—a situation some of you may also be in—and it led me to asking crucial questions. What should such a team own?

You know that old adage about not seeing the forest for the trees? In our Authors’ Cut series, we’ve been looking at the trees that make up the observability forest—among them, CI/CD pipelines, Service Level Objectives, and the Core Analysis Loop. Today, I'd like to step back and take a look at how observability fits into the broader technical and cultural shifts in technology: cloud-native, DevOps, and SRE.

To many engineers, the idea that you can accurately and comprehensively track your application's user experience using just a few simple metrics might sound far-fetched. Believe it or not, there are four metrics that aim to do just that. They're called the four Golden Signals and should be a core part of your observability and reliability practices.

So you’ve decided to take advantage of Site Reliability Engineering by hiring SREs for your company. Now, you have a second decision to make: Exactly how many SREs to hire. Do you need just one or two SREs? Or should you build a sprawling SRE team, with a dozen or more SREs on hand to support your organization’s reliability needs? The answers to these questions will, of course, vary; every business’s needs are different.

When it comes to building reliable and scalable software, few organizations have as much authority and expertise as Google. Their Site Reliability Engineering Handbook, first published in 2016, details their practices to maintain reliability as Google scaled. But when you have over a million servers running thousands of services across more than twenty data centers, how do you monitor them in a consistent, logical, and relevant way?