Software Engineering

From Honeycomb Customer to Bee: An Observability Champion's Journey

In early 2019, I was ramping up and wrapping my head around our areas of ownership, and that was also around the time when Liz Fong-Jones left Google and joined Honeycomb. Her arrival introduced me to the world of observability, which forever shifted my perspective on how my engineering colleagues and I could be empowered to deeply and collaboratively understand and manage the services and systems in our care.

Leveraging Cognitive Diversity to Tackle System Complexity

When we compose teams or staff an incident review, we almost always use identity as a proxy for perspective. We include someone from platform, someone from the application layer, someone from the team that owns the affected service. We assume that different roles and tenures will produce different mental models of the problem, and sometimes that assumption holds. But research on how people actually build mental models of complex systems suggests it fails more often than we'd expect.

Production Is Where the Rigor Goes

In early February, Martin Fowler and the good folks at Thoughtworks sponsored a small, invite-only unconference in Deer Valley, Utah—birthplace of the Agile Manifesto—to talk about how software engineering is changing in the AI-native era. The longer I sit with this recap, the more troubled I am by what it doesn't say. I worry that the most respected minds in software are unintentionally replicating a serious blind spot that has haunted software engineering for decades: relegating production to the realm of bugs and incidents.

“You Had One Job”: Why Twenty Years of DevOps Has Failed to Do it

I think the entire DevOps movement was a mighty, twenty year battle to achieve one thing: a single feedback loop connecting devs with prod. On those grounds, it failed.

What Is Application Performance Monitoring?

Application performance monitoring, also known as APM, represents the difference between code and running software. You need the measurements in order to manage performance.

Design as Infrastructure

For those not familiar with the term design system, at its core, it is a collection of reusable building blocks such as buttons, colors, text styles, icons. These blocks are also commonly referred to as components, which make everything look and feel cohesive, like it belongs to the same product.

5 Best Practices for Incorporating AI Into Your Team

Honeycomb’s Jessica Kerr and Fred Hebert recently hosted a webinar with Courtney Nash of The VOID where they dug into one of the biggest questions in tech right now.

What the 2025 DORA Report Teaches Us About Observability and Platform Quality

The 2025 DORA State of AI-Assisted Software Development Report delivers a critical insight for technology leaders: AI is fundamentally an amplifier, not a solution. It magnifies the strengths of high-performing organizations with robust observability while exposing the dysfunctions of struggling ones.

Disposable Code Is Here to Stay, but Durable Code Is What Runs the World

Every day I seem to run into yet another post with someone solemnly opining that “writing code has never been the hardest part of software engineering.

Honeycomb Observability Day London: A Jam-Packed Day of Great Talks

Beyond Shift Left: Engineering Leaders Increase Speed and Resilience With Observability

We recently had the privilege of hosting several industry experts and technology executives across platform strategy, SRE, and engineering enablement for breakfast at our Observability Day in London.

Dashboards, or Launchpads?

Gotta Go Slow

I anticipated this would be a challenging time and that I would be exhausted. So, the plan became: do all the demanding things, take my sabbatical in May, and use April as an ‘in-between’ period with a bit less pressure. I would willingly step off the gas and let other SREs on the team cover pressing matters, as a sort of pre-game for my full month away.

Data Strategy for SREs and Observability Teams

The idea that telemetry data needs to be managed, or needs a strategy, draws a lot of inspiration from the data world (as in, BI and Data Engineering). Your company most likely has a data team that manages the data warehouse(s), data pipelines, data sources, and reporting tools. These teams are also constantly balancing costs with their user and stakeholder needs, usability, data retention, granularity, etc. Sound familiar? That’s because if you’re working on observability data, these teams are at least several years ahead of you in addressing these tradeoffs and considerations—and can teach us quite a lot.

How Does ‘Vibe Coding’ Work With Observability?

You can’t throw a rock without hitting an online discussion about ‘vibe coding,’ so I figured I’d add some signal to the noise and discuss how I’ve been using AI-driven coding tools with observability platforms like Honeycomb over the past six months. This isn’t an exhaustive guide, and not everything I say is going to be useful to everyone—but hopefully it will clear up some common misconceptions and help folks out.

AI for Software Engineering is Just Another “Paradigm Shift”

How many of you started with technologies you still use exactly the same way today? Even if you’re a master Lisp/Clojure developer, you’ve still evolved, right? I should really get my head around those parentheses some day.

Building AI-Ready Infrastructure for the Enterprise

Last week marked the inaugural HumanX conference, a convening of leaders, technologists, policy makers, and media, all brought together to discuss the state of AI and its potential impact on the future of software, business, and society.

Does AI Help Write Better Software, or Just… More Code?

As software teams race to integrate AI into their development workflows, we need to ask ourselves: are AI-powered tools actually making software better?

How I Code With LLMs These Days

I first started using AI coding assistants in early 2021, with an invite code from a friend who worked on the original GitHub Copilot team. Back then, the workflow was just single-line tab completion, but you could also guide code generation with comments and it’d try its best to implement what you want.

The Future and The Floor: Framing Investments for Growth

There are a limited number of investments that a team can make in any given year and it can be daunting to choose the “right” ones. To simplify our options, I keep coming back to “the future” and “the floor.”