I’ve been a firmware engineer at two wearable companies in the past, Pebble and Fitbit, and there was always one class of customer support tickets and user complaints that never went away: issues around battery life. It was a constant game of whack-a-mole with every new firmware version introducing a battery regression.

I’m thrilled to announce that Gartner added Monitoring as Code (MaC) as an emerging practice into their Hype Cycles for Monitoring and Observability and Site Reliability Engineering. We are extremely hyped about this recognition and being listed as a vendor innovating in that space. Since we founded Checkly, our vision has been that monitoring should be set up as code and live in your repository; it must be open-source based and feel natural for developers.

Interest in generative AI and large language models (LLMs) has exploded in popularity thanks to a slew of announcements and product releases, such as Stable Diffusion, Midjourney, OpenAI’s DALL-E, and ChatGPT. The arrival of ChatGPT in particular was a bellwether moment, especially for developers. For the first time, an LLM was readily available and good enough that even non-technical people could use it to generate prose, re-write emails, and generate code in seconds.