The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.
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.
In this article, we’ll cover our newest feature- Microsoft Teams notifications! We’ll walk you through how to set it up, and we’ll take a look at why we are constantly making the MetricFire experience better.
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.
Kubernetes has emerged as the de facto standard for container orchestration, with its ability to automate deployment, scaling, and management of containerized applications. However, even with the best practices and expertise, Kubernetes deployment can sometimes be a complex and challenging process. It involves multiple layers of infrastructure, including the application, Kubernetes cluster, nodes, network, and storage, and each layer can have its own set of issues and challenges.
