July 2023 Summaries

Checkly has been recognized by Gartner for its work on Monitoring as Code (MaC), a philosophy that treats monitoring configurations as code, bringing programmability, speed, and reliability to the monitoring workflow. This recognition is significant, especially with the rise of modern software development, where traditional monitoring methods are struggling to keep up. MaC enables DevOps and SRE teams to manage monitoring configurations like application code, extending their capabilities and enabling them to streamline their workflows. Checkly's approach to MaC emphasizes three core pillars: Code, Test, and Deploy, which facilitate the integration of monitoring with existing development processes, increasing efficiencies across systems. The introduction of Checkly's CLI has also received a warm welcome, further enhancing the MaC workflow for developers.

Gartner has recognized Monitoring as Code (MaC) as an emerging practice, indicating its growing adoption and maturity in the monitoring and observability space. MaC is a code-driven approach to monitoring that enables collaboration, optimization, and automation of monitoring configurations, ultimately supporting high-velocity changes and reducing the risk of missed alerts. By codifying and version-controlling monitoring configurations, teams can achieve automation, consistency, and efficiency in their monitoring setups, which is essential for modern DevOps teams and engineers. MaC has been adopted by hundreds of companies, and its benefits include improved efficiency and collaboration, supporting continuous delivery, and enabling the rapid deployment of features and infrastructure while reducing the risk of missed alerts.

Table of contents In recent weeks, I've noticed an increase in job applications generated by ChatGPT, raising concerns about their authenticity. While AI-powered language models like ChatGPT can be beneficial for research and creativity, relying solely on them for applications can lead to unauthentic and unimpressive submissions. Misinformation is a common issue, with applicants mentioning skills and experiences they don't actually possess. Generic and long cover letters are also prevalent, lacking personalization and specific examples of impact. Additionally, AI-generated answers often lack relevant specifics and fail to demonstrate genuine enthusiasm for the company or role. To avoid these pitfalls, applicants should use ChatGPT as a source of inspiration while adding their unique experiences and skills to create personalized and authentic applications that showcase their value and potential.