How often should you ping your site? Should you be checking every few minutes, or every hour? Surely you have other ways to detect problems, so maybe just a daily check of your API and main page would be enough, right? While there’s no single right answer for everyone, this post tries to break down how you can find the right cadence for your site checks.

Let’s face it. Incidents will always happen. We simply can’t prevent them. But we can strive to mitigate the impact incidents have on our product and customers. Ensuring high reliability depends on quickly and effectively finding and fixing problems. This is where the metric MTTR, standing for “mean time to restore” or “mean time to resolve,” becomes valuable for organizations.

The roles of testing and monitoring often intersect, yet they maintain distinct identities. In my near-decade in the tech sector I've observed how end-to-end (E2E) tests and synthetic monitoring, despite common frameworks and requirements, often fail to benefit from collaboration and synergy.

I am happy to announce that Checkly now supports parallel scheduling as a new way to schedule your checks. Parallel scheduling allows you to reduce mean time to detection, provide better insights when addressing outages, and give improved accuracy in performance trends, making it a powerful new feature for all Checkly users.

Observability isn't just a buzzword; it's a vital compass guiding us through the maze of system health and performance. As we’ve adopted microservice architectures, the ability to know ‘what is currently happening in our system’ has diminished as our operational resilience has increased. We find services scattered among a maze of interconnections and interdependencies. And even the logs that used to guide are now scattered throughout this maze.

I’m pretty sure that you’ve had a situation where you deployed a major UX change on your web app and missed the most obvious issues, like a misaligned button or distorted images. Unintended changes on your site can cause not only a sharp decline in user satisfaction but also a large fall in sales and customer retention. By identifying and resolving these discrepancies before the update went live, you could have prevented these outcomes.