Operations | Monitoring | ITSM | DevOps | Cloud

As the use of artificial intelligence (AI) for software testing and quality assurance (QA) becomes increasingly prevalent, there are ethical considerations that must be addressed to ensure fairness, transparency, and accountability.

So you had a great day playing with really awesome new tech, solving big business challenges, and feeling like you really nailed it. Then you wake up the next day to an alert from Azure telling you you've blown your monthly budget and its only the first week of the month. We've all been there... right? Using any cloud service comes with a cost, but for most services the budget risk is low. Cost calculated daily isn't a problem when usage is predictable, but not everything works like that.

Checkly is the industry’s best tool to monitor your production applications. With the power of playwright, developers can test the systems they’ve developed, and roll out those tests as production monitors running from multiple geographies on the Checkly system. And Checkly monitors thousands of API endpoints with complex validation, setup and cleanup scripts, and reliable alerting. So why are we expanding into TCP-based checks?

Enterprises across industry verticals are looking for new ways to increase the efficacy of their businesses. One way to do this is building an efficient pipeline of processes, employees, devices, and services that are all tightly integrated to get the best return on investment. However, this requires an efficient telecommunication system where industry machines, personnel, and business services use continuous, performant, and reliable communications to work together.

We all know that Checkly is a ‘secret weapon’ for engineering teams who want to shorten their mean time to detection (MTTD). With Checkly, you can know within minutes if your service is unavailable for users, or acting unexpectedly. In this article we’ll talk about how Checkly traces can help you expand on the benefits of Checkly, adding insights that will help you diagnose root causes, and further reduce your mean time to resolution (MTTR) for outages and other incidents.

In a world where artificial intelligence (AI) is leaping forward — growing at a CAGR of almost 36% from 2024 to 2030 — questions about governance and ethics with the use of AI are surfacing. As humans continue to develop AI systems, it is crucial to establish proper guidelines to ensure powerful technologies like generative AI and adaptive AI are used in a responsible manner.