Operations | Monitoring | ITSM | DevOps | Cloud

It’s been another busy few months here at Gremlin. Overall, our team has been working on feature improvements to enable teams to measurably improve the reliability of their systems, whether that’s through broadening platform support so you can run Gremlin in more places, making it easier than ever to identify reliability risks, or improving reporting so you can manage reliability programs effectively at enterprise scale. Here’s a summary of what’s new.

The cloud’s elasticity—the ability to scale resources up and down in response to changes in demand—as well as variable cost structures offer significant advantages, enabling enterprises to move from rigid capex models to elastic opex models where they pay for what they provision, with engineers in control and focused on innovation, becoming true business accelerators.

IT leaders are thrilled about the potential of Generative AI for IT Operations. But they also want to know how it works, why it works, and what it will do for them before taking the leap and adopting this new technology. Allow me to share my perspective on the hype and the truth behind Generative AI. I’m the Field CTO for BigPanda, Operational Intelligence and Automation driven by AIOps.