Operations | Monitoring | ITSM | DevOps | Cloud

To read the full findings from this research, visit our whitepaper "Decoding Cloud Credits" by clicking here. The allure of "free" cloud credits can be tempting, but beneath the surface lies a complex web of risks and consequences that can ultimately lock businesses into costly and restrictive cloud ecosystems. Our latest whitepaper, "Decoding Cloud Credits", explores the true costs of these promotional offers and the implications for businesses.

Large enterprises face the challenge of managing high-volume, very diverse data streams that span both legacy and modern, digital systems and applications. To gain timely, accurate insight across this kind of complexity, IT teams need observability platforms that can do more than just monitor - they must also unify, contextualize and enrich data so teams can act effectively to protect the availability of the services their customers rely on.

AWS did not intend to build Amazon EKS; it simply had to. Kubernetes adoption beamed light years ahead of AWS’s own managed container orchestration service. This forced AWS to develop a managed service to accommodate customers who wanted to use upstream Kubernetes but did not want to manage it themselves. As soon as AWS got around to it, it knocked the Kubernetes-based container management service out of the park. Not only is Amazon EKS simpler than Kubernetes, but EKS pricing may also be worth it.

At Civo Navigate London 2025, we hosted a panel discussion with Josh Mesout, James Faure, Abdul Hummaida, Jonas Vermeulen, and Daniel Miodovnik to discuss the latest trends and challenges in AI adoption. Through this conversation, the panelists covered topics such as the current state of AI adoption to the challenges of scaling AI, and the future of work.

In a microservices architecture, a single user request can pass through multiple services before completing. When performance drops or an error occurs, tracing that journey is the only way to locate the source. Distributed tracing provides that visibility. At its core are OpenTelemetry Spans — units of work that capture what each service does during a request.

In my previous blog, we demonstrated how the FrogML SDK streamlines the process of integrating custom-built or publicly sourced models from your IDE into JFrog Artifactory. Now that your models are securely stored, versioned, and managed, the natural next question arises: “Ok, so you have some models in JFrog Artifactory, now what?” This is where the real power of the JFrog Platform comes into play.

The scale of modern IT is outpacing human capacity. Microservices, multi-cloud deployments, and the Internet of Things (IoT) have created a complex IT ecosystem, generating an exponential volume of operational data. Traditional operations teams, regardless of their skill, struggle to keep up. Because of this, forward-looking leaders are adopting AIOps in IT, not as an upgrade, but as a foundational shift.

Like many others, as a company, we are going through a steep learning exercise with coding agents. As we are all learning together how to face the challenges of this new era of coding, I wanted to share our learnings with you and, in turn, benefit from what you have learned in your journey with using coding agents.