Operations | Monitoring | ITSM | DevOps | Cloud

As IT environments continue to expand in scope and complexity, understanding their impact on organizations is more important than ever. That’s why ScienceLogic commissioned research specialist Vanson Bourne to survey 400 IT operations professionals across the USA, UK, Germany, and Canada with the goal of understanding the challenges they’re facing and the technologies—including automation, AI, and generative AI—they’re using to overcome them.

Azure OpenAI Service is Microsoft’s fully managed platform for deploying generative AI services powered by OpenAI. Azure OpenAI Service provides access to models including GPT-4o, GPT-4o mini, GPT-4 Turbo with Vision, DALLE-3, and the Embeddings model series, alongside the enterprise security, governance, and infrastructure capabilities of Azure.

Employees can sometimes be a step ahead of their organizations when it comes to leveraging new technology. This cybersecurity month, we’re looking at the risks of shadow AI and outlining a multi-pronged approach to turn your team's AI enthusiasm from a security risk to a productivity driver.

In the ever-evolving DevOps and site reliability engineering (SRE) landscape, Kubernetes stands out as a pivotal technology, revolutionizing how we deploy, scale, and manage containerized applications. K8s offers powerful orchestration capabilities, ensuring our applications are resilient and can scale seamlessly to meet varying demands. However, as robust as Kubernetes is, managing it efficiently requires significant expertise and effort.

Kubernetes has become the dominant orchestration platform for cloud-native apps– and for good reason. It can be a powerful tool in your software development lifecycle. But how do you know if your Kubernetes-based app can handle the demands of production traffic? Kubernetes alone isn’t always enough to ensure your app’s performance under load. In many cases, it is, but it’s always wise to know your application’s limits.

Generative AI has emerged as a powerful force for synthesizing new content—text, images, even music—with astounding proficiency. However, monitoring, optimizing, and maintaining the health of these complex AI systems is challenging, and traditional observability tools are struggling to keep pace. At Grafana Labs, we believe that every data point tells a story, and every story needs a capable narrator.