Operations | Monitoring | ITSM | DevOps | Cloud

In the digital era, where data flows like a ceaseless river, real-time monitoring stands as a pivotal technology, allowing organizations to not only keep pace but also to deeply understand the intricate dance of their operational ecosystems. This technology is not just about keeping tabs; it’s about gaining a profound, almost intuitive sense of the micro-worlds within which systems, containers, services, and applications pulse and thrive.

Today, every business is a tech business. Even veterinarians need to make sure their tech stack is up to par, so they can deliver the best care to pets whatever their need. Enter Vetcor, a shining example of how technology can revolutionize the management and operations of veterinary care across North America. Leveraging NinjaOne, Vetcor has successfully consolidated an IT ecosystem of 15,000 endpoints across more than 850 veterinary practices across the United States and Canada.

In the dynamic world of container orchestration, Kubernetes stands out as the undisputed champion, empowering organizations to scale and deploy applications seamlessly. Yet, as the deployment scope increases, so do the associated Kubernetes workload costs, and the need for effective resource capacity planning becomes more critical than ever. When dealing with containers and Kubernetes you can find yourself facing multiple challenges that can affect your cluster stability and your business performance.

Monitoring SNMP (Simple Network Management Protocol) devices is crucial for maintaining network health and security, enabling early detection of issues and proactive troubleshooting. Continuous monitoring ensures efficient resource utilization, minimizes downtime, and enhances overall network performance. In this article, we'll detail how to use the Telegraf agent to collect SNMP (MIB) performance statistics that you can forward to a data source.

Since the release of ChatGPT, there’s been growing excitement about the potential of generative AI—a class of artificial intelligence trained on pre-existing datasets to generate text, images, videos, and other media—to transform global businesses. Last year, we released our own generative AI-powered DevOps copilot called Bits AI in private beta. Bits AI provides a conversational UI to explore observability data using natural language.

There’s more pressure than ever to deliver high-availability Kubernetes systems, but there’s a combination of organizational and technological hurdles that make this ‌easier said than done. Technologically, Kubernetes is complex and ephemeral, with deployments that span infrastructure, cluster, node, and pod layers. And like with any complex and ephemeral system, the large amount of constantly-changing parts opens the possibility for sudden, unexpected failures.

Today at Google Next, Charity Majors demonstrated how to use Honeycomb to find unexpected problems in our generative AI integration. Software components that integrate with AI products like Google’s Gemini are powerful in their ability to surprise us. Nondeterministic behavior means there is no such thing as “fully tested.” Never has there been more of a need for testing in production!

Grafana Cloud offers organizations an end-to-end observability platform, without the overhead of building and maintaining their own observability stack. We’re constantly shipping new Grafana Cloud features to ensure users get the most out of the fully managed platform, which is powered by our open source Grafana LGTM Stack (Loki for logs, Grafana for visualization, Tempo for traces, and Mimir for metrics).

Node.js was introduced over 20 years ago and remains a popular choice for web application teams with over 30 million users. Sites such as Netflix, PayPal, and Uber continue to rely on Node.js to build and maintain their applications.

NMS can do so much that one blog topic triggered an idea for another, and another, and here we are, six posts later and I haven’t explained how to install NMS yet. The time for that post has come.