Operations | Monitoring | ITSM | DevOps | Cloud

Since the inception of public clouds, a lot of CXOs have considered moving their IT infrastructure to the cloud and many have already done that. If your organization is considering migration to the cloud, learn what drove this mass movement from on-premises servers to the cloud. In this article, we'll explain the major reasons why organizations prefer the cloud, the issues you should watch out for, and how you should protect your cloud infrastructure.

Kubernetes has been facilitating container orchestration for around a decade for both stateful and stateless application workloads. With the recent rise of AI and the advent of tools like Kubeflow and Argo Workflows, Kubernetes is also becoming a first-class citizen when it comes to running AI workloads. When you are training a model on K8s, you may be tweaking many parameters and have to test each of them one by one.

Box.com is a cloud-based content management and file-sharing platform designed for the enterprise and used by nearly 100,000 companies around the world. When a Box outage strikes, businesses can experience costly disruptions. On February 19, 2025, a disruption in core Box services including uploads, downloads, and the All Files page, affected thousands who depend on the cloud storage and collaboration platform.

Snowflake is a powerful, cloud-based data platform designed for high-performance analytics. Whether you're running massive analytical queries, managing structured and semi-structured data, or optimizing data pipelines, visibility into your Snowflake instance is essential. Performance bottlenecks, query execution delays, and unexpected cost spikes can quickly become issues without proper monitoring.

This weekend, I binge-watched Netflix’s new series Zero Day, starring Robert De Niro. The series has sparked excitement and curiosity among cybersecurity enthusiasts and political thriller fans alike. As the title suggests, the show revolves around a cyberattack that exploits unknown vulnerabilities—so-called “zero days”—to wreak havoc on critical systems. But what if the organizations targeted in Zero Day had the right cybersecurity strategy in place?

Artificial Intelligence (AI) is reshaping industries worldwide, and Sub-Saharan Africa is no exception. Across the region, governments, businesses, and start-ups are recognising the potential of AI to drive economic growth, improve efficiencies, and enhance decision-making. Yet, as AI adoption accelerates, so does the demand for robust digital infrastructure, including high-performance computing, data centres, and connectivity.

OpenTelemetry is a big, big project. It’s so big, in fact, that it can be hard to know what part you’re talking about when you’re talking about it! One particular critique I’ve seen going around recently, though, is about how OpenTelemetry is just ‘three pillars’ all over again. Reader, this could not be further from the truth, and I want to spend some time on why.

When you think about “AI reliability,” what comes to mind? If you’re like most people, you’re probably thinking of generative AI model accuracy, like responses from ChatGPT, Stable Diffusion, and Sora. While this is certainly important, there’s an even more fundamental type of reliability: the reliability of the infrastructure that your AI models and applications are running on. AI infrastructure is complex, distributed, and automated, making it highly susceptible to failure.

OpenTelemetry is an open-source observability framework designed to instrument, generate, collect, and export telemetry data, including traces, metrics, and logs. It is vendor-agnostic, allowing developers to send data to multiple backend services like Last9, Prometheus, Datadog, or Jaeger without vendor lock-in. For Next.js applications, OpenTelemetry is particularly useful due to the framework’s hybrid rendering approach.

If you've ever deployed a distributed system at scale, you know things break—often in ways you never expected. That’s where Chaos Engineering comes in. But running chaos experiments without robust observability is like debugging blindfolded. This guide will walk you through how observability empowers Chaos Engineering, ensuring that your experiments yield meaningful insights instead of just causing chaos for chaos’ sake.