Operations | Monitoring | ITSM | DevOps | Cloud

AI Agent for Incident Resolution: Combining Intelligence with Autonomous Actions

Incident management is a high-stakes function. IT operations teams and SRE teams may play different roles, but when a priority incident surfaces, it is often all-hands-on-deck to ensure it is resolved in minimal time. That’s because of the high impact of incidents-if not resolved in time, they can cascade and impact other IT systems, leading to downtime, business disruptions, monetary losses, and impacting brand value, compliance, and regulatory rules.

AI-Powered Translation Tools: A Hidden Asset for Scaling DevOps Globally

DevOps or development (Dev) and IT operations (Ops) teams are no longer confined to single geographic locations or language groups. With over 80% of organizations now practicing DevOps (a figure projected to reach 94% in the near future), the challenge of scaling operations globally has never been more critical. Yet, one persistent bottleneck continues to slow down even the most sophisticated DevOps workflows: language barriers.

AI Software Development Solutions: Transforming Modern Business

Artificial intelligence is no longer a futuristic concept-it has become a critical driver for businesses across all industries. Companies that embrace AI can streamline operations, unlock valuable insights from data, and innovate faster than their competitors. By leveraging ai software development solutions, organizations can automate routine tasks, accelerate product development, and improve decision-making. These solutions are increasingly central to digital transformation strategies, giving businesses a competitive edge in a rapidly evolving marketplace.

Regain Control and Visibility of All IT Assets Across Your Organization

When you don’t have reliable processes for managing IT assets, you can quickly lose control. Asset inventories lose their accuracy, data across tools like CMDBs and spreadsheets stops matching reality, and no one can say with confidence what equipment is in use, where it’s located, how it’s connected, and whether it’s still needed. For data center professionals, a lack of asset visibility creates real risks.

Why GPUs accelerate AI learning: The power of parallel math

What makes GPUs so crucial for AI workloads? Is it just about raw processing power, or is there more to it? As we explore the world of AI infrastructure, understanding the role of GPUs is essential. Let's dive into the math behind AI. At its core, AI is all about mathematics, and matrix multiplication is a critical component. Whether you're training a model to recognize images or predict outcomes, the data is converted into massive arrays or matrices of numbers.

Demo of Raygun's remote MCP

This Raygun remote MCP demo highlights the new depth of context available. The agent isn’t just fetching error lists. it’s reasoning through stack traces to find the issues. Combine this with the ability to now view associated deployment versions, browser information, breadcrumbs, customer data and more, the agent becomes infinitely more capable at solving errors. We’ve even heard of some of the early testers going from having errors in production to having them solved within minutes.

Data Sovereignty in the Age of AI: A Conversation with Kelsey Hightower and Mark Boost

Join Kelsey Hightower and Mark Boost at Civo Navigate London as they discuss sovereignty in the context of AI and cloud computing. The conversation highlights the need for a more nuanced approach to cloud computing, one that balances the benefits of public cloud with the need for control and sovereignty. The discussion emphasizes the importance of open protocols and the role of the community in driving innovation, and notes that the adoption of AI workloads is driving a shift towards more decentralized and sovereign cloud architectures.

Bridging partners in pursuit of agentic AI - Part 1: Why partnerships matter for enterprise intelligence

The pace of change in AI development has been dizzying. In just a few years, we’ve moved from experimenting with AI, machine learning (ML), retrieval augmented generation (RAG), and agents to asking how these innovations can solve real business problems. Enterprises are no longer impressed by the novelty and possibilities; instead, they expect outcomes.

Bridging the Gap Between Customer Support and Data Intelligence in Modern Operations

Customer support and operational data used to live in different worlds. Support teams handled people and conversations, while operations focused on systems and uptime. But those worlds are no longer separate, and pretending they are only slows things down. A spike in complaints might point to a backend issue. A confusing interface can trigger more tickets than any automated alert ever could.