Operations | Monitoring | ITSM | DevOps | Cloud


Future-Proof Your IT Ecosystem: The Road to IT Optimization

Learn more about how IT optimization reduces operating costs, improves efficiency and increases application performance for your business. By working out an optimization initiative, businesses can refine the functionality of their enterprise architectures, ensuring that they’re using resources to their utmost potential. This not only streamlines your automating processes but also bolsters overall performance and business efficiency, allowing you to stay competitive.

AI Explainer: Feature Extraction

In a previous blog post, which was a glossary of terms related to artificial intelligence, I included this brief definition of "feature extraction": Let’s go a bit deeper on that. In the ever-expanding landscape of machine learning, feature extraction stands out as a crucial technique for enhancing the performance of models and uncovering valuable insights from complex datasets.

A Comprehensive Guide to IT Capacity Planning

Effective capacity planning and management are fundamental to maintaining a robust IT infrastructure, helping teams optimize available resources to meet performance needs. In this guide, we’ll walk you through everything you need to know about these invaluable processes to ensure your organization’s IT infrastructure is prepared for current and future demands.

Observability vs. Monitoring: How Do They Work?

As organizations increasingly depend on distributed system architectures to provide modern applications and microservices, their legacy monitoring tools struggle to keep pace. These outdated systems are often based on predictable failures, but when an unforeseen performance issue occurs, it can lead to outages and unplanned downtime that impacts your customers and your business.

AI Explainer: Supervised vs. Unsupervised Machine Learning

Machine learning is a powerful tool that enables computers to learn from data and make predictions or decisions without being explicitly programmed. Two fundamental approaches to machine learning are supervised and unsupervised learning. In this blog post, we'll explore the key differences between these two approaches, along with examples of their applications.

AI Explainer: Continuous Space

I wrote a previous blog post, "AI Explainer: What's Our Vector, Victor?," to scratch the surface on vector databases, which play a crucial role in supporting applications in machine learning, information retrieval and similarity search across diverse domains. From that blog arose the topic of embeddings, which I addressed in a subsequent post, "AI Explainer: Demystifying Embeddings." In explaining embeddings, the notion of continuous space was presented, which is the topic of this blog.

What Is Application Performance Monitoring?

Applications serve as the backbone of countless operations, driving productivity, customer experience and business success. Tracking and managing their performance is therefore critical to maintain continuity and efficiency, enabling IT teams to proactively identify and resolve issues before they lead to downtime and potential revenue loss. That’s where application performance monitoring (APM) comes in.

OTel Explainer: Simplifying Observability in Modern IT Environments

In today's rapidly evolving landscape of distributed systems and microservices, understanding how applications behave in production environments has become increasingly complex. Traditional monitoring tools often fall short when it comes to providing comprehensive insights into the performance and behavior of these modern architectures.