When your IT systems are nearing capacity, you need to make decisions to expand provision, and many of those decisions will revolve around the choices you make to scale up vs scale out. For many the decision is intrinsically linked to their choice of platform and whether they are looking at cloud based, hybrid infrastructure or on-premises led strategies.

Dynatrace and AppDynamics are two of the most well-known Observability and monitoring tools. Even though they share many features, they have several differences that might make you choose one over the other. Dynatrace is great for comprehensive system performance monitoring. It covers everything from infrastructure and application performance to log management and real user monitoring. AppDynamics, on the other hand, focuses more on application performance and business transactions.

The Azure Well-Architected Framework for Azure Virtual Desktop Workloads details certain key considerations that you should include when architecting the monitoring of your AVD workloads and deployments. These key considerations are: Whilst native tools are provided, to meet the criteria of the Azure Well-Architected Framework, significant configuration is needed to leverage Azure Monitor. Monitoring AVD requires you to configure at least one Log Analytics workspace.

In May, GPT-4o was released, refining the GPT-4 architecture with native multi-modal input support, faster speeds, and a cheaper price per token. This week, with the release of GPT-4o mini, it’s even more cost-effective and quicker. This model is considered better than GPT-3.5 Turbo, being faster and smarter—a win all around. Let’s put it to the test in a real-world application to see just how good it is for software developers.

“O11y”, also known as Observability, is changing how we handle system performance. This guide will walk you through the essentials of O11y and how to implement it effectively. Let's dive in.