If you're working in IT monitoring and observability, you simply cannot ignore the power of Datadog and New Relic. These two tools have plenty of features that can revolutionize your entire observability strategy and give you complete control over your infrastructure. These tools are built so as to capture the tiniest of details, be it on applications, infrastructure, databases, servers, or something completely on the cloud.

During the early periods of cloud computing, most organizations used single-location data centers. These single-location data centers often faced higher risks of downtime and service disruption due to localized disasters or hardware failures. As a solution to these problems, cloud services like AWS introduced the concept of availability zones. This introduction was an important milestone in the evolution of cloud computing, as it facilitated high availability through geographic distribution.

IT monitoring software tracks the operations and activities of your end users and any software in your IT environment. IT experts use this specific type of software to determine the health and performance of your IT infrastructure and its components so that you can make well-informed and real-time decisions for resource provisioning and IT security. You may be researching the best IT monitoring software on the market today but don’t know where to start. That’s where we come in.

API monitoring is crucial for the health of your digital services. This article goes straight to the heart of it, addressing the tools, strategies, and metrics essential in spotting and solving API issues quickly. Learn to maintain and enhance the performance of your APIs, prevent downtime, and improve user experiences through effective monitoring techniques.

Regardless of how much effort teams put into developing, training, and evaluating ML models before they deploy, their functionality inevitably degrades over time due to several factors. Unlike with conventional applications, even subtle trends in the production environment a model operates in can radically alter its behavior. This is especially true of more advanced models that use deep learning and other non-deterministic techniques.