The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.
Cloud infrastructure and application monitoring dashboards are critical to gaining visibility into the health and performance of your system. But what are the best metrics to monitor? What are the best types of visualizations to monitor them? How can you ensure your alerts are actionable? We answered these questions on our webinar Build the Ultimate Cloud Monitoring Dashboard.
Communication with our users is very important. You want them to be aware of the new features that your platform exposes, exciting news about the company, but also about the status of the services that you are building for them. This includes information about all the functionalities and the infrastructure and applications behind them – when they work correctly and efficiently and when they don’t.
Before diving into how to monitor HTML Canvas, let’s define it. HTML Canvas is a powerful feature of HTML5 that allows developers to create and manipulate graphics, animations, and other visual effects using JavaScript. It’s a blank slate on which you can draw whatever you want, making it an excellent tool for creating interactive and dynamic web content.
Overprovisioning or underprovisioning your Kubernetes resources can have significant consequences on both your budget and your app performance. By underprovisioning your Kubernetes infrastructure, you’ll end up with lagging, underperforming, unstable, or non-functional applications. On the opposite end of the spectrum, overprovisioning is a costly issue: Organizations spent almost $500 billion on cloud resources in 2022, yet an estimated 30% of those were wasted.
Many developers and product teams are iterating faster and deploying more frequently to meet user expectations for responsive and optimized apps. These constant deployments—which can number in the dozens or even hundreds per day for larger organizations—are essential for keeping your customer base engaged and delighted. However, they also make it harder to pinpoint the exact deployment that led to a rise in errors, a new error, or a performance regression in your app.