A server monitoring tool is software that monitors the operation and general health of servers and other components of IT infrastructure. These tools continuously track and gather information on a variety of parameters, such as CPU utilization, memory usage, disc space consumption, network traffic, and application performance. So, you get real-time insights into a server’s functionality and health, and IT specialists can identify and address issues before they affect end users.

This practitioner blog will show you how to consume telemetry data from your network devices in five easy steps. Telemetry is a monitoring technology used to do high-speed data collection from network devices. According to EMA research on network performance management, “71% of enterprises are interested in collecting streaming network telemetry with their network management tools.” This next-generation approach to monitoring has been expected to replace SNMP for years.

We’re happy to announce that the Sentry SvelteKit SDK is now generally available and ready to help you monitor your SvelteKit application. Last year, we entered the Svelte ecosystem by creating an SDK for Svelte, which provides support for Svelte single page apps. We knew that SvelteKit was already quite far along back then and we kept a close eye on its development. We also received a lot of requests from the community to support SvelteKit.

Since Microsoft announced the RDP Shortpath feature was going to be enabled by default on September 6, 2022 for all Azure Virtual Desktop (AVD) customers, monitoring and troubleshooting this feature has become important. RDP Shortpath feature improves the AVD connectivity by establishing a direct UDP protocol between the AVD session hosts and the Remote Desktop Client by reducing the dependency on gateways.

With Cribl Stream, our customers are experiencing choice and control over their data that would have been a pipe dream (or maybe I should say a pipeline dream) before. The ability to get the right data to the right destination in the right format is extremely powerful. Stream can optimize the data being sent to expensive destinations; you can remove unnecessary or redundant fields, drop unnecessary events, or even pull valuable metrics from verbose logs. Optimizing your data has a few benefits.

Welcome to the digital realm, where networks thrive and connectivity reigns supreme! In this age of remote work and virtual collaboration, our networks have become the unsung heroes of productivity. But have you ever wondered how they seamlessly navigate the vast expanse of cyberspace while ensuring optimal performance? Enter the enigmatic world of remote network monitoring! In this blog post, we're embarking on an electrifying adventure to demystify the magic behind remote network monitoring.

Honeycomb recently released our Query Assistant, which uses ChatGPT behind the scenes to build queries based on your natural language question. It's pretty cool. While developing this feature, our team (including Tanya Romankova and Craig Atkinson) built tracing in from the start, and used it to get the feature working smoothly. Here's an example. This trace shows a Query Assistant call that took 14 seconds. Is ChatGPT that slow? Our traces can tell us!

“Observability” seems to be the buzzword du jour in IT these days but what does it actually mean, and how is it any different from plain, old monitoring? In simple terms, observability is the ability to understand how a system is performing and how it is behaving from the data that system generates. It is not just about monitoring metrics or collecting logs, but also understanding the context of those metrics and logs, and how they relate to the overall health of the system.

In the last post, we addressed validating whether a string was null or empty. Today I will speak about another good Best practice, Tips, and Tricks that you must consider while designing your business processes (Logic Apps) and another usual validation requirement: How to validate if an Array is empty or not.

This is the third and final post (for now) in the series about developing email templates with MJML and deploying them to AWS. In the previous post, we developed a Gulp script to automatically build HTML from the MJML file and insert it in a template file for AWS. In this post, we will set up an automated build and deployment of the email template using Azure DevOps. A quick recap.