We live in a data-rich world - every click, swipe, like, share, and purchase online generates data points companies use to optimize offerings. However, even vast real-world data has limitations in developing robust artificial intelligence (AI) and data models, particularly with regard to AIOps (Artificial Intelligence for IT Operations). Enter synthetic data.

Organizations face a constant fight against cyber threats. One such solution that is gaining prominence in this battle is Managed Detection and Response (MDR). In this article, we’ll take a look at what MDR is and how it helps organizations protect themselves, explore the different types of MDR solutions available, and outline some of the key considerations you should keep in mind when selecting an MDR provider.

After 15 years working on SQL Server and believing the world revolved around databases, I came to SolarWinds where I could learn more about operational technology and its role in full-stack observability. I've had fun watching these two industries collide, delivering on the promise of better value for businesses. I recently read “End of Abundance in Tech” by Ben DeBow, and it encouraged me to think about what the next big market shift will mean for my industry.

InvGate Insight was added to the latest version of Gartner’s Voice of the Customer for Software Asset Management Tools Report. The inclusion is a recognition of the tool’s usefulness for this particular practice. The Voice of the Customer is based on peer reviews and currently features eight vendors. Keep reading to learn more about this report.

Multi-step synthetic transactions, also known as multi-step transactions or multi-step scripts, are automated tests that simulate complex user interactions with a website or web application. Unlike a single-step transaction (like page load), multi-step transactions involve a series of sequential steps or workflows that mimic real-world user journeys.

Numerous companies keep launching AI/ML features, specifically “ChatGPT for XYZ” type productization. Given the buzz around Large Language Models (LLMs), consumers and executives alike are growing to assume that building AI/ML-based products and features is easy. LLMs can appear to be magical as users experiment with them.

New in Cribl 4.5, the Model Driven Telemetry Source enables you to collect, transform, and route Model Driven Telemetry (MDT) data. In this blog, you’ll learn how to explore the YANG Suite to understand the wide variety of datasets available to transmit as well as how to configure the tools to get data flowing from Cisco IOS XE network devices to Cribl Stream.

Research firm, IDC, published a study in early February 2024 predicting that Google Cloud Platform (GCP) customers break even after just 10 months. Moreover, the study, The Business Value of Google Cloud IaaS, reported that after migrating to GCP, the participants were on track to achieve a 318% ROI in five years. Here’s the thing. Achieving these milestones requires a robust GCP cost monitoring and optimization plan.

In the world of IT support, artificial intelligence (AI) has become a game-changer, revolutionizing how organizations handle tech issues. From streamlining ticketing systems to providing instant chatbot solutions, AI for IT support has proven its worth. We’ve already explored the various applications of ChatGPT for IT support, such as writing SOPs or quick email responses. Since then, AI has evolved non-stop, widely expanding its offering and capabilities for IT Service Management (ITSM).

Progress Flowmon is a core network monitoring and security tool. Confirming if it is up and running can mean the difference between responding to a data breach or overlooking such a critical event. Like any other critical system, it is a good practice to include the monitoring of Flowmon uptime, resource consumption and health in an IT infrastructure monitoring (ITIM) dashboard, such as Progress WhatsUp Gold.