ScienceLogic, a provider of AI-driven monitoring solutions for hybrid cloud management, has raised US$105 million (€86.38 million) in growth financing. Silver Lake Waterman led the company's Series E round with participation from existing investors Goldman Sachs, Intel Capital and NewView Capital. The investment will support the company's continued innovation in the AIOps market and further broaden ScienceLogic's position within the $30 billion (€24.68 billion) IT Operations Management software market. Companies across the globe are adopting cloud strategies and tools more than ever amid the COVID-19 pandemic, with massive demand for digital services and scalability. We believe ScienceLogic is poised to meet that demand as organisations look for hybrid-cloud toolsets from trusted partners to securely harness business agility, cost savings and innovation.

You've probably heard this term used over and over again as the next big thing in IT management. But what exactly is AIOps? And why should you care about it? AIOps or artificial intelligence for IT operations is a term first coined by Gartner. It is the application of advanced analytics--in the form of machine learning (ML) and artificial intelligence (AI), towards automating operations so that your IT Ops team can move at the speed that your business expects today.

You've probably heard this term used over and over again as the next big thing in IT management. But what exactly is AIOps? And why should you care about it? AIOps or artificial intelligence for IT operations is a term first coined by Gartner. It is the application of advanced analytics--in the form of machine learning (ML) and artificial intelligence (AI), towards automating operations so that your IT Ops team can move at the speed that your business expects today.

It is hard to believe it was less than half a year ago we were still putting the final touches on SL1 – the engineering teams hard at work making sure the platform was ready, the marketing team getting logos, branding and messaging polished. Our goal when we launched SL1 was to refashion what AI and ML meant to the IT operations, DevOps and IT management community. We'd been watching for years as ephemeral, complex IT infrastructure became the enterprise IT norm and consequently threaten enterprises by that complexity. We realized the market had an emerging need for a solution that could manage that complexity and help IT organizations build and maintain the resilient, robust digital experiences that were growing in demand. By now you are all familiar with the story – we started with the basic premise that enterprises needed greater visibility into their IT ecosystems, the context to understand that visibility, and then the tools to act on what they found.