In the brave new world of new Hybrid Datacentre, management, control and monitoring of the application estate and its underlying infrastructure is increasingly challenging. Implementing real-time monitoring, empowered by AI-based analytics, for all key applications and infrastructure is the only way to measure, control and ensure end to end performance and availability. Legacy silo-specific monitoring tools are no longer adequate as they can’t communicate or relate to one another and have no understanding of the Applications, their service level requirements that are running on their components. Application Performance Management tools (APM) alone can’t ensure performance and frequently can’t identify the root cause of performance degradation, especially those rooted in some part of the I/O path, such as the network or storage infrastructure. With the advent of the Internet of Things (IoT), the increasingly collaborative and global nature of business, and adoption of Cloud services, that infrastructure is getting more and more complex to manage.
There is a relatively new monitoring space; categorized by Gartner as AIOps (Artificial Intelligence Operations) which encompasses the areas of Application, Infrastructure and Network monitoring. The promise is that AIOps will help make sense of the increasingly complex Enterprise Datacenter landscape; Hybrid Cloud, Big Data, layers and layers of infrastructure and its associated management tools and from them, almost constant alerting all of which are making it almost impossible for operations teams to deliver on their SLAs back to the business. With this in mind, AI and ML based tools are designed to augment the work that operations and infrastructure teams do in order to manage this increasingly complex and dynamic Hybrid Cloud world. The challenge here is that, when walking the expo floor of any trade show these days, all IT tool vendors claim they provide an ‘end-to-end’, real-time, single pane of glass view, with AI and ML thrown in so it is confusing as to who should be believed!
With this in mind, Bloor Research, a UK based independent IT analyst, have created a survey of the key issues related to vendor functionality. The objective of the survey is to try and map the various vendor solutions against two critical business issues:
- The mix of complexity of the infrastructure and volume of activity to be monitored.
- The likely immediacy and impact of performance degradation or outages on the business.
It provides clarity on the positioning and segmentation of some solutions for vendors and users alike.
As you can see, we are proud to see that Virtana has been recognized as the clear leader in this analysis. Virtana combines deep infrastructure visibility with AI-based analytics to empower IT teams to proactively optimize performance, availability, capacity and efficiency. It helps eliminate fragmented, reactive, and ineffective tools that slow problem resolution. Many of the worlds largest enterprises rely on Virtana to assure the critical applications that are running their business.
To download the complete report please click here: Bloor Report
Further information is available from:
www.bloorresearch.com/technology/hybrid-infrastructure-management/
James Bettencourt
