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Device42 today announced it has added support for additional platforms to an AIOps tool that enables organizations to discover IT resources residing in the cloud and in on-premises IT environments.
As enterprise IT environments become more extended, platforms are being added in a way that is not always immediately discernible to a centralized IT team. Developers, for example, now routinely spin up virtual machines on public clouds without any intervention on the part of an internal IT team required.
AIOps tools from Device42 employ machine learning algorithms to create device and application topologies and impact charts that surface all the IT infrastructure being employed across a hybrid cloud computing environment. The latest update adds the ability to also discover cloud databases, along with other types of cloud services — in addition to storage resources in on-premises IT environments.
Those assets are discovered using the application programming interfaces (APIs) that have been exposed by cloud services providers and IT vendors that provide infrastructure for on-premises IT environments. Once all those assets are mapped, it becomes possible for IT teams to employ a search function to uncover, for example, dependencies between multiple services being employed, Device42 cofounder and CEO Raj Jalan told VentureBeat.
Challenges at scale
Not every IT organization may need an AI platform to keep track of its IT assets. But the larger an organization becomes, the more challenging it is to monitor what infrastructure is being employed where and for what purpose. Cloud services, especially, tend to be dynamically consumed, which makes trying to keep track of usage manually nearly impossible. It’s not uncommon for IT organizations to find themselves being billed for cloud services they had no idea where being employed until the invoice from the cloud service provider arrived.
At the same time, more application workloads are now starting to be pushed out to the network edge in places centralized IT teams often have no way to physically reach.
With the addition of each new platform to an IT environment, the probability an organization is going to run afoul of one compliance regulation or another increases, Jalan noted. The Device42 platform makes it easier for IT teams to uncover potential issues long before any audit might, he said.
This capability can also play a role in helping IT teams discover application workloads they may want to move from on-premises IT environments to the cloud or vice versa.
Future of AIOps
Overall, the rate of change in IT environments is accelerating as organizations add, for example, Kubernetes clusters to run microservices-based applications that are being rolled out by a line-of-business unit. IT organizations now need AIOps capabilities to keep track of the changes and updates being made across an extended enterprise. “IT has become too complex to run without it,” he said.
Longer-term, it’s not clear to what degree AIOps will remain a discrete concept or simply become part of the IT service management (ITSM) firmament. At some point, every ITSM tool is going to be infused with machine learning algorithms to some degree. Of course, many IT professionals are dubious about the capabilities of AIOps platforms. But the longer machine learning algorithms are employed, the more accurate they become since they continuously learn from their environment.
As the overall size of the IT environment continues to expand, increasing the size of the IT staff needed to manage it become financially impractical. It’s now only a question of to what degree AI will be employed to augment IT teams that have no other viable way of managing modern IT environments.
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Author: Michael Vizard
Source: Venturebeat