Riverbed today launched a revamped artificial intelligence for IT operations (AIOps) platform that makes use of an expanded ability to collect data via agent software the company has developed and third-party data sources.
As part of that effort, the company also added a unified agent for collecting data, a Riverbed Data Store to centralize the management of data, a Topology Viewer for mapping devices connected to a corporate network and Riverbed Aternity Mobile, a monitoring tool for Apple iOS and Google Android devices.
Finally, Riverbed is extending its network performance monitoring (NPM) platform delivered via a cloud service by adding a network profiling capability along with integration with the Riverbed Unified Agent.
Riverbed IQ 2.0 is a software-as-a-service (SaaS) platform for enabling AIOps that makes uses of machine learning algorithms to automate a range of IT operations tasks. This latest update expands the library of 170 pre-built triggered remediations based on Riverbed Aternity Mobile. Additionally, there is now support for custom tags and pre-configured runbooks that can be invoked as needed.
In general, there is no shortage of approaches to AIOps platforms. Riverbed, however, is using its network management platform as a foundation for collecting a range of data to unify observability in a way that can be used to automate the management of anything connected to the network.
Riverbed CTO Richard Tworek said organizations should soon expect Riverbed to expand those efforts to include generative AI capabilities to further automate workflows using AI assistants. The overall goal is to reduce the level of expertise required to successfully manage IT environments that continue to become more complex as more endpoints are added to distributed networks, he added.
Each IT organization will need to determine how many AIOps platforms might be required to manage IT operations that span networking, security, storage, servers, endpoints and applications. Riverbed is betting that as a provider of network management services it is in a better position to extend the reach of an AIOps platform that can correlate often conflicting data, noted Tworek. That capability is critical in an era where the reliability of an AIOps platform is directly tied to the quality of data used to train it, said Tworek.
It’s not clear what impact AIOps will have on demand for IT services management (ITSM) expertise. The one thing that is certain is that as IT environments become more complex, most organizations can not hire a small army of IT professionals to manually manage workflows. Each IT professional will soon find themselves augmented by multiple AI assistants that will asynchronously perform multiple tasks on their behalf. IT professionals will still be needed to ensure those tasks are performed accurately.
In the meantime, IT teams should start assessing now which tasks are likely to be automated soon using AI. Once that becomes clear, it then becomes simpler to determine how IT teams might need to be reorganized once the need for various specialists becomes less pronounced. While AI may not eliminate the need for IT professionals, there is no doubt at this point that just about every role within those IT teams is never going to be the same again.
