VMware is moving to make it easier for organizations to automate data centers and public cloud based on its core hypervisor technology by injecting advanced analytics into its VMware vRealize Suite, enabling them to manage IT environments based on intent rather than having to manually manage every process themselves.
At the core of those update is the Capacity Analytics Engine, which is being added to version 6.7 of vRealize Operations. Mahesh Kumar, senior director of product marketing for cloud management at VMware, said the capacity analytics engine makes use of Autoregressive Integrated Moving Average (ARIMA) techniques to forecast future system events based on historical data points that identify a long-term trend of sudden spikes in usage. Armed with that data, vRealize Operations can now provide cost analytics that include advice on ways to adjust application size and reclaim idle resources on either a public cloud or inside a local data center. IT organizations can also run “what if” scenarios, Kumar said.
On top of that capability, VMware is also now adding predictive analytics that enables IT organizations to define a set of intents such as workload balancing to reduce software license cost, prioritize one set of application to maintain a service level agreement (SLA) or make sure certain workloads only run on servers that have been shown to comply with a specific regulation or mandate. Tighter integration between vRealize Operations 6.7 and vRealize Automation 7.4 then can be continuously employed to automate DevOps processes in a closed-loop manner at higher levels of scale without having to add additional headcount, Kumar said.
In addition, the latest version of VRealize Automation includes more than 120 free, curated blueprints and OVF (Open Virtualization Format) files out of the box. VMware has teamed with Bitnami to add 20 new blueprints and 100-plus new OVFs of applications and databases including GitLab, Hadoop, Jenkins and MongoDB to speed application development and deployment. VMware also updated the Custom Form Designer and added multitenancy capabilities.
Finally, VMware vRealize Operations is sporting a new user interface and integrates with VMware Wavefront monitoring software.
Longer term, Kumar said vRealize Operations will be where VMware applies machine learning algorithms to enable artificial intelligence (AI) models to automate the management of VMware environments.
Collectively, Kumar said the VMware vRealize Suite moves IT organizations that have standardized on VMware in both their local data centers and in the public cloud much farther down the DevOps maturity curve. In effect, VMware vRealize Suite creates an “easy button” for managing complex VMware environments spanning multiple clouds, Kumar said.
VMware is also betting that AI models will make it a lot easier for organizations to make a cultural adjustment as the management of compute, storage and networking becomes more unified. It’s not clear how long it will take for those machine learning algorithms to manifest themselves in VMware management software. But it’s clear most IT organizations running VMware soon will need to rethink who is responsible for running what inside an IT operations team.