ZeroStack, a start-up based in Mountain View, California focused on self-driving private clouds, unveiled its roadmap and first suite of artificial intelligence (AI) capabilities derived from machine learning.
ZeroStack’s intelligent cloud platform collects operational data and leverages machine learning to help customers make decisions about capacity planning, troubleshooting and optimized placement of applications.
ZeroStack said its vision is to extend existing functionality in three phases:
- First, a suite of capabilities that deliver the self-driving capability in three levels of ‘cognitive’ capacity planning, a state machine to perform ‘hands-free’ upgrades, and ‘intelligent’ optimization, to manage virtual machine (VM) sizing. These capabilities guide the user to optimized use of infrastructure.
- Next, ZeroStack will release a cloud optimization suite, including a broker that will assist with workload placement for best cost / performance outcomes.
- The third component is automated performance troubleshooting. The capability will assist in identifying the root cause of application performance issues, such as correlating application performance with CPU, memory and IO metrics and identifying anomalies that may have caused poor performance. These capabilities can also be used to detect potential security issues.
“ZeroStack has continually worked to reduce IT’s I&O burden for enterprise customers, and our AI software strategy points the way to the future of IT operations,” said Kamesh Pemmaraju, vice president of product management at ZeroStack. “As placement and management of customer workloads increase datacenter complexity, AI will be a key requirement for cost-effective management, and we are at the forefront of using this technology.”
