AT A GLANCE
vRealize AI Cloud is a secure SaaS service that uses Reinforcement Learning to continuously learn, adapt, and optimize your infrastructure KPIs to deliver consistent and optimal performance for your application workloads
BENEFITS:
- Improved infrastructure performance – up to 60%
- Reduced monitoring effort – up to 15 min per day
- Reduced support tickets/escalations – up to 5 tickets per month
STORAGE POLICY GENIE:
- Analyzes infrastructure and provides recommendations for improving performance or capacity and factors and cost of changes on a net benefit score
vRealize AI Cloud is an artificial intelligence and machine learning solution used to continuously optimize infrastructure operations and configure KPIs of dynamic modern apps
Overview
Today’s IT datacenters are complex and dynamic. IT teams continuously add new technologies while having to maintain legacy deployments. But no matter the environment, the goal is clear - maintaining optimal performance and constant balancing of system resources. Workloads are deployed on physical servers, virtual machines, containers, Kubernetes, or cloud-native applications. These workloads constantly change, move and share resources within the same hosts. Clusters that may have been initially configured to support legacy applications are now hosting modern workloads which no longer follow best practice considerations. These different deployments create IT complexity, which can hurt performance, efficiency and drift from SLA requirements.
No matter where companies host workloads - on-prem, private, hybrid, or multicloud environments - they need optimal performance across any platform to meet customer requirements and SLA agreements
VMware vRealize AI Cloud is an intelligent, self-tuning service that uses
reinforcement learning to continuously adapt to the changing needs of your
application workloads. Through data collection and machine learning, it analyzes
performance KPI’s to not only predict performance improvements but also
dynamically self-tunes VMware SDDC and vSAN parameters to give you the best
performance results.
vRealize AI Cloud uses machine learning and reinforcement learning techniques
to intelligently and continuously optimize VMware infrastructure operations,
starting with the first release of vRealize AI Cloud to optimize vSAN performance.
The service learns about your operating environment and adapts to changing
dynamics, ensuring optimization per the stated KPI.
SaaS datalake and on-prem data collections enable real-time and historical
observability. IT teams can reduce or eliminate repetitive manual processes with
guardrails in place to limit negative impacted performance. And companies
improve application workload performance by evaluating all possible VMware
SDDC tunables to select the optimal configuration.
The latest version includes a preview of the Storage Genie Policy engine that
analyzes and predicts performance, capacity and evaluates the complexity (cost)
of that change to trigger recommendations based on a net performance or
capacity improvements benefit score. The recommendations suggested by the
Storage Genie Policy engine help:
- Suggest changes to default storage policy
- Review multiple alternatives with differing trade-offs and explanations
vRealize AI Cloud‘s is a performance optimization engine that uses machine
learning and reinforcement learning techniques to continuously learn, adapt, and
optimize your storage KPIs. This helps deliver consistent and optimal performance
for your mixed application workloads. As workload applications scale out or
migrate to different datacenters or clusters, vRealize AI Cloud will dynamically
adjust vSAN tunables to continuously optimize KPIs such as I/O read and write
throughput or reducing network latency.
Other 3rd party analytic solutions do not collect and analyze the data, but instead
take decisions on mere utilization and available resources to optimize
performance. vRealize AI Cloud takes a proactive approach to optimize
infrastructure and application performance with its self-tuning of VMware SDDC
tunables.
