An Intellyx Brain Candy Brief
Opsani uses machine learning to adjust multiple cloud instance parameters on a second-by-second basis in order to optimize the cost, performance, and reliability of cloud-based applications and services.
Opsani works with any application in any cloud, but is particularly well-suited for Kubernetes-based applications. In Kubernetes, Opsani automatically creates ‘tuning pods’ that act like staging environments within Kubernetes clusters in order to optimize multiple parameters without adversely impacting the end-user experience as it adjusts various parameters.
Opsani helps system reliability engineers (SREs) manage to their organizations’ service-level objectives (SLOs), especially when those SLOs reflect the customer (or other end-user) experience.
Opsani’s continuous approach to optimization differentiates it from other cloud optimization technologies that focus on the proper selection of cloud instance types and placement of workloads. Moving workloads between instances can take many minutes or even hours, while Opsani delivers optimization in seconds.
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