Pepperdata has announced its new Autonomous FinOps for Kubernetes (K8s) offering. The latest release enables executives, platform engineering and IT ops teams, and finops professionals managing Kubernetes workloads in public clouds to achieve desired economics from compute resources – without manual intervention or code changes.
Existing FinOps tools provide a barrage of optimization suggestions, but these recommendations are often unrealized because engineering teams find them too burdensome to implement at scale. With Autonomous Optimization, however, these concerns are no longer an issue. The AI engine takes care of all the hard work – identifying opportunities for savings, recommending changes that can be made without impacting performance or reliability, and implementing those changes autonomously across an organization’s entire Kubernetes infrastructure.
Customers can take advantage of the following new platform capabilities enable customers to minimize cloud cost overruns and maximize control over cloud budgets:
- Cost allocation and visibility: Achieve container-level cost visibility by breaking down costs by Kubernetes object types to provide a holistic view of FinOps
- Instance Rightsizer: Recommend optimal instance types for workloads to reduce over-provisioning
- Scale optimization: Scale efficiently by using actual resource utilization, intelligent bin packing, and reclaiming waste
- Automatic remediation: Run optimizers continuously and autonomously by analyzing container cost data and runtime behavior
As public clouds have proliferated in recent years, so too have concerns about unpredictable bills and runaway costs. According to Gartner, spending on public cloud services will reach $500 billion by 2022, making ‘FinOps’ – financial operations specifically tailored to manage cloud costs – a top priority for businesses.