The Auto-Pilot feature for suggestion implementation in Intel Granulate’s Kubernetes improvement solution has been released. Intel Granulate, a company acquired last year by Intel, is a pioneer in real-time continuous application performance improvement. With this feature, Kubernetes users may choose to enable autonomous optimization, which adjusts resource demands and HPA settings automatically and constantly in real-time to save “up to 45% on CPU and memory overhead while still meeting user performance requirements.”
Whether using Kubernetes self-managed, through EKS, AKS, GKE, OpenShift, or even a federated cluster, this may be seen as a major improvement that might be very helpful to DevOps workers. In addition to optimizing at the Kubernetes layer, the Auto-Pilot feature would easily combine with Intel Granulate's special app-level optimization powers.
“Comparing this dual-level optimization to rival products that are just focused on bin-packing or Kubernetes rightsizing, we can achieve both improved performance and reduced costs,” said Asaf Ezra, CEO of Intel Granulate. “With this added auto-pilot capability to Intel Granulate’s capacity optimization, we are able to offer a holistic solution that empowers Kubernetes users to reduce overprovisioning while avoiding higher latency and throttling.”
For developers in charge of orchestrated applications, Intel Granulate's Kubernetes Optimization solution would offer a number of special advantages including:
- Get Rid of Over-Provisioning – Users may let Auto-Pilot adjust workloads and only pay for what they use
- Optimize the whole cloud stack - By combining Kubernetes rightsizing with autonomous runtime optimization, users may achieve comprehensive, multi-level performance gains
- Become fully customizable and able to see your clusters - To find CPU, memory, and cost-saving options, users may tailor their capacity optimization to application’s requirements, whether per cluster or label
- Guarantee optimum performance – Users may lower Kubernetes expenses without sacrificing stability, availability, or resilience while maintaining competitive SLAs
About Intel Granulate
With real-time, continuous application-level performance optimization and capacity management on any kind of workload, Intel Granulate would enable corporations and digital native companies to reduce compute costs associated with on-premises and cloud computing. The AI-driven solution, which is available in the AWS, GCP, Microsoft Azure, and Red Hat markets, would optimize workloads and capacity management automatically and constantly during runtime without requiring changes to the code.
A range of optimization solutions is provided by Intel Granulate, which supports resource management technologies like Kubernetes and YARN, big data infrastructures like Spark, MapReduce, and Kafka, and containerized architecture. Intel Granulate offers optimization solutions for all major programming languages, including Go, Java, Scala, and Python, to DevOps teams.
