Containers are now the modern application standard. Turbonomic optimizes container platforms on any cloud or infrastructure.
Intelligent Cluster Scaling
No thresholds or autoscaling policies to set! Turbonomic AI-powered decisions account for all resources and full-stack interdependencies.
Continuously Optimizing Performance, Compliance, and Cost
It's about 24/7/365 intelligent automation. Because you were destined for bigger things.
Underlying Resources Always Service Demand
Turbonomic provides continuous workload placement actions at the container and VM level. Whether a Kubernetes Pod, Cloud Foundry Container, or VM placement decisions are based on container demand for memory and CPU and the available supply of VM and host resources, including CPU, memory, network, IO, ready-queue, swapping and ballooning. The analytics automatically account for affinity/anti-affinity rules, as well as resource quotas.
Workloads that peak together are automatically redistributed to satisfy their exact resource needs and avoid “noisy neighbor” contention.
Turbonomic optimizes every layer of the stack, from containers through infrastructure. You and your teams have a common source of truth.
Key features & benefits
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Continuously Optimize Container Platforms
When container workload demand increases, Turbonomic will automatically scale the underlying node (or cell) and determine which host and datastore to run it on. That's full-stack optimization the easy way.
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When a container workload requires additional CPU or Memory, Turbonomic can scale the workload, while fully understanding the availability of the underlying resources. It assures performance, while you avoid the work of setting static thresholds. Rightsizing a container also ensures you are cloning the best configuration possible when horizontally scaling. Booyah.
Resource fragmentation occurs when the CPU and Memory requirements of new container workloads cannot be scheduled to a node (or cell). Turbonomic avoids this issue by rescheduling existing container workloads before placing new workloads.
In this example, CPU/Memory from the dark gray pod on “Node 2” would be rescheduled to “Node 1” to make room for the new pod on “Node 2.”
Want to learn more? We have a Resource Center where you can find all of our latest and greatest content around container platform optimization.
No Latency Due to Resource Fragmentation
No Noisy Neighbor Contention
AI-Generated Continuous Placement & Rescheduling
Turbonomic is continuously analyzing the environment and providing actions to optimize it. You can set Turbonomic to full automation--executing actions in real time--or you can execute the actions during change windows.
It's your journey, your choice.
Full-stack Control Unites Teams
Optimization on Any Hybrid or Multicloud
Turbonomic continuously makes the right resource decisions at the right time so you don't have to. Watch this webinar preview to see just how smart its actions are. Or, watch the full webinar to learn how Turbonomic makes Amazon EKS, Azure AKS, Google GKE, and Pivotal PKS self-managing anywhere in real time. That's SMART.
Minimal Human Intervention
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Better Rightsizing, Better Scaling
Intelligent Cluster Scaling
Organizations are adopting containers to bring apps and services to market faster. Container platforms provide the building blocks to manage and orchestrate containerized environments, but it's still on you to optimize them.
What would you do differently, if software optimized it for you?
Turbonomic supports any upstream distribution of Kubernetes, as well as Cloud Foundry and Mesos.
Container workloads rely on nodes or cells that can service demand. Turbonomic places nodes or cells on hosts or storage with the right resource capacity to ensure container workloads get what they need when they need it.