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How we solved the BIG Kubernetes Automation challenges:


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Challenge 1:

Kubernetes cluster management is complex, time consuming and resource intensive.

It requires a lot of expertise due to its highly dynamic nature.

And involves making multiple architectural decisions and modifications along the way - leading to unnecessary waste of resources and increasing costs.



Fully automated, container-driven scaling that perfectly matches Kubernetes workload requirements to compute resources and frees DevOps from tedious cloud infrastructure management.

Challenge 2:

Kubernetes workloads come in various shapes and sizes - there’s no one-size-fits-all and each workload is its own snowflake.

Setting this up involves making multiple architectural decisions without the ability to get a 360 view of all applications and the infrastructure options available.

Inevitably, this is prone to failure by design, leading to a tremendous waste of resources (e.g. over-provisioning and mismatches between container resource requirements and underlying compute nodes) and increasing costs.



Flexible node group management and right sizing allows you to run different applications with different compute requirements, on appropriate instance types and sizes all within a single cluster.

AI-driven prediction of spot instance interruptions and advanced rebalancing of workloads across an optimal blend of spot, reserved and on-demand capacity, delivers extreme cost reduction for even production and mission-critical workloads.

Challenge 3:

Achieving and maintaining application availability while consumption is dynamic and ever-changing and continuous infrastructure maintenance (debugging, upgrades, monitoring) is essential and cannot be avoided.critical for workload continuity and customer satisfaction.



Intelligent and controlled implementation of infrastructure overprovisioning that allocates just the right amount of “headroom” or spare resources, available for whenever applications need to scale out.

This allows applications to instantly scale out as there’s absolutely zero seconds of infrastructure prep, as the nodes are already there.

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