Demos

This demo showcases multi-cloud Kubernetes orchestration through Taikun Cloudworks enhanced by Arctos Labs ECO.

In the demo, we optimize across multi-clouds provided by AWS, Azure, and Zadara, as well as private clouds, all of which are managed through Taikun Cloudworks.

ECO takes the role of optimizing how these locations are being utilized in a cost-optimized way considering QoS requirements.

ECO generates in the demo Terraform configurations that are used to instruct Taikun Cloudworks on the operations needed.

ECO is used in this demo to optimize the selection of User Plane Functions (UPFs) in a 5G slice orchestration scenario.

The challenges addressed are to enable autonomous networks that cater to the vast number of service variants in the mobile private networks, thereby enabling the long-tail nature of this emerging business.

The solution in the demo is developed in collaboration with Inmanta and FNT software.

Features highlighted are policy control to define specialized slice types, cost optimization, and constraints fulfillment for requirements on latency.

ECO is in this demo used to optimize the compute capacity and its distribution across a set of candidate edge infrastructure locations intended to serve a high number of services.

Features highlighted are cost optimization across compute and data transport with a complex non-linear cost model, and constraints fulfillment for requirements on latency.

ECO is here used as a placement engine in an infrastructure planning scenario.

ECO optimizing placement across multiple on-prem and public k3 clusters.

Features highlighted are cost optimization across compute and data transport, resource awareness for small footprint locations, constraints fulfillment for requirement on latency, cloud-bursting / moving back to on-prem on demand.

ECO is here used as a placement engine as part of application deployment.

ECO optimizing placement across multiple Openstack datacenters.

Features highlighted are cost optimization across compute and data transport, resource awareness, assurance for resilience, constraints fulfillment for requirement on latency.

ECO is here used as a placement engine as part of application deployment.