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1) A single Cloud Region needs to be able to manage multiple distributed (typically Edge) physical DCs
2) Standardized representation of Multi-vendor Cloud Object Hierarchy for aggregate
- Aggregate objects (Cloud Region, Tenants, DCI Overlay etc.)
...
- Atomic objects (VMs, Containers etc.)
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- Resource (CPU, Memory, Network etc.) allocation statistics and resource utilization metrics
3) Standardized representation of Multi-vendor Cloud Analytics
- Events (E.g. VM Power On/Off),
- Alerts (E.g. Cloud Region CPU Usage exceeds threshold)
...
- and
- Faults (E.g. Loss of Redundancy from a Host NIC perspective)
- Policies for correlating between various Events, Alerts, Faults
4) Near-real-time Streaming Data Management
- Resource (CPU, Memory, Network etc.) Utilization Metrics
- Analytics (Events/Alerts/Faults)
5) Inter-Cloud (typically Edge) Workload (especially Data Plane) including Policies4) Inter-Cloud Workload Placement/Scheduling/Change Management decisions to leverage metrics , especially latency and bandwidth, and analytics information at an aggregate object level
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Wind River: Gil Hellmann, Bin Yang
Reviewers
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Huawei: Zhipeng Huang
AT&T: Arun Gupta, Alok Gupta
VMware: Richard Boswell
Planned Next Steps on Document:
- Update to Use Sub Committee
- Update to Modelling Sub Committee