Purpose:
Main purpose of F-GPS (a.k.a. ONAP-Valet) is, with considering placement rules, (1) to precisely check capacity & capability of target Cloud Region and then, (2) to determine VNF placements (i.e., target zone or compute host for each workload of VNF).
- Placement rules include Affinity and Anti-affinity.
- Scopes of placement rules are, in a target Cloud Region, across availability-zones and optionally, across compute hosts.
- Applications of placement rules are workloads within a VNF or workloads across VNFs.
- Opportunity to standardize many other placement rules (e.g., Exclusivity, Quorum-Diversity) in VNFD and Policy.
- Integrated into OOF/HAS (maybe initially as dark mode for evaluation in Dublin).
Owner : TBD
Participating Companies: VMware (Architecture/Modelling), Intel (Architecture), AT&T
Operator Support: OOF/HAS, 5G Use Case (TBD)
Parent page: TBD
Use Case Name
| Showcase VNF | Test Environment | Integration Team Liaison |
|---|---|---|
| 5G | TBD | OOF |
5G Data Plane Performance use case:
A VNF instance has 2 workloads (2 VM instances) that must be placed in a same zone (or compute host) because of the high throughput requirement between workloads. Meanwhile, 2 more replicas of the VNF instance must be placed in different zones (or different compute hosts) of the same Cloud Region because of the high-reliability requirements for the VNF.
To meet these requirements, each VNF instance must specify an Affinity rule for its 2 workloads. Meanwhile, the same type of workloads in those 3 VNF instances must specify an Anti-affinity rule.
5G VNF user(s) aware Placement:
Place 5G VNF in a specific DC location/zone in a distributed cloud for user(s) proximity. A single cloud control plane is managing several distributed DC locations/zones.
Dublin Focus:
- Seed code for placement decisions for OpenStack cloud and evaluate in an OpenStack testbed. Later, extend to the other clouds including Azure and AWS.
- Capacity & Capability checking for an OpenStack cloud: 1) Checking the number of zones of the target Cloud Region to solve the Anti-affinity rules, 2) Checking available capacity of each zone to solve Affinity rule, 3) Checking available host profiles of each zone to solve flavor matching (i.e., Host-Aggregates).
- Placement decisions for Affinity and Anti-Affinity among zones of target Cloud Region. Optionally, decisions go into compute hosts (for private cloud case).
- Defining Affinity and Anti-affinity rules in Policy (Stretch Goal). Until this is ready, evaluate with a manual/hard-coded policy.
- Specifying Affinity and Anti-affinity rules in homing/placement request (Stretch Goal). Until this is ready, evaluate with a manual/hard-coded specification.
- Distributed cloud modelling immediately relevant to F-GPS - a single cloud control plane to be able manage several distributed DC locations/zones.
Leverage capacity alerts (significant change in capacity) from Model-driven Distributed Analytics work.
Impacted Projects
| Project | PTL | JIRA Epic / User Story* | Requirements |
|---|---|---|---|
| OOF | Sarat Puthenpura |
| |
| Multi-VIM/Cloud |
| ||
| A&AI |
|
Architecture committee suggestions
On Dec. 4, 2018
- Need end-to-end workflows: The overall flow is ready (below), and detailed will be ready soon.
- Modeling Affinity/Anti-affinity: Investigated ETSI NFV-IFA and turns out that it includes Affinity/Anti-affinity specification per DC (NFVI-PoP), Zone (Availability-zone), and compute server (NFVI-node).
- Modeling Distributed cloud: Each Cloud Region has multiple Availability-zones (DCs)
- Capacity check: Fine grained, per Availability-zone (or DC).