Kubernetes Native Infrastructure and Operator Framework for 5G Edge Cloud Computing - Hyde Sugiyama - Chief Architect, Red Hat K.K.
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Kubernetes Native Infrastructure and Operator Framework for 5G Edge Cloud Computing Hyde Sugiyama - Chief Architect, Red Hat K.K.
OpenShift/K8s on OpenStack NFV session@OSS2018
OpenShift on OpenStack NFV
B2B2X for SoE apps in OpenShift
(in VM) on top of DCN(NFVI)
2NFV Evolution to Kubernetes
Y2018-2019 Y2019-2020 Y2020-2021
70 30 50 50 30 70
(IT SoE apps (Stateless & Stateful
VNF
VNF Container VNF Container VNF Container
VNF Container
K8s/OCP CNF CNF
CNF
Hypervisor Hypervisor Hypervisor
Kubevirt
OpenStack OpenStack K8s/OCP4 OpenStack K8s/OCP4
Bare Metal Bare Metal Bare Metal
Data Lake Data Lake Data Lake
SoE: System of Engagement OCP4: OpenShift Container Platform 4
3Innovation - 2019
4G
All IP packet
5G
5GC
Carrier Cloud native/Service Based Archtecture
Grade
CP and UPF separation
Linux Network
Function Network slicing
Virtualization UPF offload (FPGA, Edge Switch Fabric)
Distribute vRAN CU-DU split
Compute
Heterogeneous Computing
Node
DPDK(vCPU)
VNF Multiaccess
Edge CNF GPU
FPGA
Computing
Autonomous micro edge cloud
Edge AI platform(Intelligent Edge)
Data Lake /Data Hub
4Performance Sensitive Application Platform
OpenShift 4 becomes the 5G/Edge
single platform to run any Machine FSI
Learning
application:
HPC ISVs
● Old or new
● Monolithic/Microservice
Big Data Animation
6Possibility for NFV architecture change by adapting
Kubernetes Operator(w/ OpenShift Operator framework)
API management
OSS/BSS NFVO
OSS/BSS
=VM= =VM= =VM= =Pod= =Pod= =Pod=
VNF+ VNF+ VNF+ CNF CNF CNF
guest guest guest VNF-M (SMF) (UDM) (...)
OS OS OS
CNF-M CNF-M CNF-M
OpenShift
Cluster Operator
= Hypervisor= OpenShift Worker Master
VIM
NFVI (host OS) (host OS)
BM(s) BM(s)
VNF CNF
7Kubernetes Operator
● Automate day 2 lifecycle management of
containerized applications in Kubernetes
● Leverage CRDs to deploy Kubernetes native LIFECYCLE
services that can access Kube API events SDK METERING
MANAGEMENT
● Operator SDK simplifies creation of Operators in
Go (or leverage Helm or Ansible automation)
● Helm Operator allows you to convert Helm Charts
into Operators
○ Deploy Charts without requiring Tiller
○ Leverage Kube RBAC to deploy Charts
○ Automated, over the air updates for Chart
deployed services
Implementation pattern of "SRE (Site Reliability Engineering)"
that incorporates operations by software
https://www.youtube.com/watch?v=LymzLHRbQdk
8Full-Stack Automated Operations in OpenShift
APPLICATIONS AND SERVICES
ISV Operators
Custom Operators (built w/Operator SDK)
PLATFORM AND CLUSTER MANAGEMENT
Automated updates for Kubernetes,
monitoring, security, registry and more
LINUX HOST
Over-the-air updates for Red Hat CoreOS
ANY INFRASTRUCTURE
95GC system architecture
Network
Slice
Selection
Function
Access &
Mobility mgmnt
Function
User
Plane
Packet Function
Forwarding AUthentication
Control Server
Protocol Function
Policy
Control
Function
Unified
Data
Management
Session
Data Management
Network Function
Data Network
11KIALI ( GUI for Istio )
5G SBI and Service Mesh
OPENSHIFT SERVICE MESH
● A dedicated network for service to
service communications
● Observability and distributed tracing
● Policy-driven security
● Routing rules & chaos engineering
● Powerful visualization & monitoring
● Will be available via OperatorHub
12Service Mesh 5GC SBA and KNI(Kubernetes Native
Infrastructure) provider extensions
Network
Slice
Selection
Function
Istio MULTUS CNI setup, Access &
service Stateful management, Mobility mgmnt
Function
mesh CNF LCM, K8s LCM, Network
etc Repository
Function
AUthentication
5GC Server
Function
Policy
Control
Function
Unified
Data
Management
User Equipment Session
Management
Function
GPU device plugin, DPDK, FPGA,
Serverless, Data lake, etc
135G UPF and Network Slicing in Cloud edge fabric for
B2B2X workloads and etc
Multi cluster for istio Slice 1 for
service mesh might be B2B2X workloads 1
needed : SMF1 & UPF1
Slice 2 for
B2B2X workloads 2
: SMF2 & UPF2
* https://www.youtube.com/
* * watch?v=1X5U4Jo0Jlw
UE https://www.pilab.jp/ipop2
**
019/exhibition/WhitePaper
_iPOP2019.pdf
**
14O-RAN alliance &
RAN Cloudification w/
Kubernetes
153GPP &
O-RAN alliance Design Inventory Policy Configuration RAN Intelligent Controller (RIC)non-RT
Orchestration & Automation (e.g. ONAP): MANO, NMS
A1
3GPP (e/g)NB RAN Intelligent Controller (RIC) near-RT
Applications
E
3rd party
Layer 2 Radio Connection Mobility QoS Interference Trained
APP Mgmt Mgmt Mgmt. Mgmt Model
Radio-Network Information Base
3GPP CU E2 :btw RIC near-RT and O-CU/O-DU
Multi-RAT CU-CP CU-UP
RRC E1 SDAP
O-CU Protocol
Stack PDCP-C PDCP-U
Our focus NFVI Platform: Virtualization layer and COTS platform F1
OpenStack,
OpenShift/k8s
O-DU: RLC/MAC/PHY-high
Open Front Haul
3GPP DU
O-RU: PHY-low/RF
16O-RAN alliance WG6
Decoupling of software from hardware for all RAN modules in all splits
S/W Flexible O-CU O-DU O-RU All RAN modules
Orch.
Inventory, Support 10,000s
H/W Discovery, H/W abstraction layer
of distributed
Registration
Policy,
NFVI stack (containers or VMs), OS, cloud m-plane cloud sites
Blackbox Metrics
BBU Heterogeneous
Common
LCM computing
mechanisms
Multitude of deployment
models: CloudRAN,
Centralized CU/DU CU/DU split
CU-DU split,
Distributed
(C-RAN) CU/DU dRAN on whitebox or DC
(D-RAN)
17Candidate WG6 Scenarios B,C
Scenario B: Distributed vO-CU and vO-DU
BBU chassis at cell site
Near-RT vBBU
vO-CU +
To UPF RIC E2 vO-DU
Open fronthaul O-RU The O-CU/O-DU functionality can be
& MEC 1:N, remote 1:m, local
NFVI NFVI Cell site pooled from multiple O-RUs, and meet
Regional cloud Open chassis and blade spec O-DU latency requirements.
K8s or OpenStack Cell site area
Near-RT RIC can serve a very large
number of O-RUs
Scenario C: Centralized vO-CU with distributed vO-DU
O-DU chassis at cell site
Near-RT
vO-CU vO-DU Open fronthaul
To UPF RIC F1 O-RU The O-DU functionality can be pooled
& MEC 1:N, remote 1:m, local
NFVI NFVI
Cell site
from multiple O-RUs, and meet O-DU
Regional cloud Open chassis and blade spec
latency requirements.
K8s or OpenStack Near-RT RIC can serve a very large
Cell site area number of O-RUs, and O-CU is very
centralized.
18KNI Edge
Kubernetes
Native
Infrastructure
for Edge
19Akraino Edge Stack project
KNI-Edge Blueprints (in Progress)
Provider Access Edge (PAE) Industrial Edge (IE)
Optimized for real-time and Optimized for small footprint and
networking performance for low-latency for IoT, serverless, and
Containerized vRAN and MEC workloads. machine learning workloads.
MEC Apps VM1 ... VMN ML Apps Srv-less ML Apps IoT Apps
vRAN URLLC
Apps
(RIC) MEC MW KubeVirt Kubeflow Apps Kubeflow EdgeX
kNative
Cluster/ Prometheus Cluster/ Prometheus
Machine OpenShift/OKD + exporters Machine OpenShift/OKD + exporters
Operator Operator
Tungsten Ceph CRI-O OVN/OVS Ceph CRI-O
NOS CoreOS and CentOS-rt NOS CoreOS and CentOS-rt
... ...
switch COTS COTS COTS switch COTS COTS COTS
https://wiki.akraino.org/display/AK/Kubernetes-Native+Infrastructure+%28KNI%29+Blueprint+Family
20IoT Apps - Eclipse IoT project
APPLICATION DEVELOPMENT,
DELIVERY, & INTEGRATION
CONNECTE IoT IoT
D “THINGS” EDGE INTEGRATION HUB
App
integration
Management
Telemetry
Telemetry
Edge
analytics
DATA MANAGEMENT & ANALYTICS
Machine
Management Telemetry
learning CLOUDERA’S DISTRIBUTION
INCLUDING HADOOP (CDH)
Machine learning model
21ML Apps - OPEN DATA HUB
Collaborate on a Data & AI platform for the Edge Cloud & Core
A collection of open source and
cloud components packaged in a
“machine learning-as-a-service”
platform to solve business
problems.
22Collaborate on a Data & AI platform for the Edge Cloud & Core
● AI Library
● Data Science and ETL
Tools
● Streaming and Enriching
Data
● Storing Data
● Managing Data
● Monitoring Infrastructure
23Serverless Apps - Knative
• Familiar to Kubernetes users. Native.
• Scale to 0 and autoscale to N based on demand
• Applications and functions. Any container
workload.
• Powerful eventing model with multiple event
sources.
• Operator available via OperatorHub
• Knative v0.6 (v1beta1 APIs)
• No vendor lock in
Learn more
https://www.openshift.com/learn/topics/knative
24Red Hat OpenShift Hybrid Serverless
Developer experience Function as a Service Invoker Runtime CLI API
APIs, CLI, service binding Red Hat OpenShift Knative Events Build Serving
ODO CLI Eclipse Che
Building blocks for serverless
RH MW Services ISV Services
Source-centric and container- (Operator backed) (Operator backed)
based Operator Framework
Automated
Istio
Operations
The leading enterprise
Hybrid Install / Ops Install / Upgrade Network / CNI
Kubernetes platform
Ops & Dev Consoles Security / Auth Storage / CSI
Automated Operations
Build an run anywhere (Hybrid
Kubernetes
Cloud)
Red Hat Enterprise Linux or Red Hat CoreOS
25Knative Event Sources
Upstream Event Sources:
GitHub
Kubernetes Events
Pub/Sub (AWS SQS, Kafka, NATS, Google PubSub)
Websockets
Expose an ingress
200+ event sources through Camel-K
Camel-K + Knative Demo
https://github.com/knative/eventing-sources
26Serverless IoT Sensor
Java Reports
Java Python Java
IoT API
Gateway
Java JavaScript
(NodeJS)
Archiving
EDGE Private Hybrid Public
27Summary 28
Next Generation DPF(Digital service platform)
Application portability in any environment and consistency in operation.
Application Portability
Container * Container * Container * Container
Container * Container
Container *
Application Application
Application Application
Application Application
Application Application
Application
OS dependencies OS
OS dependencies
dependencies OS
OSdependencies
dependencies OSdependencies
OS dependencies OS
OSdependencies
dependencies
Pod Pod Pod Pod Pod
Easy LCM per microservice, multi-cluster management and federation
Multi Interface, SDN for isolation
RHEL/CoreOS RHEL/CoreOS RHEL/CoreOS RHEL/CoreOS
RHEL/CoreOS
Guest VM Virtual Machine Virtual Machine Virtual Machine
GPU FPGA
LAPTOP VIRTUALIZATION PRIVATE CLOUD BARE METAL PUBLIC CLOUD
Code Ready ** RHV, VMWARE OpenStack NFV Intel, Power, ARM(plan Azure, AWS, Google, etc.
It is also possible to duplicate and store the same
By using UBI (Universal Base Image),
* developers can concentrate on container
container image in geographically distant places
application development at any platform. (utilization of Ceph data lake and QUEY)
** https://github.com/code-ready/crc
29Summary
1. Heterogeneous Computing Platform
2. K8s as AI platform at Telco Edge
a. Data Lake/Hub at Telco node
3. Kubernetes Native Infrastructure on Bare metal across Telco
Core and Telco Edge
a. Operator Framework for Site Reliability Engineering and Provider
extension
i. Autonomous micro-cloud at Telco edge
ii. Digital Service Provider driven CNF apps management
b. Service mesh for micro service
c. Challenge for Serverless at Telco edge node
30Thank you!
hyde@redhat.com
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